Abstract
With the currently growing interest in the Semantic Web, personal metadata to model a user and the relationship between users is coming to play an important role in the Web. This paper proposes a novel keyword extraction method to extract personal information from the Web. The proposed method uses the Web as a large corpus to obtain co-occurrence information of words. Using the co-occurrence information, our method extracts relevant keywords depending on the context of a person. Our evaluation shows better performance to other keyword extraction methods. We give a discussion about our method in terms of general keyword extraction for the Web.
Original language | English |
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Pages (from-to) | 337-345 |
Number of pages | 9 |
Journal | Transactions of the Japanese Society for Artificial Intelligence |
Volume | 20 |
Issue number | 5 |
Publication status | Published - 2005 |
Externally published | Yes |
Keywords
- Keyword extraction
- Metadata
- Search engine
- Social network
- Word co-occurrence
ASJC Scopus subject areas
- Artificial Intelligence