Global ETD Search
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Showing 1 to 7 of 7 for “"Pseudo-Relevance Feedback"”.
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Axiomatic analysis of smoothing methods in language models for pseudo-relevance feedback
Pseudo-Relevance Feedback (PRF) is an important general technique for improving retrieval effectiveness without requiring any user effort. Several state-of-the-art PRF models are based on the language modeling approach where a query language model is learned based on feedback documents. In all …
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Entity finder: A system for entity web page retrieval using pseudo-relevance feedback
… special retrieval problem, and propose a novel pseudo-relevance feedback approach to improve the retrieval accuracy. We evaluate our system over a dataset containing 112 alumni in the College of Engineering of the University of Illinois, and show that our system can effectively retrieve relevant …
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Investigating ontology based query expansion using a probabilistic retrieval model
… ways and in this work we consider the use of relevance feedback and pseudo-relevance feedback for query expansion. We examine relevance feedback and pseudo-relevance to ascertain the existence of performance differences between relevance feedback and pseudo-relevance feedback. The information …
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Improving the effectiveness of language modeling approaches to information retrieval: bridging the theory-effectiveness gap
… modeling the highly empirical notion of relevance within a standard statistical model has led to slow progress in optimizing language modeling approaches; after more than one decade of research, the basic language modeling approach to retrieval still remains the same. This suggests that …
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Making a Better Query: Find Good Feedback Documents and Terms via Semantic Associations
… the original query with more related terms. Pseudo relevance feedback (PRF) has proven to be effective to expand origin queries and improve the performance of IR. It assumes the top k ranked documents obtained through the first round retrieval are relevant as feedback documents, and expand …
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Enabling access to and exploration of information graphs
… we study algorithms and implementations based on pseudo-relevance feedback for \emph{exemplar query suggestion}, along with an in-depth study of their effectiveness. Finally, as there exist many graph databases, high heterogeneity can be observed in the functionalities and performances of these …
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Leveraging user interaction to improve search experience with difficult and exploratory queries
… propose and study three methods for interactive feedback that allow the search systems to interactively improve the quality of retrieval results for difficult and exploratory queries: question feedback, sense feedback and concept feedback. All three methods are based on a novel question-guided …