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  • 16.Cnf-145
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16.Cnf-145 Paper View Page
Title Data Mining Implementation for Keywords Extraction
Authors Dr. Rafeeq A. Al-Hashemi, Al-Hussein Bin Talal University, Ma'an, Jordan
Prof. Hilal Saleh, University of Technology, Baghdad, Iraq
Dr. Ahmed Alobaidi, University of Technology, Baghdad, Iraq
Abstract Keywords are useful for a variety of purposes, including summarizing, indexing, labeling, categorization, clustering, and searching. The objective of the proposed system is to automatic keyword extraction. The proposed system solves this problem through many statistics and linguistic approaches in addition to the novel use of data mining. The entered document first, pre-processed to remove noisy data, word tagging, and word stemming. Second, three extracting approaches utilized in the proposed system, N-gram approach; part-of-speech approach (POS) that extracts phrases, which match a set of patterns, and NP-chunk which extract noun phrases. The proposed system uses a scoring system to give a weight for each candidate keyword depending on many features. The proposed system uses document classification as a subsystem that classifies the document in order to recognize the meaningful keywords that are not frequently used in the class. The proposed system also presents a new approach to use rules mined from the extracted keywords' database to improve the accuracy of keyword extraction, by integrating data mining with the keyword extraction system. We compared the results of our algorithm to the manual extracted keywords, and we obtained a good result reached 74% of accuracy.
Track CSE: Computer Science and Engineering
Conference 4th Mosharaka International Conference on Communications, Computers and Applications (MIC-CCA 2011)
Congress 2011 Global Congress on Communications, Computers and Applications (GC-CCA 2011), 22-24 July 2011, Istanbul, Turkey
Pages --1
Topics Design of Computing Algorithms
Programming Languages
ISSN 2227-331X
Paper Views 676 Paper Views Rank 71/527
Paper Downloads 220 Paper Downloads Rank 84/527
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