Name
Abstract | ||
|---|---|---|
This paper presents a multi-dependency language modeling approach to information retrieval. The approach extends the basic KL-divergence retrieval approach by introducing the hybrid dependency structure, which includes syntactic dependency, syntactic proximity dependency and co-occurrence dependency, to describe dependencies between terms. Term and dependency language models are constructed for both document and query. The relevant between a document and a query is then evaluated by using the KL-divergence between their corresponding models. The new dependency retrieval model has been compared with other traditional retrieval models. Experiment results indicate that it produces significant improvements in retrieval effectiveness. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-77018-3_48 | PAKDD Workshops |
Keywords | Field | DocType |
basic kl-divergence retrieval approach,multi-dependency language modeling approach,information retrieval,dependency language model,hybrid dependency structure,retrieval effectiveness,syntactic dependency,co-occurrence dependency,new dependency retrieval model,syntactic proximity dependency,traditional retrieval model,language model | Divergence-from-randomness model,Query expansion,Information retrieval,Computer science,Dependency structure,Natural language processing,Artificial intelligence,Vector space model,Term Discrimination,Syntax,Language model | Conference |
Volume | ISSN | ISBN |
4819 | 0302-9743 | 3-540-77016-X |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
5 | ||