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  • GC-CCA 2011
  • 16.Cnf-145
Papers Published at GC-CCA 2011
All 9 Papers
IDAuthors and TitlePages
16.Cnf-64 Prof. Ahmed Dooguy Kora
Mr. Octave Ringar
Dr. Samuel Ouya
Prof. Jean-Pierre Cances
Wavelength division multiplexing of 1D-code division multiple access systems limitations in optical network using large spectrum sources
16.Cnf-87 Dr. Musaria Mahmood
Prof. Fawzi Al-Naima
Prof. Nikolaos Uzunoglu
OPNET simulation of data transmission network: a case study for control system in a petroleum refinery complex in Iraq

GS Citations

Ms. Imane Benkhelifa
Dr. Samira Moussaoui
APPL: Anchor path planning based localization for wireless sensor networks
16.Cnf-124 Dr. Omar Batarfi
Mrs. Arwa Diwali
A Proposed Model for Certificate Validation in WPKI
16.Cnf-126 Mr. Badoui Yamine
Prof. Rahim Tafazolli
Dynamic Storage Method for the UMTS Radio Resource Control
16.Cnf-131 Mr. Amin Ebrahimzadeh
Dr. Javad Musevi Niya
Energy Efficient Centralized Clustering Hierarchical Routing Protocol for Wireless Sensor Networks
16.Cnf-142 Dr. Abdul_bary Suleiman
Dr. Mahmod Mahmod
Mr. Omar W. Hamdon
Real-Time TMS3206713 DSP-Based Adaptive Noise Cancellation for Speech Signal Processing
16.Cnf-145 Dr. Rafeeq A. Al-Hashemi
Prof. Hilal Saleh
Dr. Ahmed Alobaidi
Data Mining Implementation for Keywords Extraction
16.Cnf-147 Mr. Leonardo O. Iheme
On the information content of an image transmitted over fading channels using CC versus RS-CC coding
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 37-42
Topics Design of Computing Algorithms
Programming Languages
ISSN 2227-331X
BibTeX @inproceedings{145CCA2011,
title={Data Mining Implementation for Keywords Extraction},
author={Rafeeq A. Al-Hashemi, and Hilal Saleh, and Ahmed Alobaidi},
booktitle={2011 Global Congress on Communications, Computers and Applications (GC-CCA 2011)},
organization={Mosharaka for Research and Studies} }
Paper Views 22 Paper Views Rank 267/524
Paper Downloads 19 Paper Downloads Rank 181/524
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