Abstract
This paper presents a novel way of building the user profile of concept network for personalized search. The user profile is defined as a concept network, in which each concept is approximately represented with the formal concept analysis (FCA) theory. We assume that a concept, called 'session interest concept', subsume a user's query intention during a query session and it can reflect the user's preference. Whenever a user issues his/her query, a session interest concept is generated. Then, new concepts are merged into the current concept network (i.e., a user profile) in which recent user preferences are accumulated. According to FCA, a session interest concept is defined as a pair of extent and intent where the extent covers a set of documents selected by the user among the search results and the intent covers a set of keyword features extracted from the selected documents. And, in order to make a concept network grow, we need to calculate the similarity between a new concept and existing concepts, and to this end, we use a reference concept hierarchy called Open Directory Project. The user profile of concept network is eventually used to expand a user's initial query. The empirical results show that our approach improves the accuracy of search results in terms of personal preference.
Original language | English |
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Title of host publication | Proceedings - 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010 |
Place of Publication | Piscataway, NJ |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 567-572 |
Number of pages | 6 |
ISBN (Print) | 9780769541471 |
DOIs | |
Publication status | Published - 2010 |
Externally published | Yes |
Event | 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010 - Yamagata, Japan Duration: 18 Aug 2010 → 20 Aug 2010 |
Other
Other | 9th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2010 |
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Country/Territory | Japan |
City | Yamagata |
Period | 18/08/10 → 20/08/10 |
Keywords
- Concept network
- Information retrieval
- Keyword extraction
- Personalized search
- Query expansion
- User profile