Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
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 language modeling approach to information retrieval
A language modeling approach to information retrieval
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
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
The Importance of Prior Probabilities for Entry Page Search
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Passage retrieval based on language models
Proceedings of the eleventh international conference on Information and knowledge management
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A two-stage mixture model for pseudo feedback
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A framework for selective query expansion
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Regularized estimation of mixture models for robust pseudo-relevance feedback
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Enhancing relevance models with adaptive passage retrieval
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Lexical and Syntactic knowledge for Information Retrieval
Information Processing and Management: an International Journal
Bias-variance analysis in estimating true query model for information retrieval
Information Processing and Management: an International Journal
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In this paper, a new robust relevance model is proposed that can be applied to both pseudo and true relevance feedback in the language-modeling framework for document retrieval. There are at least three main differences between our new relevance model and other relevance models. The proposed model brings back the original query into the relevance model by treating it as a short, special document, in addition to a number of top-ranked documents returned from the first round retrieval for pseudo feedback, or a number of relevant documents for true relevance feedback. Second, instead of using a uniform prior as in the original relevance model proposed by Lavrenko and Croft, documents are assigned with different priors according to their lengths (in terms) and ranks in the first round retrieval. Third, the probability of a term in the relevance model is further adjusted by its probability in a background language model. In both pseudo and true relevance cases, we have compared the performance of our model to that of the two baselines: the original relevance model and a linear combination model. Our experimental results show that the proposed new model outperforms both of the two baselines in terms of mean average precision.