Utilizing probase in open directory project-based text classification

So Young Jun, Dinara Aliyeva, Ji Min Lee, Sang-Geun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Open Directory Project (ODP) has been successfully utilized in text classification due to its representation ability of various categories. However, ODP includes a limited number of entities, which play an important role in classification tasks. In this paper, we enrich the semantics of ODP categories with Probase entities. To effectively incorporate Probase entities in ODP categories, we first represent each ODP category and Probase entity in terms of concepts. Next, we measure the semantic relevance between an ODP category and a Probase entity based on the concept vector. Finally, we use Probase entity to enrich the semantics of the ODP categories. Our experimental results show that the proposed methodology exhibits a significant improvement over state-of-the-art techniques in the ODP-based text classification.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2018-July
ISBN (Electronic)9781509060207
DOIs
Publication statusPublished - 2018 Oct 12
Event2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Rio de Janeiro, Brazil
Duration: 2018 Jul 82018 Jul 13

Other

Other2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
CountryBrazil
CityRio de Janeiro
Period18/7/818/7/13

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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  • Cite this

    Jun, S. Y., Aliyeva, D., Lee, J. M., & Lee, S-G. (2018). Utilizing probase in open directory project-based text classification. In 2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings (Vol. 2018-July). [8491626] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FUZZ-IEEE.2018.8491626