AHP based feature ranking model using string similarity for resolving name ambiguity

Document Type : Research Paper

Authors

Department of Computer Applications, PSG College of Technology, Coimbatore, Tamilnadu, India

Abstract

In recent years of Natural Language Processing research, the name ambiguity problem remains unresolved while retrieving the information of author names from bibliographic citations in a digital library system. In this paper, a feature ranking model is investigated that resolve the ambiguity problem with Analytical Hierarchy Process (AHP). The AHP procedure prioritizes and assigns the weights for certain criteria which forms a judgemental matrix called pairwise comparison matrix. The result of the AHP analysis aims to get the preprocessing level using Levenshtein Distance. Finally, the AHP helps to find the co-author criteria as the highest priority than the other criteria taken from the digital library data set.

Keywords

Volume 12, Special Issue
January 2021
Pages 1745-1751
  • Receive Date: 28 November 2021
  • Accept Date: 28 November 2021
  • First Publish Date: 28 November 2021