Published Papers - KAZAMA Kazuhiro

Predicting the future citation counts for arXiv preprints immediately after publication

MAEYAMA Kosuke, KAZAMA Kazuhiro, YOSHIDA Mitsuo, SATO Sho, ONAMI Jyunichi

JSAI Technical Report, SIG-KBS ( The Japanese Society for Artificial Intelligence )  133   17 - 24   2024.12

DOI

特集：「地理空間データを利活用した研究の展望」特集「地理空間データを利活用した研究の展望」にあたって

伏見 卓恭, 風間 一洋

人工知能 ( 一般社団法人 人工知能学会 )  39 ( 4 ) 442 - 443   2024.07

DOI

Burst Characteristics Analysis of Altmetrics for Research Papers

Kazuhisa KOBAYASHI, Kazuhiro KAZAMA, Mitsuo YOSHIDA, Ikki OHMUKAI, Sho SATO, Marie KATSURAI

The IEICE Transactions D (Japanese Edition) ( The Institute of Electronics, Information and Communication Engineers )  J105-D ( 5 ) 310 - 321   2022.05  [Refereed]

DOI

Analysis of Leading Communities Contributing to arXiv Information Distribution on Twitter

Kyosuke Shimada, Kazuhiro Kazama, Mitsuo Yoshida, Ikki Ohmukai, Sho Sato

WI-IAT '21: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology     2021.12  [Refereed]

インターネット上のユーザの行動データを用いた論文の普遍性の分析手法

小林 和央, 風間 一洋, 吉田 光男, 大向 一輝, 佐藤 翔

情報知識学会誌   30 ( 3 )   2020.10  [Refereed]

媒介度に基づく道路ネットワークのコミュニティ抽出法

Fushimi Takayasu, Saito Kazumi, Ikeda Tetsuo, Kazama Kazuhiro

Transactions of the Japanese Society for Artificial Intelligence ( The Japanese Society for Artificial Intelligence )  34 ( 5 ) F-wd12_1 - 11   2020.01  [Refereed]

　View Summary

In this study, we address the problem of detecting effective installation sites of signboards and identifying their influential zones for a given road network, under the setting that many residents can view them on their shortest paths to the destinations. To this end, based on a notion of group-betweenness centrality measure, we newly formalize this problem as a k-betweens problem and propose a community extraction method of road networks to identify the influential zones. In an existing method, the influential zone of each signboard is extracted by Voronoi tessellation against its installation site, which assumes that residents view the nearest signboard. In our proposed method, it is extracted by the proportion including the signboard on the shortest paths from the resident’s departure point to various destinations. From experimental evaluations using artificial and real road networks, we confirmed that our method can extract effective installation sites of signboards such as intersection nodes near the entrance of the express highway, and their influential zones as communities according to the positional relationships with arterial roadways. Furthermore, by computing the degree of antagonism among communities using the entropy of betweenness contribution rates, we can quantify the effectiveness of installing the same signboards for residents of areas where the influential zones of multiple signboards overlap.

DOI

Community extraction method of road networks based on betweenness con-tribution

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Transactions of the Japanese Society for Artificial Intelligence ( Japanese Society for Artificial Intelligence )  35 ( 1 )   2020

　View Summary

In this study, we address the problem of detecting effective installation sites of signboards and identifying their influential zones for a given road network, under the setting that many residents can view them on their shortest paths to the destinations. To this end, based on a notion of group-betweenness centrality measure, we newly formalize this problem as a fc-betweens problem and propose a community extraction method of road networks to identify the influential zones. In an existing method, the influential zone of each signboard is extracted by Voronoi tessellation against its installation site, which assumes that residents view the nearest signboard. In our proposed method, it is extracted by the proportion including the signboard on the shortest paths from the resident's departure point to various destinations. From experimental evaluations using artificial and real road networks, we confirmed that our method can extract effective installation sites of signboards such as intersection nodes near the entrance of the express highway, and their influential zones as communities according to the positional relationships with arterial roadways. Further-more. by computing the degree of antagonism among communities using the entropy of betweenness contribution rates, we can quantify the effectiveness of installing the same signboards for residents of areas where the influential zones of multiple signboards overlap.

DOI

cookpadの献立データからのパターン抽出

奈須 日向太, 風間 一洋

第12回Webとデータベースに関するフォーラム(WebDB Forum 2019) ( 日本データベース学会 )    2019.09  [Refereed]

学術情報検索における閲覧論文の文献種別による分析

小林 和央, 風間 一洋, 吉田 光男, 大向 一輝, 佐藤 翔

第12回Webとデータベースに関するフォーラム(WebDB Forum 2019) ( 日本データベース学会 )    2019.09  [Refereed]

Estimating Node Connectedness in Spatial Network under Stochastic Link Disconnection Based on Efficient Sampling

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Applied Network Science   4 ( 66 ) 66 - 24   2019.08  [Refereed]

DOI

A New Group Centrality Measure for Maximizing the Connectedness of Network Under Uncertain Connectivity

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

The 7th International Conference on Complex Networks and Their Applications (COMPLEX NETWORKS 2018) ( Springer )    3-14 - 14   2018.12  [Refereed]

DOI

Improving Approximate Extraction of Functional Similar Regions from Large-Scale Spatial Networks Based on Greedy Selection of Representative Nodes of Different Areas

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Applied Network Science   3 ( 18 ) 43844 - 14   2018.07  [Refereed]

DOI

Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Machine Learning Techniques for Online Social Networks, Lecture Notes in Social Networks (LNSN) Series     43852   2018.05  [Refereed]

リンク切断に頑健な連結中心性とその高速計算法

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋

情報処理学会論文誌：数理モデル化と応用   11 ( 2 )   2018.01  [Refereed]

Fast Extraction Method of Functional Clusters from Large-Scale Spatial Networks Based on Transfer Learning

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

The 6th International Conference on Complex Networks and Their Applications (COMPLEX NETWORKS 2017) ( Springer )    1210-1222 - 1222   2017.12  [Refereed]

DOI

ネットワーク上での特徴量分布を考慮したアノテーション付与法

伏見 卓恭, 佐藤 哲司, 斉藤 和巳, 風間 一洋

情報処理学会論文誌, 特集「ネットワーク科学」   58 ( 6 ) 1246 - 1257   2017.06  [Refereed]

ジオタグ付きツイートを用いた交通路の抽出法

谷 直樹, 風間 一洋, 榊 剛史, 吉田 光男, 斉藤 和巳

情報処理学会論文誌：データベース   10 ( 2 ) 31 - 41   2017.06  [Refereed]

メトリック空間における複数カテゴリに属するハイブリッドオブジェクト抽出法の提案

伏見 卓恭, 斉藤 和巳, 風間 一洋

情報処理学会論文誌, 特集「ネットワーク科学」   58 ( 6 ) 1258 - 1267   2017.06  [Refereed]

