A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Integrating word relationships into language models
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using term relationships in language models for information retrieval
Proceedings of the 14th ACM international conference on Information and knowledge management
Query expansion using a collection dependent probabilistic latent semantic thesaurus
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
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Language modelling is new form of information retrieval that is rapidly becoming the preferred choice over probabilistic and vector space models, due to the intuitiveness of the model formulation and its effectiveness. The language model assumes that all terms are independent, therefore the majority of the documents returned to the ser will be those that contain the query terms. By making this assumption, related documents that do not contain the query terms will never be found, unless the related terms are introduced into the query using a query expansion technique. Unfortunately, recent attempts at performing a query expansion using a language model have not been in-line with the language model, being complex and not intuitive to the user. In this article, we introduce a simple method of query expansion using the naïve Bayes assumption, that is in-line with the language model since it is derived from the language model. We show how to derive the query expansion term relationships using probabilistic latent semantic analysis (PLSA). Through experimentation, we show that using PLSA query expansion within the language model framework, we can provide a significant increase in precision