Term dependence: truncating the Bahadur Lazarsfeld expansion
Information Processing and Management: an International Journal
A general language model for information retrieval (poster abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Model-based feedback in the language modeling approach to information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Exploiting syntactic structure of queries in a language modeling approach to IR
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Dependence language model for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
An exploration of axiomatic approaches to information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
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One of important problems of dependence retrieval model is the challenge to integrate both single words and dependencies in one weighting schema. Although there are many retrieval models that exploit term dependencies in language modeling framework, seldom of them simultaneously study the problem on different query types, e.g., short queries and verbose queries. In this paper, we derive an axiomatic dependence model by defining several basic desirable constraints that a retrieval model should meet. The experiment results show that our model significantly and robustly improves retrieval accuracy over the baseline (unigram model) in verbose queries and achieves better performance than some state-of-art dependence models.