一般化ピボットによるL1距離に基づくK-medoidsクラスタリングの高速化

伏見 卓恭, 斉藤 和巳, 風間 一洋

人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )  2017 ( 0 ) 3M11 - 3M11   2017

　View Summary

<p>高次元ベクトルで表現されるデータの増大により，クラスタリング技術が注目を浴びている．ベクトル間の距離計算には多大な計算コストを要するため，L1距離に着目した一般化ピボットを利用し効率的なピボット枝刈りによる高速なK-medoidsアルゴリズムを提案する．実データを用いた評価実験により，クラスタリングの高速化を実現できていることを示す．</p>

DOI

Accelerating greedy K-medoids clustering algorithm with L1 distance by pivot generation

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Springer Verlag )  10352   87 - 96   2017  [Refereed]

　View Summary

With the explosive increase of multimedia objects represented as high-dimensional vectors, clustering techniques for these objects have received much attention in recent years. However, clustering methods usually require a large amount of computational cost when calculating the distances between these objects. In this paper, for accelerating the greedy K-medoids clustering algorithm with L1 distance, we propose a new method consisting of the fast first medoid selection, lazy evaluation, and pivot pruning techniques, where the efficiency of the pivot construction is enhanced by our new pivot generation method called PGM2. In our experiments using real image datasets where each object is represented as a high-dimensional vector and L1 distance is recommended as their dissimilarity, we show that our proposed method achieved a reasonably high acceleration performance.

DOI

Clustering and visualizing functionally similar regions in large-scale spatial networks

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

Journal of Information Processing ( Information Processing Society of Japan )  25 ( 6 ) 398 - 406   2017  [Refereed]

　View Summary

We address the problem of extracting functionally similar regions in urban streets and regard such regions as spatial networks. For this purpose, based on our previous algorithm called the FCE method that extracted functional clusters for each network, we propose a new method that efficiently deals with several large-scale networks by accelerating our previous algorithm using lazy evaluation and pivot pruning techniques. Then we present our new techniques for simultaneously comparing the extracted functional clusters of several networks and an effective way of visualizing these clusters by focusing on the fact that the maximum degree of the nodes in spatial networks is restricted to relatively small numbers. In our experiments using urban streets extracted from the OpenStreetMap data of four worldwide cities, we show that our proposed method achieved a reasonably high acceleration performance. Then we show that the functional clusters extracted by it are useful for understanding the properties of areas in a series of visualization results and empirically confirm that our results are substantially different from those obtained by representative centrality measures. These region characteristics will play important roles for developing and planning city promotion and travel tours as well as understanding and improving the usage of urban streets.

DOI

Proposal of Recipe Search Method by Temporal Representations Based on Temporal Features Derived from Recipe Usage History

桐本 宙輝, 風間 一洋

情報処理学会論文誌：データベース   9 ( 4 ) 11 - 16   2016.12  [Refereed]

　View Summary

本論文では，料理レシピのような永続性が高い情報をユーザが利用する際の時間特性を利用して，指定された時間的状況下で調理されたレシピを，時間表現で検索するための新しい手法を提案する．まず，ユーザが入力した時間的状況を表す言語表現を，それから導かれる時間パラメータと確率密度関数を用いて時間特性を表す特徴ベクトルに変換し，cookpadの「つくれぽ」の頻度変化から求めた特徴ベクトルとのコサイン類似度を求めることで，ユーザが想定している時間的状況で調理されるレシピを発見する．実際に，入力した時間表現とレシピの特徴ベクトルとの類似度が高いレシピを求めて，レシピの内容と特徴ベクトルの確率密度分布の一致度，類似度の値を分析して，入力時に想定した時間的状況によく合致しているレシピが得られることを示す．This paper presents a new method to search recipes, which are cooked under the specified temporal situation, by temporal representations. The method uses temporal features derived from recipe usage history. First, we convert an input language representation about a temporal situation into a temporal feature vector by a probability density function and temporal parameters. Next, we find temporally similar recipes by calculating the cosine similarity between an input feature vector and each recipe feature vector that is derived from frequency variation of cookpad's "Tsukurepo". We analyze the content of recipes, the degree of coincidence between feature vectors, and the values of similarities. In the result, we show that our proposed method is able to search recipes, which are appropriate to user input temporal situation.

ピボットを用いたK-medoidsクラスタリング高速化による大規模機能コミュニティ抽出

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋

第15回情報科学技術フォーラム (FIT2016) ( 第15回情報科学技術フォーラム (FIT2016) )    2016.09  [Refereed]

マルチエージェント型情報拡散モデルの提案

池田 圭佑, 岡田 佳之, 鳥海 不二夫, 榊 剛史, 風間 一洋, 野田 五十樹, 篠田 孝祐, 諏訪 博彦, 栗原 聡

人工知能学会論文誌   31 ( 1 ) NFC-C_1 - 13   2016.09  [Refereed]

Functional Cluster Extraction from Large Spatial Networks

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

The 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM2016) ( IEEE Computer Society )    57 - 62   2016.08  [Refereed]

DOI

Extracting and Characterizing Functional Communities in Spatial Networks

Takayasu Fushimi, Kazumi Saito, Tetsuo Ikeda, Kazuhiro Kazama

The Workshop on Artificial Intelligence for Tourism (AI4Tourism 2016)     2016.08  [Refereed]

複雑ネットワークの機能コミュニティ構造の可視化

FUSHIMI Takayasu, SAITO Kazumi, KAZAMA Kazuhiro

Journal of the Visualization Society of Japan ( The Visualization Society of Japan )  36 ( 141 ) 68-74 - 20   2016.04  [Invited]

　View Summary

In this paper, in order to reveal the characteristics and functions of many networks with complex structure, we explain a framework that extracts communities with different point of view and colors all the nodes of visualization results according to the extracted communities. In real networks, each node has intrinsic functions and roles, and mutually affects on other nodes. In this paper, different from existing community of densely connected nodes, we extract the nodes with similar functions, referred to as functional community. Concretely, we calculate the PageRank score convergence curve of each node and divide all nodes by similarities of these curves as functional community. Finally we color all the node with respect to functional community. From experimental results using artificial and real networks, we confirm that our framework can extract adequate functional communities.

DOI

Proposal of AIDM: Agent-Based information diffusion model

Keisuke Ikeda, Takeshi Saskaki, Fujio Toriumi, Kazuhiro Kazama, Itsuki Noda, Hirohiko Suwa, Kosuke Shinoda, Satoshi Kurihara

Transactions of the Japanese Society for Artificial Intelligence ( Japanese Society for Artificial Intelligence )  31 ( 1 )   2016.01  [Refereed]

　View Summary

During the 2011 East Japan Great Earthquake Disaster, some people used social media such as Twitter to get information important to their lives. However, the spread of groundless rumor information was big social problem. Therefore, social media users pay attention to prevent wrong information from diffusing. The way to stop the spread of a false rumor is needed, so we have to understand a diffusion of information mechanism. We have proposed information diffusion model which is based on SIR model until now. This model is represented by the stochastic state transition model for whether to propagate the information, and its transition probability is defined as the same value for all agents. People ’s thinking or actions are not the same. To solve this problem, we adopted three elements in our model: A new internal state switching model, user diversity and multiplexing of information paths. In this paper, we propose a novel information diffusion model, the Agent-based Information Diffusion Model (AIDM). We reproduce two kinds of false rumor information diffusion using proposed model. One is “single burst type false rumor spread ”, and another is “multi burst type false rumor spread. ”Proposal model is estimated by comparing real data with a simulation result.

