Results 221 to 230 of about 142,435 (303)

Co-Designing Mobile Serious Games to Support Patients With Psoriatic Arthritis and Chronic Pain: Mixed Methods Study.

JMIR Serious Games
Ramalho B, Gomes S, Silva Vicente M, Magalhães F, Gonçalves Costa R, Gama S, Charisis V, Hadjileontiadis L, B Dias S, iPROLEPSIS Consortium.   +9 more
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Semantics-aware query expansion using pseudo-relevance feedback

Journal of Information Science, 2023
In this article, a pseudo-relevance feedback (PRF)–based framework is presented for effective query expansion (QE). As candidate expansion terms, the proposed PRF framework considers the terms that are different morphological variants of the original query terms and are semantically close to them. This strategy of selecting expansion terms
Pankaj Singh, Plaban Kumar Bhowmick
openaire   +2 more sources

Pseudo-Relevance Feedback with Dense Retrievers in Pyserini

Proceedings of the 26th Australasian Document Computing Symposium, 2022
Transformer-based Dense Retrievers (DRs) are attracting extensive attention because of their effectiveness paired with high efficiency. In this context, few Pseudo-Relevance Feedback (PRF) methods applied to DRs have emerged.
Hang Li, Shengyao Zhuang, Xueguang Ma, Jimmy Lin, Guido Zuccon   +4 more
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Pseudo relevance feedback optimization

Information Retrieval Journal, 2021
We propose a method for automatic optimization of pseudo relevance feedback (PRF) in information retrieval. Based on the conjecture that the initial query’s contribution to the final query may not be necessary once a good model is built from pseudo relevant documents, we set out to optimize per query only the number of top-retrieved documents to be ...
Arampatzis A., Peikos G., Symeonidis S.
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Collaborative pseudo-relevance feedback

Expert Systems with Applications, 2013
Pseudo-relevance feedback (PRF) is a technique commonly used in the field of information retrieval. The performance of PRF is heavily dependent upon parameter values. When relevance judgements are unavailable, these parameters are difficult to set. In the following paper, we introduce a novel approach to PRF inspired by collaborative filtering (CF). We
Dong Zhou, Mark Truran, Jianxun Liu, Sanrong Zhang   +3 more
openaire   +1 more source

Improving semantic information retrieval by combining possibilistic networks, vector space model and pseudo-relevance feedback

Journal of information science, 2023
To improve the performance of information retrieval systems (IRSs), we propose in this article a novel approach that enriches the user’s queries with new concepts.
Wiem Chebil, L. Soualmia
semanticscholar   +1 more source

A probabilistic framework for integrating sentence-level semantics via BERT into pseudo-relevance feedback

Information Processing & Management, 2022
Existing pseudo-relevance feedback (PRF) methods often divide an original query into individual terms for processing and select expansion terms based on the term frequency, proximity, position, etc.
Min Pan, Junmei Wang, J. Huang, Angela J. Huang, Qi Chen, Jinguang Chen   +5 more
semanticscholar   +1 more source

Evaluating Elements of Web-Based Data Enrichment for Pseudo-relevance Feedback Retrieval

Conference and Labs of the Evaluation Forum, 2022
In this work, we analyze a pseudo-relevance retrieval method based on the results of web search engines. By enriching topics with text data from web search engine result pages and linked contents, we train topic-specific and cost-efficient classifiers ...
Timo Breuer, Melanie Pest, Philipp Schaer   +2 more
semanticscholar   +1 more source