A Text Mining Algorithm Optimising the Determination of Relevant Studies

Mouayad Khashfeh, Moamin A. Mahmoud, Mohd Sharifuddin Ahmad

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

Abstract

In this paper, we develop a text mining algorithm that influences the identification of relevant literature studies. The algorithm consists of three processes, detection process; preparation process; and mining process. The detection process includes the determination of document language and abstract and keywords. The Preparation includes the processes, split content to paragraphs; paragraph length determination; converting text to lower case; text typography factor; content tokenization, removing stop words. Finally, the mining includes the processes, regular expression; normalization; grouping and computing frequency. The proposed algorithm would be useful in providing an alternative means of searching highly relevant content from large databases.

Original languageEnglish
Title of host publicationInternational Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538678565
DOIs
Publication statusPublished - 19 Nov 2018
Event2018 International Symposium on Agents, Multi-Agent Systems and Robotics, ISAMSR 2018 - Putrajaya, Malaysia
Duration: 27 Aug 2018 → …

Publication series

NameInternational Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018

Other

Other2018 International Symposium on Agents, Multi-Agent Systems and Robotics, ISAMSR 2018
CountryMalaysia
CityPutrajaya
Period27/08/18 → …

Fingerprint

Text Mining
Preparation
Process Mining
Regular Expressions
Grouping
Normalization
Mining
Computing
Alternatives

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Optimization

Cite this

Khashfeh, M., A. Mahmoud, M., & Ahmad, M. S. (2018). A Text Mining Algorithm Optimising the Determination of Relevant Studies. In International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018 [8540553] (International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISAMSR.2018.8540553
Khashfeh, Mouayad ; A. Mahmoud, Moamin ; Ahmad, Mohd Sharifuddin. / A Text Mining Algorithm Optimising the Determination of Relevant Studies. International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018).
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Khashfeh, M, A. Mahmoud, M & Ahmad, MS 2018, A Text Mining Algorithm Optimising the Determination of Relevant Studies. in International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018., 8540553, International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018, Institute of Electrical and Electronics Engineers Inc., 2018 International Symposium on Agents, Multi-Agent Systems and Robotics, ISAMSR 2018, Putrajaya, Malaysia, 27/08/18. https://doi.org/10.1109/ISAMSR.2018.8540553

A Text Mining Algorithm Optimising the Determination of Relevant Studies. / Khashfeh, Mouayad; A. Mahmoud, Moamin; Ahmad, Mohd Sharifuddin.

International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8540553 (International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018).

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

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AB - In this paper, we develop a text mining algorithm that influences the identification of relevant literature studies. The algorithm consists of three processes, detection process; preparation process; and mining process. The detection process includes the determination of document language and abstract and keywords. The Preparation includes the processes, split content to paragraphs; paragraph length determination; converting text to lower case; text typography factor; content tokenization, removing stop words. Finally, the mining includes the processes, regular expression; normalization; grouping and computing frequency. The proposed algorithm would be useful in providing an alternative means of searching highly relevant content from large databases.

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Khashfeh M, A. Mahmoud M, Ahmad MS. A Text Mining Algorithm Optimising the Determination of Relevant Studies. In International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8540553. (International Symposium on Agents, Multi-Agent Systems and Robotics 2018, ISAMSR 2018). https://doi.org/10.1109/ISAMSR.2018.8540553