DOI

グラフ構造に着目した評価文書の極座標可視化法

伏見 卓恭, 佐藤 哲司, 斉藤 和巳, 風間 一洋

人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )  2016 ( 0 ) 1E41 - 1E41   2016

DOI

Content centrality measure for networks: Introducing distance-based Decay weights

Takayasu Fushimi, Tetsuji Satoh, Kazumi Saito, Kazuhiro Kazama, Noriko Kando

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Springer Verlag )  10047   40 - 54   2016  [Refereed]

　View Summary

We propose a novel centrality measure that is called Content Centrality for a given network that considers the feature vector of each node generated from its posting activities in social media, its own properties and so forth, in order to extract nodes who have neighbors with similar features. We assume that nodes with similar features are located near each other and unevenly distributed over a network, and the density gradually or rapidly decreases according to the distance from the center of the feature distribution (node). We quantify the degree of the feature concentration around each node by calculating the cosine similarity between the feature vector of each node and the resultant vector of its neighbors with distance-based decay weights, then rank all the nodes according to the value of cosine similarities. In experimental evaluations with three real networks, we confirm the validity of the centrality rankings and discuss the relation between the estimated parameters and the nature of nodes.

DOI

Comparison of influence measures on structural changes focused on node functions

Takayasu Fushimi, Tetsuji Satoh, Kazumi Saito, Kazuhiro Kazama

17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015 - Proceedings ( Association for Computing Machinery, Inc )    2015.12  [Refereed]

　View Summary

The structures of some real-world networks are dynamic in nature as time goes by. These changes consist of the addition or deletion of nodes or links and the rewiring of links. Even if link rewiring occurs, the influence degree tends to differ depending on the location in which it occurs, the nature of the nodes, and so forth. In this paper, by quantifying the influence degree of each node, we attempt to extract the influential structural changes wherein each node in a large population changes its function. Concretely, we de-fine the node function as the PageRank convergence curve of the node and the influence degree affecting the node as distance based on a correlation coefficient of convergence curves before and after change occurs. We then propose the Structural Change Influence Measure (SCIM), which is the average value of the influence degree of all nodes. Based on experimental evaluation using several synthetic and real networks, we found five promising properties of our proposed measure. Our method indicates a higher value for changes in: 1) number of link rewirings
2) concentrated link deleting
3) link addition between distant nodes
4) link addition between important and unimportant nodes
and 5) link deletion between communities.

DOI

距離減衰重みを導入したノード群へのアノテーション付与法

伏見 卓恭, 佐藤 哲司, 斉藤 和巳, 風間 一洋

Webとデータベースに関するフォーラム (WebDB Forum 2015) ( 日本データベース学会 )  ( 2015 ) 142 - 149   2015.11  [Refereed]

時間減衰付きカテゴリ選択モデルを用いたレビュー傾向分析

伏見 卓恭, 佐藤 哲司, 斉藤 和巳, 風間 一洋

第14回情報科学技術フォーラム (FIT2015) ( 情報処理学会 )  -   2015.09  [Refereed]

多重有向グラフのコア部抽出のためのMDSR法の提案と評価

加藤 翔子, 斉藤 和巳, 風間 一洋, 佐藤哲司

日本データベース学会和文論文誌   14-J ( 1 )   2015.04  [Refereed]

ノード属性情報からのリンク存在確率の推定

伏見 卓恭, 斉藤 和巳, 風間 一洋

日本データベース学会和文論文誌 ( 日本データベース学会 )  13-J ( 2 ) 32 - 37   2015.02  [Refereed]

実距離を考慮した中心性指標の提案と重要観光スポット抽出への応用

伏見 卓恭, 斉藤 和巳, 武藤 伸明, 池田 哲夫, 風間 一洋

人工知能学会論文誌, ネットワークが創発する知能論文特集   30 ( 4 ) 32 - 37   2015.02  [Refereed]

Proposing Centrality Measures Considering Actual Distances and Applications to Extracting Important Sightseeing Spots

Fushimi Takayasu, Saito Kazumi, Mutoh Nobuaki, Ikeda Tetsuo, Kazama Kazuhiro

Transactions of the Japanese Society for Artificial Intelligence ( The Japanese Society for Artificial Intelligence )  30 ( 6 ) 703 - 712   2015

　View Summary

In this paper, we propose novel centrality measures which extract important nodes from weighted networks like road networks where an actual distance is assigned over each link. Since the distances between nodes are not taken into consideration in traditional centrality measures like closeness and betweenness, there is a limit to an application to a real world problem for road networks with distances. Aiming at extracting important sightseeing spots so as to improve the convenience of tourists, we propose two measures considering actual distances, one is ``detour centrality which is an easiness measure of brief detour and the other is ``convenience centrality which is an accessibility measure based on traditional closeness and betweenness centrality respectively. Furthermore, when we extracting two or more nodes, there is a problem which these nodes are located in near places with each other only by extracting nodes with high rank of a centrality measure, since the whole balance is not taken into consideration. To overcome these shortcomings, we extend the above-mentioned centrality measures to ``set detour centrality and ``set convenience centrality and attempt to maximize the utility of all tourists over the target area by extracting set of nodes so as to maximize the values of these set centrality measures. In our experiments using two real sightseeing spot datasets, we show that our extended measures can extract an appropriate set of spots in terms of easiness of detour and accessibility, and these measures are robust to change of distances and emerging some outlier spots.

