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Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem

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.
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Category

Academic article

Language

English

Author(s)

  • Asma Belhadi
  • Youcef Djenouri
  • Jerry Chun-Wei Lin
  • Chongsheng Zhang
  • Alberto Cano

Affiliation

  • SINTEF Digital / Mathematics and Cybernetics
  • Norwegian University of Science and Technology
  • Western Norway University of Applied Sciences
  • University of Science and Technology 'Houari Boumediene' Algiers
  • Henan University
  • Virginia Commonwealth University

Year

2020

Published in

IEEE Access

Volume

8

Page(s)

10569 - 10583

View this publication at Norwegian Research Information Repository