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
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
SIGIR '92 Proceedings of the 15th 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
Improving automatic query expansion
Proceedings of the 21st 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
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Term dependence: a basis for Luhn and Zipf models
Journal of the American Society for Information Science and Technology
A Corpus-Based Learning Method of Compound Noun Indexing Rules for Korean
Information Retrieval
CRTER: using cross terms to enhance probabilistic information retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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
| Hi-index | 0.00 |
Most previous information retrieval (IR) models assume that terms of queries and documents are statistically independent from each another. However, this kind of conditional independence assumption is obviously and openly understood to be wrong, so we present a new method of incorporating term dependence in probabilistic retrieval model by adapting Bahadur-Lazarsfeld expansion (BLE) to compensate the weakness of the assumption. In this paper, we describe a theoretic process to apply BLE to the general probabilistic models and the state-of-the-art 2-Poisson model. Through the experiments on two standard document collections, HANTEC2.0 in Korean and WT10g in English, we demonstrate that incorporation of term dependences using the BLE significantly contribute to the improvement of performance in at least two different language IR systems.