DOI

PageRank収束曲線を用いたコミュニティ特性の定量化

伏見 卓恭, 斉藤 和巳, 風間 一洋, 佐藤 哲司

人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )  2015 ( 0 ) 1M41 - 1M41   2015

　View Summary

<p>本稿では，ネットワーク内のコミュニティと呼ばれるサブネットワークを対象とし，その特性を定量化することでコミュニティ間の構造的な類似度を定義する． 具体的には，PageRank収束曲線を各ノードの特徴ベクトルとして表現し，各コミュニティに属するノードの特徴ベクトルを平均化することで，コミュニティの特性を定量化する． 複数の構造の異なるネットワークに適用し提案指標の有効性を確認する</p>

DOI

Classification Method for Shared Information on Twitter Without Text Data

Seigo Baba, Fujio Toriumi, Takeshi Sakaki, Kosuke Shinoda, Satoshi Kurihara, Kazuhiro Kazama, Itsuki Noda

WWW'15 COMPANION: PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON WORLD WIDE WEB ( ASSOC COMPUTING MACHINERY )    1173 - 1178   2015  [Refereed]

　View Summary

During a disaster, appropriate information must be collected. For example, victims and survivors require information about shelter locations and dangerous points or advice about protecting themselves. Rescuers need information about the details of volunteer activities and supplies, especially potential shortages. However, collecting such localized information is difficult from such mass media as TV and newspapers because they generally focus on information aimed at the general public. On the other hand, social media can attract more attention than mass media under these circumstances since they can provide such localized information. In this paper, we focus on Twitter, one of the most influential social media, as a source of local information. By assuming that users who retweet the same tweet are interested in the same topic, we can classify tweets that are required by users with similar interests based on retweets. Thus, we propose a novel tweet classification method that focuses on retweets without text mining. We linked tweets based on retweets to make a retweet network that connects similar tweets and extracted clusters that contain similar tweets from the constructed network by our clustering method. We also subjectively verified the validity of our proposed classification method. Our experiment verified that the ratio of the clusters whose tweets are mutually similar in the cluster to all clusters is very high and the similarities in each cluster are obvious. Finally, we calculated the linguistic similarities of the results to clarify our proposed method's features. Our method classified topic-similar tweets, even if they are not linguistically similar.

DOI

Estimating Network Structure from Anonymous Ego-centric Information

Takayasu Fushimi, Kazumi Saito, Kazuhiro Kazama

2014 Pacific Rim Knowledge Acquisition Workshop (PKAW 2014) ( Springer )    236 - 245   2014.12  [Refereed]

DOI

メトリック空間オブジェクトを対象とした中心性指標の提案

伏見 卓恭, 斉藤 和巳, 風間 一洋

第13回情報科学技術フォーラム ( 電子情報通信学会 )    2014.09  [Refereed]

Proposal of Multi-Agent Information Diffusion Model for Twitter

Keisuke Ikeda, Yoshiyuki Okada, Fujio Toriumi, Takeshi Sakaki, Kazuhiro Kazama, Itsuki Noda, Kosuke Shinoda, Hirohiko Suwa, Satoshi Kurihara

2014 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2014) ( IEEE/WIC/ACM )    2014.08  [Refereed]

SIR-Extended Information Diffusion Model of False Rumor and its Prevention Strategy for Twitter

Satoshi Kurihara, Yoshiyuki Okada, Takeshi Sakaki, Fujio Toriumi, Kosuke Shinoda, Kazuhiro Kazama, Itsuki Noda, Masuyuki Numao

Journal of Advanced Computational Intelligence and Intelligent Informatics ( FUJI TECHNOLOGY PRESS LTD )  18 ( 4` ) 598 - 607   2014.07  [Refereed]

　View Summary

Nowadays, users of Twitter, one of famous social networking service, have rapidly increased in number, and many people have been exchanging information by Twitter. When the Great East Japan Earthquake struck in 2011, people were able to obtain information from social networking services. Though Twitter played an important role, one problem was especially pointed out: false rumor diffusion. In this study, we propose an information diffusion model based on the SIR model and discuss how to prevent false rumor diffusion.

DOI

異種協調型災害情報支援システム実現に向けた基盤技術の構築

鳥海 不二夫, 篠田 孝祐, 榊 剛史, 栗原 聡, 風間 一洋, 野田 五十樹

人工知能学会論文誌特集「データマイニングとシミュレーション」特集・編集委員   29 ( 1 ) 113 - 119   2014.01  [Refereed]

部分情報からの連結性を保証したネットワーク構造推定

伏見 卓恭, 斉藤 和巳, 風間 一洋

人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )  2014 ( 0 ) 3F33 - 3F33   2014

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<p>本研究では，属性情報などのエゴセントリック情報のみを用いて，連結性を保証してネットワーク全体の構造を推定することを試みる．著者らが提案した構造推定法では，推定結果のネットワークが1つの連結成分になることを保証していない．そこで，全体が1つの連結成分になることを保証した推定法へ改良する． 複数のネットワークを用いた評価実験から，改良を加えた提案法が既存法より推定精度が幾分か高いことを確認する．</p>

DOI

Collaborative heterogeneous integration of disaster and rescue information (CHIDRI)

Fujio Toriumi, Kosuke Shinoda, Takeshi Sakaki, Satoshi Kurihara, Kazuhiro Kazama, Itsuki Noda

Transactions of the Japanese Society for Artificial Intelligence   29 ( 1 ) 113 - 119   2014  [Refereed]

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Traditionally, the support in the event of a disaster were based on hardware, the expertise are strongly required to rescuers. For this reason, in the case that the disaster had been occurred, the role of the people expressly divided to the victims, the rescuers, and the onlookers. On the other hand, in the case of the Great East Japan Earthquake, many engineers tried to develop information support systems for the victims by information technologies. This fact shows that some of engineers become not onlookers but information providers. It can be estimated that one of the reasons why these systems were realized is generally utilization of information infrastructures such as web in our daily life. After such situation is considered, we started a project "Collaborative Heterogeneous Integration of Disaster and Rescue Information (CHIDRI)" which adopted to Challenge for Realizing Early Profits (CREP) in Japanese Society for Artificial Intelligence. In this paper, we explain the frame, the purpose, and the activities of the challenge.

DOI

MDSR: An eigenvector approach to core analysis of multiple directed graphs

Shoko Kato, Kazumi Saito, Kazuhiro Kazama, Tetsuji Satoh

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ( Springer Verlag )  8862   447 - 458   2014  [Refereed]

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In this paper, we address a problem of extracting core portions of a network represented as amultiple directed graph. For this purpose, we propose a new core extraction method called MDSR (Multiple-Directed-Spectral-Relaxation) based on an eigenvector approach. The MDSR method extracts a user-defined number of core portions by repeating the following three steps
1) calculating the left-and right-eigenvectors of an adjacency matrix of a network, 2) quantizing elements of these eigenvectors to binary ones as an indicator of extracting core portion, and 3) removing links of the extracted one. The left-and right-eigenvectors at the first iteration respectively correspond to the hub and authority vectors of the HITS algorithm. In our experiments using a reply network on Twitter constructed as a multiple directed graph, we demonstrate that theMDSR method was able to uncover some part of communities, such as groups of similar account names, users who like to sendmessages to ‘null’, and so on. We also show that some communities were overlapped ones. Furthermore, we confirmthat such communities were hard to be automatically found by two methods, which were constructed by straightforwardly extending the conventional k-core method.

