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
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
Comments
Originally published at 10.1109/ACCESS.2020.2964682.
Funded in part by the VCU Libraries Open Access Publishing Fund.