Title: XML web quality analysis by employing MFCM clustering technique and KNN classification

Authors: M. Gopianand; P. Jaganathan

Addresses: Department of Computer Applications, PSNA College of Engineering and Technology, Dindigul, India ' Department of Computer Applications, PSNA College of Engineering and Technology, Dindigul, India

Abstract: The great accomplishment of web search engine is keyword search which is the most trendy search representation for regular consumers. It is permits that the consumer can create the queries without the knowledge of query language and the database schema. So, it is also considered as a user friendly method. The quality of XML web has to be accurate if the exact queries have to be answered. Here we have proposed a method to access the quality of the XML web by analysing the keyword present in the XML web based on the respective keyword search. In our proposed method we collect number of XML documents and are clustered based on the keyword depending on the type of XML files. Modified fuzzy C means (MFCM) is used for clustering. Once the clustering based on the respective keyword is done, we classify the XML web based on quality of the data by utilising KNN classifier.

Keywords: XML web; K nearest neighbour; error value; classification accuracy; feature vectors.

DOI: 10.1504/IJBIDM.2020.108041

International Journal of Business Intelligence and Data Mining, 2020 Vol.17 No.1, pp.1 - 11

Received: 23 Nov 2016
Accepted: 17 Nov 2017
Published online: 02 Jul 2020 *

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