Publication: A Text Mining Algorithm Optimising the Determination of Relevant Studies
Date
2018
Authors
Khashfeh M.
Mahmoud M.A.
Ahmad M.S.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
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. � 2018 IEEE.
Description
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