Distributed Feature Sets for Document Specific Key-Phrase Extraction-Reference-Cited by-同舟云学术

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Distributed Feature Sets for Document Specific Key-Phrase Extraction

Published:2022-04-01 Issue:2 Volume:54 Page:139-167
ISSN:0196-9722
Container-title:Cybernetics and Systems
language:en
Short-container-title:Cybernetics and Systems

Author:

Alotaibi Fahd Saleh¹,Sharma Saurabh²³

Affiliation:

1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

2. University Institute of Engineering and Technology, Panjab University Chandigarh, Chandigarh, India

3. Thapar Institute of Engineering and Technology, Patiala, India

Funder

Deanship of Scientific Research (DSR), King Abdulaziz University Jeddah

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Information Systems,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/01969722.2022.2055990

Reference53 articles.

1. Exploiting extensible background knowledge for clustering-based automatic keyphrase extraction

2. Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors

3. Bennani-Smires, K., C. Musat, A. Hossmann, M. Baeriswyl, and M. Jaggi. 2018. Simple unsupervised keyphrase extraction using sentence embeddings. In Proceedings of the 22nd Conference on Computational Natural Language Learning, 221–29.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Keyphrase Extraction Using Enhanced Word and Document Embedding;IETE Journal of Research;2022-08-07

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