Results 191 to 200 of about 10,903 (240)
Some of the next articles are maybe not open access.
Predicting document effectiveness in pseudo relevance feedback
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011Pseudo relevance feedback (PRF) is one of effective practices in Information Retrieval. In particular, PRF via the relevance model (RM) has been widely used due to the theoretical soundness and effectiveness. In a PRF scenario, an underlying relevance model is inferred by combining language models of the top retrieved documents where the contribution ...
Mostafa Keikha +3 more
openaire +1 more source
Pseudo-relevance feedback query based on Wikipedia
2012 IEEE International Conference on Granular Computing, 2012The traditional information retrieval (IR) model always only use the BOW (bag-of-words)-based retrieval model or Concepts-based retrieval model. However BOW-based model ignore the rich semantic relations between the words and text, and Concept-based model always bring in the noisy concepts and loss the precision.
Tingting He, Xionglu Dai
openaire +1 more source
Semantics-aware query expansion using pseudo-relevance feedback
Journal of Information Science, 2023In 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 +1 more source
Pseudo Topic Analysis for Boosting Pseudo Relevance Feedback
2019Traditional Pseudo Relevance Feedback (PRF) approaches fail to mode real-world intricate user activities. They naively assume that the first-pass top-ranked search results, i.e. the pseudo relevant set, have potentially relevant aspects for the user query.
Rong Yan, Guanglai Gao
openaire +1 more source
Pseudo-Relevance Feedback for Multimedia Retrieval
2003Video information retrieval requires a system to find information rele-vant to a query which may be presented simultaneously in different ways through a text description, audio, still images and/or video sequences. The actual search also takes place in the text, audio, image or video domain.
Rong Yan +2 more
openaire +1 more source
Flexible pseudo-relevance feedback via selective sampling
ACM Transactions on Asian Language Information Processing, 2005Although Pseudo-Relevance Feedback (PRF) is a widely used technique for enhancing average retrieval performance, it may actually hurt performance for around one-third of a given set of topics. To enhance the reliability of PRF, Flexible PRF has been proposed, which adjusts the number of pseudo-relevant documents and/or the number of expansion terms for
Tetsuya Sakai +2 more
openaire +1 more source
Pseudo-Relevance Feedback Based on Matrix Factorization
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 2016In information retrieval, pseudo-relevance feedback (PRF) refers to a strategy for updating the query model using the top retrieved documents. PRF has been proven to be highly effective in improving the retrieval performance. In this paper, we look at the PRF task as a recommendation problem: the goal is to recommend a number of terms for a given query
Hamed Zamani +3 more
openaire +1 more source
Improving pseudo-relevance feedback via tweet selection
Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013Query expansion methods using pseudo-relevance feedback have been shown effective for microblog search because they can solve vocabulary mismatch problems often seen in searching short documents such as Twitter messages (tweets), which are limited to 140 characters.
Taiki Miyanishi +2 more
openaire +1 more source
Term Proximity Constraints for Pseudo-Relevance Feedback
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017Pseudo-relevance feedback (PRF) refers to a query expansion strategy based on top-retrieved documents, which has been shown to be highly effective in many retrieval models. Previous work has introduced a set of constraints (axioms) that should be satisfied by any PRF model.
Ali Montazeralghaem +2 more
openaire +1 more source
Hyperlink-extended pseudo relevance feedback for improved microblog retrieval
Proceedings of the first international workshop on Social media retrieval and analysis, 2014Microblog retrieval has received much attention in recent years due to the wide spread of social microblogging platforms such as Twitter. Many research studies investigated different approaches for microblog retrieval. Query expansion is one of the approaches that showed stable performance for improving microblog retrieval effectiveness.
El-Ganainy, Tarek +2 more
openaire +1 more source