Web Proxy Log Data Mining System for Clustering Users and Search Keywords

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Celal Bayar Üniversitesi Fen Bilimleri Dergisi
Volume:13 Issue:4
Web Proxy Log Data Mining System for Clustering Users and Search Keywords

Web Proxy Log Data Mining System for Clustering Users and Search Keywords

Authors : Turgay BİLGİN, Mustafa AYTEKİN

Pages : 873-881

Doi:10.18466/cbayarfbe.330088

View : 41 | Download : 12

Publication Date : 2017-12-29

Article Type : Research Paper

Abstract :In this study, Internet users were clustered by the search keywords which they type into search bars of search engines. Our proposed software is called UQCS (User Queries Clustering System) and it was developed to demonstrate the efficiency of our hypothesis. UQCS co-operates with the Strehl’s relationship based clustering toolkit and performs segmentation on users based on the keywords they use for searching the web. Internet Proxy server logs were parsed and query strings were extracted from the search engine URL’s and the resulting IP-Term matrix was converted into a similarity matrix using Euclidean, Jaccard, Cosine Distance and Pearson Correlation Distance metrics. K- Means and graph-based OPOSSUM algorithm were used to perform clustering on the similarity matrices. Results were illustrated by using CLUSION visualization toolkit.
Keywords : Data mining, Document clustering, Graph clustering, web mining

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.