DOI

Extracting important sightseeing spots considering actual distances

FUSHIMI Takayasu, SAITO Kazumi, MUTOH Nobuaki, IKEDA Tetsuo, KAZAMA Kazuhiro

JSAI Technical Report, SIG-KBS ( The Japanese Society for Artificial Intelligence )  102   6 - 6   2014

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<p>In this paper, we attempt to extract important sightseeing spots so as to improve the convenience of tourists. To this end, we propose two measures, one is detour centrality which is a easiness measure of brief detour and the other is convenience centrality which is a accessibility measure, based on traditional closeness and betweenness centrality respectively. These traditional centrality measures do not intend for actual distances as weights on links therefore, our proposed measures are designed with distances between spots. Furthermore, by assuming that these natures like easiness of detour and accessibility of spots behave collaboratively, we also propose extended measures for an arbitrary set of spots. In our experiments using two real sightseeing spots datasets, we show that our extended method can extract an appropriate set of spots in terms of easiness of detour and accessibility, and these pivots extracted by two methods are substantially different.</p>

DOI

顔文字に着目したツイートの感情変化の分析

風間 一洋, 榊 剛史, 鳥海 不二夫, 篠田 孝祐, 栗原 聡, 野田 五十樹

WebDB Forum 2013     2013.11  [Refereed]

MDSR法を用いたreplyツイートネットワークの特性分析

加藤 翔子, 斉藤 和巳, 風間 一洋, 佐藤 哲司

WebDB Forum 2013     2013.11  [Refereed]

エゴセントリック情報からのネットワーク構造推定

伏見 卓恭, 斉藤 和巳, 風間 一洋

WebDB Forum 2013     2013.11  [Refereed]  [Invited]

ノードの注目度に基づく機能コミュニティ抽出法

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋

情報処理学会論文誌：データベース   6 ( 4 ) 104 - 112   2013.09  [Refereed]

ネットワーク分析によるTwitterユーザのフォロー形成に関する一考察

小出 明弘, 斉藤 和巳, 風間 一洋, 鳥海 不二夫

情報処理学会論文誌：数理モデル化と応用   6 ( 2 ) 164 - 173   2013.08  [Refereed]

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本稿では，Twitterのフォローネットワークを分析することにより，ユーザのフォローがどのような目的で行われているのか議論する．まず，フォローネットワークの特徴を把握するため，ネットワーク内の高次数ノードに着目し，ブログの読者関係とレビューサイトのお気に入り関係を表したそれぞれのネットワーク構造の特徴と比較する．その結果，ブログやレビューサイトでは，比較的小規模な高コリンクグループが得られたのに対し，フォローネットワークでは，強い双方向関係により構築された大規模な高コリンクグループと，双方向関係がほとんど見られない複数の小規模な低コリンクグループが存在することが分かった．さらに，高次数ノードのツイート集合を分析し，これらのグループは同じようなツイートをしているにもかかわらず，フォロワとの関係に大きな違いが見られることが分かった．In this paper, we explored Twitter's follow mechanism through a network analysis. In order to characterize the salient structure of Twitter's follow network, we first empirically compared it with those of reader and favorite networks form blog and review sites by focusing on their high degree nodes. From this experiment, we observed a relatively large high co-link group whose nodes are mutually connected to each other and some small low co-link groups whose nodes are not mutually connected to each other in Twitter's network. On the other hand, most groups are relatively small high co-link groups such as discussion groups in blog and review sites. Moreover, by analyzing messages tweeted by these group's users, we found that these groups much differ in relation with followers although these groups resemble in content of tweets.

リンクの向きに着目した機能コミュニティとモチーフの関係分析

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋

情報処理学会論文誌：数理モデル化と応用   6 ( 2 ) 137 - 146   2013.08  [Refereed]

Information Sharing on Twitter During the 2011 Catastrophic Earthquake

Fujio Toriumi, Takeshi Sakaki, Kosuke Shinoda, Kazuhiro Kazama, Satoshi Kurihara, Itsuki Noda

SWDM 2013 ( ASSOC COMPUTING MACHINERY )    1025 - 1028   2013.05  [Refereed]

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Such large disasters as earthquakes and hurricanes are very unpredictable. During a disaster, we must collect information to save lives. However, in time disaster, it is difficult to collect information which is useful for ourselves from such traditional mass media as TV and newspapers that contain information for the general public. Social media attract attention for sharing information, especially Twitter, which is a hugely popular social medium that is now being used during disasters. In this paper, we focus on the information sharing behaviors on Twitter during disasters. We collected data before and during the Great East Japan Earthquake and arrived at the following conclusions:- Many users with little experience with such specific functions as reply and retweet did not continuously use them after the disaster.- Retweets were well used to share information on Twitter.- Retweets were used not only for sharing the information provided by general users but used for relaying the information from the mass media.We conclude that social media users changed their behavior to widely diffuse important information and decreased non-emergency tweets to avoid interrupting critical information.

Regional Analysis of User Interactions on Social Media in Times of Disaster

Takeshi Sakaki, Fujio Toriumi, Kosuke Shinoda, Kazuhiro Kazama, Satoshi Kurihara, Itsuki Noda

WWW 2013     2013.05  [Refereed]

SIR-Extended Information Diffusion Model of False Rumor and its Prevention Strategy for Twitter

Satoshi Kurihara, Yoshiyuki Okada, Takeshi Sakaki, Fujio Toriumi, Kosuke Shinoda, Kazuhiro Kazama, Itsuki Noda, Masuyuki Numao

The 5th International Workshop on Emergent Intelligence on Networked Agents (WEIN 2013) ( AAMAS )    2013.05  [Refereed]

東日本大震災時におけるTwitterの活用状況とコミュニケーション構造の分析

SHINODA Kosuke, SAKAKI Takeshi, TORIUMI Fujio, KAZAMA Kazuhiro, KURIHARA Satoshi, NODA Itsuki, MATSUO Yutaka

J. SOFT ( Japan Society for Fuzzy Theory and Intelligent Informatics )  25 ( 1 ) 598 - 608   2013.03  [Refereed]

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The Great East Japan Earthquake caused devastating damage to infrastructure and loss of life. Many people used social media to communicate and share information through the series of earthquake events and aftershocks. We analyzed over 400 million Tweets and the Twitter network in Japan before and after the earthquake, which revealed the earthquake that occurred in the Twitter milieu itself. We performed analyses of two kinds. As a result, we suggest that the role of Twitter as a means to share information changed during the earthquake period.

DOI

異なる視点からのノード機能に基づくコミュニティ抽出法

伏見 卓恭, 斉藤 和巳, 風間 一洋

日本データベース学会論文誌 ( 日本データベース学会 )  11 ( 3 ) 27 - 32   2013.02  [Refereed]

The possibility of social media analysis for disaster management

Takeshi Sakaki, Yutaka Matsuo, Satoshi Kurihara, Fujio Toriumi, Kosuke Shinoda, Itsuki Noda, Koki Uchiyama, Kazuhiro Kazama

2013 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2013     238 - 243   2013  [Refereed]

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Collecting sharing, and delivering information in disaster situations is crucially important. Mass media such as TV, radio, and newspapers have played important roles in information distribution in past disasters and crises. Recently, social media have received much attention for their use as an information sharing tool. Especially, it is said that people used Twitter to collect and share information in the aftermath of the Great East Japan Earthquake. In academic fields, some researchers have started to propose some methods and systems for disaster management by analyzing social media data. Other people doubt whether social media will actually function effectively for disaster management because of uncertainty and inaccuracies related to rumors and misunderstanding. In this paper, we overview current studies of social media analysis for disaster management and explain some studies in detail to show their possibility and availability. We specifically examine situational awareness, user behavior analysis and information propagation analysis, which are three approaches to social media analysis, to clarify what social media analysis can and cannot do. Additionally, we propose some concepts for social media analysis and show how those concepts help to collaborate with us, researchers in social media analysis fields and other research fields. © 2013 IEEE.

