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
Dissemination of collection wide information in a distributed information retrieval system
SIGIR '95 Proceedings of the 18th 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
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
Global term weights in distributed environments
Information Processing and Management: an International Journal
Introduction to Information Retrieval
Introduction to Information Retrieval
Statistical Language Models for Information Retrieval A Critical Review
Foundations and Trends in Information Retrieval
A statistical approach to mechanized encoding and searching of literary information
IBM Journal of Research and Development
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With the rapid development of the information technology, there exists the difficulty in deploying state-of-the-art retrieval models in environments such as peer-to-peer networks and pervasive computing, where it is expensive or even infeasible to maintain the global statistics. To this end, this paper presents an investigation in the validity of different statistical assumptions of term distributions. Based on the findings in this investigation, a variety of weighting models, called NG (standing for "no global statistics") models, are derived from the Divergence from Randomness framework, in which only the within-document statistics are used in the relevance weighting. Compared to the state-of-the-art weighting models in extensive experiments on various standard TREC test collections, our proposed NG models can provide acceptable retrieval performance in ad-hoc search, without the use of global statistics.