Extracting communities of interests for semantics-based graph searches

Makoto Nakatsuji; Akimichi Tanaka; Toru Ishida

Extracting communities of interests for semantics-based graph searches

Makoto Nakatsuji, Akimichi Tanaka, Toru Ishida

Research output: Contribution to journal › Conference article › peer-review

Abstract

We propose an algorithm that divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs - communities of interests (COIs). Our algorithm differs from conventional modularity-based community extraction because it introduces a mechanism to harmonize the number of users in each COI. It also attaches semantic tags to the relationships between COIs or between users based on taxonomies of the content items of interest. Our algorithm allows users to identify new interests quickly and accurately when searching their interests in the graph.

Original language	English
Journal	CEUR Workshop Proceedings
Volume	401
Publication status	Published - 2008 Dec 1
Externally published	Yes
Event	7th International Semantic Web Conference, ISWC 2008 - Karlsruhe, Germany Duration: 2008 Oct 28 → 2008 Oct 28

ASJC Scopus subject areas

Computer Science(all)

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title = "Extracting communities of interests for semantics-based graph searches",

abstract = "We propose an algorithm that divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs - communities of interests (COIs). Our algorithm differs from conventional modularity-based community extraction because it introduces a mechanism to harmonize the number of users in each COI. It also attaches semantic tags to the relationships between COIs or between users based on taxonomies of the content items of interest. Our algorithm allows users to identify new interests quickly and accurately when searching their interests in the graph.",

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AU - Tanaka, Akimichi

AU - Ishida, Toru

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N2 - We propose an algorithm that divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs - communities of interests (COIs). Our algorithm differs from conventional modularity-based community extraction because it introduces a mechanism to harmonize the number of users in each COI. It also attaches semantic tags to the relationships between COIs or between users based on taxonomies of the content items of interest. Our algorithm allows users to identify new interests quickly and accurately when searching their interests in the graph.

AB - We propose an algorithm that divides a graph, whose vertices are users and whose edges represent shared interests, into subgraphs - communities of interests (COIs). Our algorithm differs from conventional modularity-based community extraction because it introduces a mechanism to harmonize the number of users in each COI. It also attaches semantic tags to the relationships between COIs or between users based on taxonomies of the content items of interest. Our algorithm allows users to identify new interests quickly and accurately when searching their interests in the graph.

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M3 - Conference article

AN - SCOPUS:84885583310

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JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

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