DOI

情報拡散影響度に基づく機能コミュニティ抽出法

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋

人工知能学会全国大会論文集 ( 一般社団法人 人工知能学会 )  2013 ( 0 ) 2J15 - 2J15   2013

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<p>従来の機能コミュニティ抽出法では，ネットワーク上でのランダムウォークを仮定したPageRank計算において，各ステップでの確率ベクトルの収束過程を基にノードの機能を定義し，類似機能を有するノード群を抽出していた．本稿では，ネットワーク上での情報拡散に着目し，他のノードへの影響力を基にノードの機能を定義した機能コミュニティ概念，および抽出手法を提案する．</p>

DOI

ソーシャルネットワークによるWebからの情報収集

風間 一洋

情報の科学と技術   63 ( 1 ) 28 - 33   2013  [Invited]

個々のノードの視点に基づく機能コミュニティ抽出法

伏見 卓恭, 斉藤 和巳, 池田 哲夫, 風間 一洋, 松尾 真人

WebDB Forum 2012 ( 情報処理学会データベースシステム研究会など )    2012.11  [Refereed]

Twitter上のリプライ，リツイート，ハッシュタグの類似構造分析

小出 明弘, 斉藤 和巳, 風間 一洋, 鳥海 不二夫

WebDB Forum 2012 ( 情報処理学会データベースシステム研究会など )    2012.11  [Refereed]

Characteristics Analysis of Multi Graphs Focused on Co-link Structure

小出 明弘, 斉藤 和巳, 風間 一洋, 鳥海 不二夫

日本データベース学会論文誌 ( 日本データベース学会 )  11 ( 1 ) 13 - 18   2012.10  [Refereed]

機能性に基づくコミュニティ抽出法の比較

伏見 卓恭, 斉藤 和巳, 風間 一洋

情報処理学会論文誌：データベース   5 ( 3 ) 26 - 35   2012.09  [Refereed]

ネットワーク機能コミュニティ抽出法

伏見 卓恭, 斉藤 和巳, 風間 一洋

日本データベース学会論文誌   10 ( 3 ) 13 - 18   2012.02  [Refereed]

Characteristics of information diffusion in blogs, in relation to information source type

Kazuhiro Kazama, Miyuki Imada, Keiichiro Kashiwagi

Neurocomputing ( Elsevier BV )  76 ( 1 ) 84 - 92   2012.01  [Refereed]

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A novel method is presented to analyze the dynamics of social media, i.e., information diffusion properties, for information recommendation and ranking. In social media such as blogs, various information diffuses over time. As a result, a network structure is constructed. In an information diffusion network, each influential information source has an affected subnetwork whose nodes are reachable from it. We define three information diffusion properties of the subnetwork using the numbers of three types of directed two-edge connected subgraphs, which are basic structures in a directed acyclic graph such as an information diffusion network. Each basic structure type is related to information scattering, information gathering, or information transmission. We visualized and analyzed the structure of information diffusion networks extracted for various topics. Furthermore, we characterized the information diffusion properties by using the rank correlation coefficient, precision, and mean reciprocal rank and mean average precision of three types of information sources: official sites, news articles, and consumer generated media pages. We found that the three information diffusion properties have different characteristics and give priority to different types of information sources. © 2011 Elsevier B.V.

DOI

Extracting Communities in Networks Based on Functional Properties of Nodes.

Takayasu Fushimi, Kazumi Saito, Kazuhiro Kazama

Knowledge Management and Acquisition for Intelligent Systems - 12th Pacific Rim Knowledge Acquisition Workshop(PKAW) ( Springer )    328 - 334   2012

DOI

Studies on Relationship between TV Reports and Twitter Information Concerning the Fukushima Dai-ichi Nuclear Power Plants Accident:(2)Analysis of Word Co-occurrence Structure Concerning Radioactivity

SATO Ryosuke, KIMURA Hiroshi, TORIUMI Fujio, SAKAKI Takeshi, KAZAMA Kazuhiro, FUKUDA Kensuke

Proceedings of Annual / Fall Meetings of Atomic Energy Society of Japan ( Atomic Energy Society of Japan )  2012   8 - 8   2012

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本研究のシリーズ報告である「(1)テレビ報道からツイッターへの情報伝播に関する分析」によって、テレビ報道とツイッターの間に関連性があることが示唆された。そこで本研究は、放射能を中心とした単語を含む情報に注目し、ツイッターとテレビ報道での放射能に関連する用語の共起構造を比較することで、ツイッターとテレビ報道との関連性を明らかにする。

DOI

Distribution pattern analysis of associated geographical names on transportation network

Kazuhiro Kazama

Transactions of the Japanese Society for Artificial Intelligence ( Japanese Society for Artificial Intelligence )  27 ( 2 ) 34 - 39   2012  [Refereed]

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I present a new text mining approach combined with network analysis to quantify the distribution patterns of the associated geographical names on a transportation network. I extract geographical names from user's search queries recorded in search engine query logs and compare the similarities of any pair of geographical names using Jaccard coefficient. I found that a set of associated geographical names for each geographical name shows a specific spatial distribution pattern on transportation network and define a measure for quantifying such characteristics. Furthermore, I discuss its characteristics and application for information navigation.

DOI

Studies on Relationship between TV Reports and Twitter Information Concerning the Fukushima Dai-ichi Nuclear Power Plants Accident:(1) Analysis of Information Propagation from TV Reports to Twitter

KIMURA Hiroshi, SATO Ryosuke, SHIBATA Yogo, TORIUMI Fujio, SAKAKI Takeshi, KAZAMA Kazuhiro, FUKUDA Kensuke

Proceedings of Annual / Fall Meetings of Atomic Energy Society of Japan ( Atomic Energy Society of Japan )  2012   7 - 7   2012

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2011年3月11日に起こった東日本大震災、それに引き続いて起こった東京電力・福島第一原子力発電所事故（以降、福島原発事故）は、インターネットを含むさまざまなメディアによって扱われ、社会に大きな影響を与えたといわれる。本研究では、代表的なメディアのひとつであるテレビ報道と、インターネット上のソーシャルメディアのひとつであるツイッターとに着目し、福島原発事故に関連する情報がそれぞれのメディアでどのように扱われたのか、また、それらの情報にはどのような関連性があったのかを分析する。 なお、本報告は「（２）放射能に関連する用語についての共起構造分析」とのシリーズ報告である。

