An approach to natural language for document retrieval
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Integrating Boolean queries in conjunctive normal form with probabilistic retrieval models
Information Processing and Management: an International Journal - The Potential for Improvments in Commerical Document Retrieval Systems
Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
An analytic measure predicting information retrieval system performance
Information Processing and Management: an International Journal
Some inconsistencies and misnomers in probabilistic information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Term dependence: truncating the Bahadur Lazarsfeld expansion
Information Processing and Management: an International Journal
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
On relevance weights with little relevance information
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
On the necessity of term dependence in a query space for weighted retrieval
Journal of the American Society for Information Science
Term dependence: a basis for Luhn and Zipf models
Journal of the American Society for Information Science and Technology
Information Retrieval
PRINCIPAR: an efficient, broad-coverage, principle-based parser
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
The conflict detection and resolution in knowledge merging for image annotation
Information Processing and Management: an International Journal
A "Bag" or a "Window" of Words for Information Filtering?
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Lexical and Syntactic knowledge for Information Retrieval
Information Processing and Management: an International Journal
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Binary lexical relations for text representation in information retrieval
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Evaluation of system measures for incomplete relevance judgment in IR
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Optimising search engines using evolutionally adapted language models in typed dependency parses
SIDE'12 Proceedings of the 2012 international conference on Swarm and Evolutionary Computation
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Most previous information retrieval (IR) models assume that terms of queries and documents are statistically independent from each other. However, conditional independence assumption is obviously and openly understood to be wrong, so we present a new method of incorporating term dependence into a probabilistic retrieval model by adapting a dependency structured indexing system using a dependency parse tree and Chow Expansion to compensate the weakness of the assumption. In this paper, we describe a theoretic process to apply the Chow Expansion to the general probabilistic models and the state-of-the-art 2-Poisson model. Through experiments on document collections in English and Korean, we demonstrate that the incorporation of term dependences using Chow Expansion contributes to the improvement of performance in probabilistic IR systems.