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 |
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ASJC Scopus subject areas
- Computer Science(all)
Cite this
Extracting communities of interests for semantics-based graph searches. / Nakatsuji, Makoto; Tanaka, Akimichi; Ishida, Toru.
In: CEUR Workshop Proceedings, Vol. 401, 01.12.2008.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - Extracting communities of interests for semantics-based graph searches
AU - Nakatsuji, Makoto
AU - Tanaka, Akimichi
AU - Ishida, Toru
PY - 2008/12/1
Y1 - 2008/12/1
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.
UR - http://www.scopus.com/inward/record.url?scp=84885583310&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84885583310&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84885583310
VL - 401
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
SN - 1613-0073
ER -