DOI

情報伝播特性の定量化手法

風間 一洋, 今田 美幸, 柏木 啓一郎

コンピュータソフトウェア   28 ( 1 ) 162 - 172   2011.02  [Refereed]

Quantification method of information diffusion properties

Kazuhiro Kazama, Miyuki Imada, Keiichiro Kashiwagi

Computer Software   28 ( 1 ) 162 - 172   2011

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This paper proposes a quantification method of three information diffusion properties of the subnetwork that is reachable from an information source in the information diffusion network. This subnetwork is a directed acyclic graph and is composed of three types of directed 2-edge connected subgraphs, which is related to the basic phenomena of information diffusion: information scattering, information gathering, and information transmitting. We define the information scatter degree, the information gather degree, and information transmit degree as information diffusion properties by using the number of three types of directed 2-edge connected subgraphs. We analyze the characteristics and the time series variation of information diffusion attributes in real information diffusion networks extracted from blogspace by these information diffusion properties.

Characteristics estimation of information sources by information diffusion analysis

Kazuhiro Kazama, Miyuki Imada, Keiichiro Kashiwagi

Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010   1   484 - 491   2010  [Refereed]

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This paper presents a novel method to estimate characteristics of information sources about a topic by analyzing their information diffusion subnetworks in blogspace. In an information diffusion network, each influential information source has an affected subnetwork whose nodes are reachable from it. We define three information diffusion properties of the subnetwork using the numbers of three types of directed 2-edge connected subgraphs, which are basic structures in a directed acyclic graph such as an information diffusion network. Each type of basic structure is related to information scattering, information gathering, or information transmission. We visualized and analyzed the structure of information diffusion networks extracted for other topics. Furthermore, we characterize the information diffusion properties by using the rank correlation coefficient, precision, and mean reciprocal rank (MRR) and mean average precision (MAP) of three types of information sources: official sites, news sites, and CGMs. We found that the three information diffusion properties have different characteristics and give priority to different types of information sources. © 2010 IEEE.

DOI

Quantification of information diffusion network characteristics in blogspace

Kazuhiro Kazama, Miyuki Imada, Keiichiro Kashiwagi

Transactions of the Japanese Society for Artificial Intelligence ( Japanese Society for Artificial Intelligence )  25 ( 3 ) 404 - 409   2010  [Refereed]

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This paper proposes three new quantification measures of information diffusion characteristics in blogspace. These measures are calculated from the number of three basic structures, which are directed 2-edge connected sub graphs, in information diffusion networks. Each basic structure is related to information scattering, information gathering or information transmission. We analyze and visualize information diffusion networks extracted from six blog datasets. In the result, we show that the difference of information diffusion characteristics can be discriminated by the combination of three measures and human activity in blogspace can be explained by them.

DOI

The k-dense method to extract communities from complex networks

Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama

Studies in Computational Intelligence   165   243 - 257   2009  [Refereed]

　View Summary

To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it only discovers coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method. © 2009 Springer-Verlag Berlin Heidelberg.

DOI

Extracting Communities from Complex Networks by the k-Dense Method

Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES ( IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG )  E91A ( 11 ) 3304 - 3311   2008.11  [Refereed]

　View Summary

To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.

DOI

Extraction of Overlapping Community Structures from Human Relationships.

風間一洋, 佐藤進也, 斉藤和巳, 山田武士

コンピュータソフトウェア   24 ( 1 ) 81 - 90   2007.06  [Refereed]

リアルタイム圧縮によるパケットキャプチャの高速化

清水 奨, 風間 一洋, 廣津 登志夫, 後藤 滋樹

情報学会論文誌：コンピューティングシステム   47 ( SIG 7(ACS14) ) 183 - 193   2006.05  [Refereed]

語の共有に基づく文書ネットワークの構造的特徴について

佐藤 進也, 風間 一洋, 福田 健介, 村上 健一郎

情報処理学会論文誌   47 ( 3 ) 829 - 839   2006.03  [Refereed]

トラックバックネットワークに基づくSEOコミュニティの分析

風間 一洋, 佐藤 進也, 斉藤 和巳, 木村 昌弘

情報処理学会論文誌   47 ( 3 ) 840 - 849   2006.03  [Refereed]

Network analyses to understand the structure of wikipedia

Takeshi Yamada, Kazumi Saito, Kazuhiro Kazama

Proceedings of AISB'06: Adaptation in Artificial and Biological Systems   3   195 - 198   2006

　View Summary

We investigated the structure of Wikipedia, the well known Web-based encyclopedia, as a very largescale hyperlink network by using network analysis methods. We analyzed the time evolution of the number of articles and links, applied core-extraction methods to identify highly interconnected subnetworks, and compared different centrality measures to understand its characteristics.

Evaluation of using human relationships on the web as information navigation paths

Kazuhiro Kazama, Shin-ya Sato, Kensuke Fukuda, Ken-ichiro Murakami, Hiroshi Kawakami, Osamu Katai

NEW FRONTIERS IN ARTIFICIAL INTELLIGENCE ( SPRINGER-VERLAG BERLIN )  4012 ( 4012 ) 302 - 313   2006  [Refereed]

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We investigated the use of human relationships on the web for information navigation paths. We propose a new information navigation method that uses personal names. It automatically extracts the human relationships of key people by analyzing the co-occurences of personal names on a web page from search results that are relevant to a specific topic and provides two facilities for using these relationships as information navigation paths. One is information navigation using a list of the key people and a list of related people. Another is information navigation using a network diagram of the key people. We consider human. relationships on the web as new information navigation paths like hyperlinks. We analyzed the network structure of human relationships for various topics and evaluated their usefulness in order to clarify the applicable scope and improve the usefulness. The results show that human relationships are adequate shortcut networks for search results for most cases. However, if the ratio of the number of personal names to the number of web pages is too high, the relationships of the people are too tight for information navigation and our future work is to reduce the number of edges without reducing the coverage of search results. If the degree of density of human-related information in the higher ranked search results is too low, human activity is low and our method is not suitable.

DOI

Extracting communities from complex networks by the K-dense method

Kazumi Saito, Takeshi Yamada, Kazuhiro Kazama

ICDM 2006: Sixth IEEE International Conference on Data Mining, Workshops ( IEEE COMPUTER SOC )    300 - 304   2006  [Refereed]

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To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the two different types of networks assembled from real data, namely, from blog trackbacks and word associations, demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.

