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AHP based feature ranking model using string similarity for resolving name ambiguity | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 1745-1751 اصل مقاله (635.33 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5862 | ||
| نویسندگان | ||
| M. Subathra* ؛ V. Umarani | ||
| Department of Computer Applications, PSG College of Technology, Coimbatore, Tamilnadu, India | ||
| تاریخ دریافت: 18 مهر 1400، تاریخ بازنگری: 11 آبان 1400، تاریخ پذیرش: 03 آذر 1400 | ||
| چکیده | ||
| 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. | ||
| کلیدواژه‌ها | ||
| NLP؛ citations؛ digital library؛ Levenshtein distance؛ AHP | ||
| مراجع | ||
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[1] T. Anwar and M. Abulaishy, Namesake alias mining on the web and its role towards suspect tracking, Info. Sci. 276 (2014) 123–145. [2] N. An, L. Jiang, J. Wang, P. Luo, M. Wang and B. N. Li, Towards detection of aliases without string similarity, Info. Sci. 261 (2014) 89–100. [3] R.G. Cota, A.A. Ferreira, C. Nascimento, M.A. Gon¸calves and A.H. Laender, An unsupervised heuristic-based hierarchical method for name disambiguation in bibliographic citations, JASIST 61(9) (2010) 1853–1870. [4] N. Fernandez, J.A. Fisteus, L. Sanchez and G. Lopez, Identity rank: named entity disambiguation in the news domain, Expert Syst. Appl. 39(10) (2012) 9207–9221. [5] A. Ferreira, M. Gon¸calves and A. Laender, A brief survey of automatic methods for author name disambiguation, ACM SIGMOD Record 41 (2012) 15–26. [6] F.H. Levin and C.A. Heuser, Evaluating the use of social networks in author name disambiguation in digital libraries, J. Inf. Data Manag.1(2) (2010) 183–198. [7] B. Madhuri, S.T. Rao, M. Padmaja and A.J. Chandulal, Evaluating website based on the Grey clustering theory combined with AHP, Int. J. Eng. Tech. 2(2) (2010) 71-76. [8] Q. Shen and T. Boongoen, Fuzzy orders-of-magnitude-based link analysis for qualitative alias detection, IEEE Trans. Knowledge Data Engin. 24(4) (2012) 649–663. [9] J. Tang, A.C.M. Fong, B. Wang and J. Zhang, A unified probabilistic framework for name disambiguation in digital library, IEEE Trans. Knowledge Data Engin. 24(6) (2012) 975–987. [10] O. Vechtomova and S.E. Robertson, A domain-independent approach to finding related entities, Inf. Proces. Manag. 48(4) (2012) 654–670. [11] A. Veloso, A.A. Ferreira, M.A. Gon¸calves, A.H. Laender and W.Jr. Meira, Cost-effective on-demand associative author name disambiguation, Inf. Proces. Manag. 48(4) (2012) 680–697. [12] H. Wu, B. Li, Y. Pei and J. He, Unsupervised author disambiguation using Dempster–Shafer theory, Scientomet. 101 (2014) 1955–1972. [13] J. Zhu, A Multiple-Layer Clustering Approach to the Name Ambiguity Problem, School of ITEE, University of Queensland, Australia, Fang Yang, School of Business, Renmin University of China, China. | ||
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