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Performance evaluation of RM-MapReducer in web page categorization

Publication Type : Journal Article

Publisher : Journal of Engineering and Applied Sciences

Source : Journal of Engineering and Applied Sciences, Medwell Journals, Volume 13, Issue 23, p.10037-10038 (2018)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057995786&doi=10.3923%2fjeasci.2018.10037.10038&partnerID=40&md5=351c1f33325adc56b6bcd5d1afdc3985

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2018

Abstract : This study presents the performance evaluation of Relevancy Measure based MapReducer (RM-MapReducer) in supporting web page categorization with different datasets between 200 and 400 web pages as test data. Experiments were performed using datasets of WebKB and ODP with the real time crawler dataset. It was observed that the real time crawler dataset provides better results compared to the other dataset of WebKB and ODP using MapReduce programming model. © Medwell Journals, 2018.

Cite this Research Publication : P. Malarvizhi and Dr. Radhika N., “Performance evaluation of RM-MapReducer in web page categorization”, Journal of Engineering and Applied Sciences, vol. 13, no. 23, pp. 10037-10038, 2018.

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