Document retrieval using clustering-based Aquila hash-Q optimization with query expansion based on pseudo relevance feedback-Reference-Cited by-同舟云学术

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

Published:2024-04-23 Issue:7 Volume:46 Page:496-507
ISSN:1206-212X
Container-title:International Journal of Computers and Applications
language:en
Short-container-title:International Journal of Computers and Applications

Author:

Inje Bhushan¹²,Nagwanshi Kapil Kumar³,Rambola Radhakrishna²

Affiliation:

1. Amity School of Engineering and Technology, Amity University, Jaipur, India

2. NMIMS University, MPSTME Shirpur, Shirpur Dist Dhule, India

3. Department of Computer Science and Engineering, SoS Engineering and Technology, Guru Ghasidas Vishwavidyalaya, Bilaspur 495009, Chhattisgarh

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/1206212X.2024.2342715

Reference46 articles.

1. Yang W Zhang H Lin J. (2019). Simple applications of BERT for ad hoc document retrieval. arXiv preprint arXiv:1903.10972.

2. Lempel–Ziv compressed structures for document retrieval

3. Relevance-based entity selection for ad hoc retrieval

4. A Principled Approach Using Fuzzy Set Theory for Passage-Based Document Retrieval

5. Statistical language models for query-by-example spoken document retrieval

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