Abstract
This article describes a keyphrase identification program (KIP) which extracts document key concepts by using sample human keyphrases. KIP considers the composition of a keyphrase. The more keywords a phrase contains and the more significant these keywords are, the more likely this phrase is a keyphrase. KIP first populates its database using manually identified keyphrases and keywords; it then checks the composition of all identified noun phrases, looks up the database and calculates scores for all these noun phrases; the ones having higher scores will be extracted as keyphrases. KIP's learning function can enrich the database by automatically adding new keyphrases to the database. Consequently, the database will grow gradually and the system performance will be improved. The results from our small-scale preliminary experiments show that KIP is effective in extracting document keyphrases and its learning function is useful.
Original language | English (US) |
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Title of host publication | Proceedings of the 2005 International Conference on Artificial Intelligence, ICAI'05 |
Pages | 826-832 |
Number of pages | 7 |
Volume | 2 |
State | Published - Dec 1 2005 |
Event | 2005 International Conference on Artificial Intelligence, ICAI'05 - Las Vegas, NV, United States Duration: Jun 27 2005 → Jun 30 2005 |
Other
Other | 2005 International Conference on Artificial Intelligence, ICAI'05 |
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Country/Territory | United States |
City | Las Vegas, NV |
Period | 6/27/05 → 6/30/05 |
All Science Journal Classification (ASJC) codes
- Engineering(all)