Conference proceeding
Keyphrase extraction-based query expansion in digital libraries
Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '06), v 2006, pp 202-209
Jun 2006
Abstract
In pseudo-relevance feedback, the two key factors affecting the retrieval performance most are the source from which expansion terms are generated and the method of ranking those expansion terms. In this paper, we present a novel unsupervised query expansion technique that utilizes keyphrases and POS phrase categorization. The keyphrases are extracted from the retrieved documents and weighted with an algorithm based on information gain and co-occurrence of phrases. The selected keyphrases are translated into disjunctive normal form (DNF) based on the POS phrase categorization technique for better query refomulation. Furthermore, we study whether ontologies such as WordNet and MeSH improve the retrieval performance in conjunction with the keyphrases. We test our techniques on TREC 5, 6, and 7 as well as a MEDLINE collection. The experimental results show that the use of keyphrases with POS phrase categorization produces the best average precision
Metrics
11 Record Views
27 citations in Scopus
Details
- Title
- Keyphrase extraction-based query expansion in digital libraries
- Creators
- Il Yeol Song - Drexel University, Philadelphia, PARobert B Allen - Drexel University, Philadelphia, PAZoran Obradovic - Temple University, Philadelphia, PAMin Song - Temple University, Philadelphia, PA
- Publication Details
- Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '06), v 2006, pp 202-209
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Scopus ID
- 2-s2.0-34247260471
- Other Identifier
- 991014878447804721