Word Embeddings-Based Pseudo Relevance Feedback Using Deep Averaging Networks for Arabic Document Retrieval

Word Embeddings-Based Pseudo Relevance Feedback Using Deep Averaging Networks for Arabic Document Retrieval

Pseudo relevance feedback (PRF) is a powerful query expansion (QE) technique that prepares queries using the top k pseudo-relevant documents and choosing expansion elements. Traditional PRF frameworks have robustly handled vocabulary mismatch corresponding to user queries and pertinent documents; ne...

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Bibliographic Details
Main Authors: Farhan Yasir Hadi, Noah Shahrul Azman Mohd, Mohd Masnizah, Atwan Jaffar
Format: Article
Language:English
Published: Korea Institute of Science and Technology Information 2021-06-01
Series:Journal of Information Science Theory and Practice
Subjects:
automatic query expansion
information retrieval
word embedding
deep averaging networks
pseudo relevance feedback
arabic document retrieval on trec collection
Online Access:https://doi.org/10.1633/JISTaP.2021.9.2.1

Internet

https://doi.org/10.1633/JISTaP.2021.9.2.1

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