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

Yıl 2017, Cilt: 13 Sayı: 4, 873 - 881, 29.12.2017

Turgay Bilgin Mustafa Aytekin

Öz

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.

Anahtar Kelimeler

Data mining, Document clustering, Graph clustering, web mining

Kaynakça

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