Abstract: Information retrieval involves obtaining some wanted information in a database. In this paper, we used the power link to improve the extracted field association terms from corpus by the proposed algorithm to support the machine to take the right decision and attach the candidate words in their convenient position in dictionary of the field association terms. Power Link is used as a quantitative tool to compute the co-citation relation among two words depending on the co-frequency and distances among instances of the words. In this paper, concept of the Power Link as well as modifications of the rules is used to classify the scientific papers into its proper field. In this paper, instead of whole document, a given document will be divided into three parts, namely, title, abstract and body. A given term will be given a weight that depends on the location of the term inside a specific document. The greatest weight will be given to the title then the abstract then the body, respectively. Results show an improvement in precision, recall and F measure.

El-Sayed Atlam, Dawlat A. El A.Mohamed, Fayed Ghaleb and Doaa Abo-Shady, “An Improvement of FA Terms Dictionary using Power Link and Co-Word Analysis” International Journal of Advanced Computer Science and Applications(IJACSA), 9(2), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090233

@article{Atlam2018,
title = {An Improvement of FA Terms Dictionary using Power Link and Co-Word Analysis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090233},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090233},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {2},
author = {El-Sayed Atlam and Dawlat A. El A.Mohamed and Fayed Ghaleb and Doaa Abo-Shady}
}