Author(s): Akhtar, M. D. ; Manupati, V. K. ; Varela, M.L.R. ; Putnik, Goran D. ; Madureira, A. M. ; Abraham, Ajith
Date: 2018
Persistent ID: https://hdl.handle.net/1822/62959
Origin: RepositóriUM - Universidade do Minho
Subject(s): Classification; Naive bayes classifier; Support vector machine classifier; Small and medium scale enterprises; Naïve bayes classifier
With the recent development of weblogs and social networks, many supplier industries share their data on different websites and weblogs. Even the Small-to-Medium sized enterprises (SMEs) in the manufacturing sector (as well as non-manufacturing sector) are rapidly strengthening their web presence in order to improve their visibility, customer reachability and remain competitive in the global market. Our study aims to classify data into various groups so that users can identify the most appropriate content based on their choice at any given time. To classify and characterize manufacturing suppliers in supply chain through their capability narratives and textual portfolios obtained from websites of such suppliers online source portals for testing and Naive Bayes and support vector machine (SVM) Classification method at term-level for classification has been used. The performance of the proposed classifier was tested experimentally based on the standard metrics such as precision, recall, and F-measure.
