A Text Mining Algorithm Optimising the Determination of Relevant Studies
Abstracting; Autonomous agents; Computational methods; Multi agent systems; Robotics; Agent-based model; Document languages; Length determination; Literature studies; Preparation process; Regular expressions; Relevant Studies; Text mining; Data mining
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-235472023-05-29T14:50:11Z A Text Mining Algorithm Optimising the Determination of Relevant Studies Khashfeh M. Mahmoud M.A. Ahmad M.S. 57202812898 55247787300 56036880900 Abstracting; Autonomous agents; Computational methods; Multi agent systems; Robotics; Agent-based model; Document languages; Length determination; Literature studies; Preparation process; Regular expressions; Relevant Studies; Text mining; Data mining 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. � 2018 IEEE. Final 2023-05-29T06:50:11Z 2023-05-29T06:50:11Z 2018 Conference Paper 10.1109/ISAMSR.2018.8540553 2-s2.0-85059753220 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059753220&doi=10.1109%2fISAMSR.2018.8540553&partnerID=40&md5=a1166c04caeb51285ec52f11c7219d9f https://irepository.uniten.edu.my/handle/123456789/23547 8540553 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Abstracting; Autonomous agents; Computational methods; Multi agent systems; Robotics; Agent-based model; Document languages; Length determination; Literature studies; Preparation process; Regular expressions; Relevant Studies; Text mining; Data mining |
| author2 |
57202812898 |
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57202812898 Khashfeh M. Mahmoud M.A. Ahmad M.S. |
| format |
Conference Paper |
| author |
Khashfeh M. Mahmoud M.A. Ahmad M.S. |
| spellingShingle |
Khashfeh M. Mahmoud M.A. Ahmad M.S. A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| author_sort |
Khashfeh M. |
| title |
A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| title_short |
A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| title_full |
A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| title_fullStr |
A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| title_full_unstemmed |
A Text Mining Algorithm Optimising the Determination of Relevant Studies |
| title_sort |
text mining algorithm optimising the determination of relevant studies |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806426514505334784 |
| score |
13.222552 |