
Dependency Structure Applied to Language Modeling for Information Retrieval
Author(s) -
Lee Changki,
Lee Gary Geunbae,
Jang MyungGil
Publication year - 2006
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.06.0105.0020
Subject(s) - bigram , computer science , dependency (uml) , language model , natural language processing , artificial intelligence , dependency grammar , parsing , trigram
In this paper, we propose a new language model, namely, a dependency structure language model, for information retrieval to compensate for the weaknesses of unigram and bigram language models. The dependency structure language model is based on the first‐order dependency model and the dependency parse tree generated by a linguistic parser. So, long‐distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model, where the dependency structure model gives a better performance than recently proposed language models and the Okapi BM25 method, and the dependency structure is more effective than unigram and bigram in language modeling for information retrieval.