Name
Abstract | ||
|---|---|---|
Previous research has conflicting conclusions on whether word sense disambiguation (WSD) systems can improve information retrieval (IR) performance. In this paper, we propose a method to estimate sense distributions for short queries. Together with the senses predicted for words in documents, we propose a novel approach to incorporate word senses into the language modeling approach to IR and also exploit the integration of synonym relations. Our experimental results on standard TREC collections show that using the word senses tagged by a supervised WSD system, we obtain significant improvements over a state-of-the-art IR system. |
Year | Venue | Keywords |
|---|---|---|
2012 | ACL | word sense disambiguation,conflicting conclusion,supervised wsd system,novel approach,language modeling approach,sense distribution,information retrieval,word sense,state-of-the-art ir system |
Field | DocType | Volume |
SemEval,Information retrieval,Computer science,Synonym,Exploit,Natural language processing,Artificial intelligence,Language model,Word-sense disambiguation | Conference | P12-1 |
Citations | PageRank | References |
31 | 0.97 | 29 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhi Zhong | 1 | 232 | 8.96 |
| Hwee Tou Ng | 2 | 4092 | 300.40 |