Web空間における人間関係を用いた情報探索の一手法

風間 一洋, 佐藤 進也, 福田 健介, 村上 健一郎, 川上 浩司, 片井 修

情報処理学会論文誌：データベース   46 ( SIG 13 (TOD27) ) 26 - 39   2005.09  [Refereed]

実世界指向Webマイニングによる同姓同名人物の分離

佐藤 進也, 風間 一洋, 福田 健介, 村上 健一郎

情報処理学会論文誌：データベース   46 ( SIG 8 (TOD26) ) 26 - 36   2005.06  [Refereed]

分散協調翻訳支援システムの構築と運用

小山 博史, 風間 一洋, 岡本 隆史, 横田 健彦

情報処理学会論文誌   46 ( 4 ) 974 - 984   2005.04  [Refereed]

実世界指向Webマイニングの提案とその同姓同名人物分離問題への適用

佐藤 進也, 風間 一洋, 福田 健介, 村上 健一郎

DBSJ Letters ( 日本データベース学会 )  3 ( 4 ) 21 - 24   2005.03  [Refereed]

Detecting Search Engine Spam from a Trackback Network in Blogspace

Masahiro Kimura, Kazumi Saito, Kazuhiro Kazama, Shin-ya Sato

KES 2005: Knowledge-Based Intelligent Information and Engineering Systems, LNCS ( Springer Berlin Heidelberg )  3684   723 - 729   2005  [Refereed]

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We aim to develop a technique to detect search engine optimization (SEO) spam websites. Specifically, we propose four methods for extracting the SEO spam entries from a given trackback network in blogspace that are based on fundamental metrics on a network. Using real data of trackback networks in blogspace, we experimentally evaluate the performance of the proposed methods, and demonstrate that the method of ranking entries based on average degrees of nearest neighbors can be a very promising approach for extracting SEO spam entries.

DOI

Autonomous development of relationships among web servers for facilitating information utilization

Shin-Ya Sato, Masanori Harada, Kazuhiro Kazama

Systems and Computers in Japan   35 ( 10 ) 40 - 49   2004.09  [Refereed]

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A Web server can play a role as an agent for people who create information, and Web servers with related information can be searched by the agent in order to facilitate efficient information utilization on the Web. Web servers exchange information with other servers and select which ones to keep or abandon, resulting in an increase in the links with servers with greater relevance. As a result, a community, a group of Web servers that are mutually linked, is created. A Web server community can be used as a place for various forms of information utilization and exchange, such as meta-searches and contents syndication. In this paper, the authors propose an algorithm for creating communities after evaluating the meaning of facilitating information utilization via a community. They then verify the validity of their idea through simulations. © 2004 Wiley Periodicals, Inc.

DOI

Webディレクトリ拡張の自動化手法

風間 一洋, 原田 昌紀, 佐藤 進也

情報処理学会論文誌：データベース   45 ( SIG 7 (TOD22) ) 218 - 229   2004.06  [Refereed]

Query Networkによる情報発見・収集支援

佐藤 進也, 風間 一洋, 原田 昌紀

情報処理学会論文誌：データベース   45 ( SIG 7 (TOD22) ) 1 - 10   2004.06  [Refereed]

Query Networkの構造と時間発展を利用した情報発見・収集支援

佐藤 進也, 原田 昌紀, 風間 一洋

DBSJ Letters ( 日本データベース学会 )  2 ( 4 ) 11 - 14   2004.03  [Refereed]

Finding authoritative people from the Web

Masanori Harada, Shin-Ya Sato, Kazuhiro Kazama

Proceedings of the ACM IEEE International Conference on Digital Libraries, JCDL 2004 ( Association for Computing Machinery (ACM) )    306 - 313   2004

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Today's web is so huge and diverse that it arguably reflects the real world. For this reason, searching the web is a promising approach to find things in the real world. This paper presents NEXAS, an extension to web search engines that attempts to find real-world entities relevant to a topic. Its basic idea is to extract proper names from the web pages retrieved for the topic. A main advantage of this approach is that users can query any topic and learn about relevant real-world entities without dedicated databases for the topic. In particular, we focus on an application for finding authoritative people from the web. This application is practically important because once personal names are obtained, they can lead users from the web to managed information stored in digital libraries. To explore effective ways of finding people, we first examine the distribution of Japanese personal names by analyzing about 50 million Japanese web pages. We observe that personal names appear frequently on the web, but the distribution is highly influenced by automatically generated texts. To remedy the bias and find widely acknowledged people accurately, we utilize the number of web servers containing a name instead of the number of web pages. We show its effectiveness by an experiment covering a wide range of topics. Finally, we demonstrate several examples and suggest possible applications.

DOI

Autonomous Development of Relationships among Wed Servers for Facilitating Information Utilization

SATO Shin-ya, HARADA Masanori, KAZAMA Kazuhiro

The Transactions of the Institute of Electronics,Information and Communication Engineers. ( The Institute of Electronics, Information and Communication Engineers )  J86-D-I ( 8 ) 583 - 591   2003.08  [Refereed]

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Web上の効率的な情報利用を支援するため,Webサーバに情報発信者のエージェントとしての役割を与え,関連情報をもつWebサーバを探索させる. Webサーバは,互いに他のサーバに関する情報を交換し,取捨選択することで,より関連性の高いサーバとのつながりを増やしていく.その結果,相互に関連するWebサーバの集団であるコミュニティが形成される.Webサーバのコミュニティは,メタサーチやコンテンツシンジケーションなど種々の情報利用・流通の場として利用できる.本論文では,まず,コミュニティによる情報利用支援の意義を検討した上で,コミュニティ形成のアルゴリズムを提案し,シミュレーションによってその妥当性を検証する.

サーチエンジンの検索結果のマルチレベルグルーピングの評価

風間 一洋, 原田 昌紀, 佐藤 進也

コンピュータソフトウェア ( 日本ソフトウェア科学会 )  17 ( 4 ) 58 - 69   2000.12  [Refereed]

Evaluation of Multi-level Grouping Scheme for the Search Results that A Search Engine Generates.

KAZAMA Kazuhiro, HARADA Masanori, SATO Shin-ya, Kazuhiro Kazama, Masanori Harada, Shin - ya Sato, NTT Network Innovation Laboratories., NTT Network Innovation Laboratories., NTT Network Innovation Laboratories.

Computer Software ( Japan Society for Software Science and Technology )  17 ( 4 ) 354 - 365   2000.07

DOI

WWWトラフィック解析による情報生産者と情報消費者の数量的特徴付け

佐藤 進也, 風間 一洋, 清水 奨, 神林 隆

情報処理学会論文誌   40 ( 7 ) 2851 - 2860   1999.07  [Refereed]

HTML Document Correlation Analysis by User's Behavior in World Wide Web Navigation

KAZAMA Kazuhiro, SATO Shin-ya, SHIMIZU Susumu, KAMBAYASHI Takashi

Transactions of Information Processing Society of Japan ( Information Processing Society of Japan (IPSJ) )  40 ( 5 ) 2450 - 2459   1999.05  [Refereed]

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This paper describes the method to construct HTML document correlation graph that indicates mutual relations of them by analysis of user's access sequences to them and their URL 2-grams, and defines the correlation by the graph structure and path's frequency. And we evaluate the results that were acquired by this method in the small community.