Results 251 to 260 of about 142,435 (303)

Term Proximity Constraints for Pseudo-Relevance Feedback

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017
Pseudo-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, Hamed Zamani, Azadeh Shakery   +2 more
openaire   +1 more source

Document retrieval using clustering-based Aquila hash-Q optimization with query expansion based on pseudo relevance feedback

International Journal of Computer Applications
A document retrieval system helps users to retrieve the relevant documents corresponding to their query quickly and easily. In the real world, document retrieval is a difficult task due to high volumes of data, unstructured data, and different formats of
Bhushan Inje, K. Nagwanshi, Radhakrishna Rambola   +2 more
semanticscholar   +1 more source

Hyperlink-extended pseudo relevance feedback for improved microblog retrieval

Proceedings of the first international workshop on Social media retrieval and analysis, 2014
Microblog 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, Magdy, Walid, Rafea, Ahmed   +2 more
openaire   +1 more source

Evaluation of Pseudo-Relevance Feedback using Wikipedia

Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval, 2019
Users have specific information needs which are expressed in short queries to information retrieval systems. The queries are unstructured, and they tend to be short and ambiguous in most cases. Using the shallow language statistics including probabilistic or language models such as BM25 or Indri respectively can enhance the retrieval system metrics ...
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Effective pseudo-relevance feedback for spoken document retrieval

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
With the exponential proliferation of multimedia associated with spoken documents, research on spoken document retrieval (SDR) has emerged and attracted much attention in the past two decades. Apart from much effort devoted to developing robust indexing and modeling techniques for representing spoken documents, a recent line of thought targets at the ...
Yi-Wen Chen, Kuan-Yu Chen, Hsin-Min Wang, Berlin Chen   +3 more
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LLM-Assisted Pseudo-Relevance Feedback

arXiv.org
Query expansion is a long-standing technique to mitigate vocabulary mismatch in ad hoc Information Retrieval. Pseudo-relevance feedback methods, such as RM3, estimate an expanded query model from the top-ranked documents, but remain vulnerable to topic ...
David Otero, Javier Parapar
semanticscholar   +1 more source

Pseudo-Relevance Feedback Based on mRMR Criteria

2010
Pseudo-relevance feedback has shown to be an effective method in many information retrieval tasks. Various criteria have been proposed to rank terms extracted from the top ranked document of the initial retrieval results. However, most existing methods extract terms individually and do not consider the impacts of relationships among terms and their ...
Yuanbin Wu, Qi Zhang, Yaqian Zhou, Xuanjing Huang   +3 more
openaire   +1 more source

Pseudo-Relevance Feedback Driven for XML Query Expansion

Journal of Convergence Information Technology, 2010
Pseudo-relevance feedback has been perceived as an effective solution for automatic query expansion. However, a recent study has shown that traditional pseudo-relevance feedback may bring into topic drift and hence be harmful to the retrieval performance.
Zhong Minjuan -, Wan Changxuan -
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A Pseudo-relevance feedback framework combining relevance matching and semantic matching for information retrieval

Information Processing & Management, 2020
Pseudo-relevance feedback (PRF) is a well-known method for addressing the mismatch between query intention and query representation. Most current PRF methods consider relevance matching only from the perspective of terms used to sort feedback documents ...
Junmei Wang, Min Pan, Tingting He, Xiangji Huang, Xueyan Wang, Xinhui Tu   +5 more
semanticscholar   +1 more source

A Theoretical Analysis of Pseudo-Relevance Feedback Models

Proceedings of the 2013 Conference on the Theory of Information Retrieval, 2013
Our goal in this study is to compare several widely used pseudo-relevance feedback (PRF) models and understand what explains their respective behavior. To do so, we first analyze how different PRF models behave through the characteristics of the terms they select and through their performance on two widely used test collections.
Stéphane Clinchant, Eric Gaussier
openaire   +1 more source