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
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
Bayesian extension to the language model for ad hoc information retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Formal multiple-bernoulli models for language modeling
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Query refinement based on topical term clustering
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
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We present a new retrieval method based on multiple-Bernoulli model and multinomial model in this paper. We use the multiple-Bernoulli model and multinomial model to estimate the term probabilities by importing the conjugate prior and the term frequencies, and use Dirchlet method to smooth the models for solving the ”zero probability” problem of the language model.