Sentimental Analysis and LSI Similarity Measure for Efficient Page Ranking
S. Anto1, S.P. Siddique Ibrahim2, S. Siamala Devi3
1Dr. S. Anto, Associate Professor, Department of Computer Science and Engineering, VIT University, Vellore, (Tamil Nadu), India.
2S. P. Siddique Ibrahim, Assistant Professor, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Dr. S. Siamala Devi, Associate Professor, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 28 September 2019 | Revised Manuscript received on 10 November 2019 | Manuscript Published on 22 November 2019 | PP: 1143-1146 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F11900986S319/19©BEIESP | DOI: 10.35940/ijeat.F1190.0986S319
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Abstract: Supplementary factor to the general pagerank calculation which is utilized by Google chrome to rank sites in their web index results is tended to in this paper. These extra factors incorporate couple of ideas which expressly results to build the precision of evaluating the PageRank value. By making a decision about the likeness between the web page content with the text extracted from different site pagesresulted in topmost search using few keywords of the considered page for which the rank is to be determined by utilizing a comparability measure. It results with a worth or rate which speaks to the significance or similarity factor. Further, in a similar strategy if sentimental analysis is applied the search results of the keywords could be analysed with keywords of the page considered, it results with a Sentimental Analysed factor.In this way, one can improve and execute the Page ranking procedure which results with a superior accuracy. Hadoop Distributed File System is used to compute the page rank of input nodes. Python is chosen for parallel page rank algorithm that is executed on Hadoop.
Keywords: Pagerank, Sentimental Analysis, Similarity Factor, Hadoop, Python.
Scope of the Article: Predictive Analysis