DocumentCode
3570918
Title
Finding the most evident co-clusters on web log dataset using frequent super-sequence mining
Author
Xinran Yu ; Korkmaz, Turgay
Author_Institution
Comput. Sci. Dept., Univ. of Texas at San Antonio, San Antonio, TX, USA
fYear
2014
Firstpage
529
Lastpage
536
Abstract
It is important to mine the weblog dataset to find interesting and helpful information. There are three kinds of mining on weblog data which are web usage mining, web structure mining and web content mining. In our research, we are going to investigate web pages structure and find the most evident groups of users and web pages. Nowadays, big data is everywhere. Facing huge amount of web logs, it is not always necessary to group all the users in a web log dataset into different clusters, sometimes, finding out the major dominant user groups and the corresponding web pages is more important. In this paper, we are going to investigate a new way to search the most evident co-clusters of users and the corresponding web pages in the web log dataset using frequent super-sequence mining technique. Through experiments we find interesting results.
Keywords
Web sites; data mining; pattern clustering; Web content mining; Web log dataset mining; Web page structure; Web structure mining; Web usage mining; frequent super-sequence mining technique; most evident user coclusters; Clustering algorithms; Data mining; Databases; Market research; Merging; Phase change materials; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Reuse and Integration (IRI), 2014 IEEE 15th International Conference on
Type
conf
DOI
10.1109/IRI.2014.7051935
Filename
7051935
Link To Document