Document Type

Article

Original Publication Date

2020

Journal/Book/Conference Title

IEEE Access

Volume

8

First Page

10569

Last Page

10583

DOI of Original Publication

10.1109/ACCESS.2020.2964682

Comments

Originally published at 10.1109/ACCESS.2020.2964682.

Funded in part by the VCU Libraries Open Access Publishing Fund.

Date of Submission

June 2020

Abstract

Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information and speeding up the search performance. A novel algorithm called PM-HR (Pattern Mining for Hashtag Retrieval) is designed to first transform the set of tweets into a transactional database by considering two different strategies (trivial and temporal). After that, the set of the relevant patterns is discovered, and then used as a knowledge-based system for finding the relevant tweets based on users' queries under the similarity search process. Extensive results are carried out on large and different tweet collections, and the proposed PM-HR outperforms the baseline hashtag retrieval approaches in terms of runtime, and it is very competitive in terms of accuracy.

Rights

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/

Is Part Of

VCU Computer Science Publications

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