An Enhanced Web Mining Technique for Image Search using Weighted PageRank based on Visit of Links and Fuzzy K-Means Algorithm

Rashmi Sharma, Kamaljit Kaur

Abstract: Web mining is growing very rapidly. It extracts the rich information in the form of audio; video; content; links and images. The World Wide Web contains huge number of web pages and information available within web pages. When a user gives a query to the search engine; it generally returns a large amount of information in response to users query. To retrieve required information from Web pages; web mining performs various techniques. This paper proposed the hybrid technique of Weighted PageRank based on Visit of Links and Fuzzy K-Means algorithms which are applied on the search result. This paper described Fuzzy K-Means algorithm is used to group the given data-set into clusters and Weighted PageRank is used to re-rank the data according to the visit of links in the web pages. We have fetched the relevant information such as image links; images and total hyperlinks from a URL using the hybrid approach. Furthermore; we have done analysis on hybrid algorithms by applying valid parameters like execution time; recall; precision and f-measure.

Keywords: PageRank, Weighted PageRank, Weighted PageRank based on Visit of Links, K-Means and Fuzzy K-Means

How to Cite?: Rashmi Sharma, Kamaljit Kaur, "An Enhanced Web Mining Technique for Image Search using Weighted PageRank based on Visit of Links and Fuzzy K-Means Algorithm", Volume 3 Issue 6, June 2014, International Journal of Science and Research (IJSR), Pages: 2083-2089, https://www.ijsr.net/getabstract.php?paperid=2014650, DOI: https://dx.doi.org/10.21275/2014650

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