Automatic resource compilation by analyzing hyperlink structure and associated text
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Finding related pages in the World Wide Web
WWW '99 Proceedings of the eighth international conference on World Wide Web
I/O-efficient techniques for computing pagerank
Proceedings of the eleventh international conference on Information and knowledge management
Adaptive on-line page importance computation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Effectively Finding Relevant Web Pages from Linkage Information
IEEE Transactions on Knowledge and Data Engineering
CNSR '04 Proceedings of the Second Annual Conference on Communication Networks and Services Research
ACM Transactions on Internet Technology (TOIT)
Link analysis ranking: algorithms, theory, and experiments
ACM Transactions on Internet Technology (TOIT)
PageRank as a function of the damping factor
WWW '05 Proceedings of the 14th international conference on World Wide Web
Ranking systems: the PageRank axioms
Proceedings of the 6th ACM conference on Electronic commerce
Page quality: in search of an unbiased web ranking
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Identifying Interesting Customers through Web Log Classification
IEEE Intelligent Systems
Web Structure Mining for Usability Analysis
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Page-reRank: Using Trusted Links to Re-Rank Authority
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
MailRank: using ranking for spam detection
Proceedings of the 14th ACM international conference on Information and knowledge management
Hypergraph partitioning for faster parallel pagerank computation
EPEW'05/WS-FM'05 Proceedings of the 2005 international conference on European Performance Engineering, and Web Services and Formal Methods, international conference on Formal Techniques for Computer Systems and Business Processes
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With vibrant and rapidly growing web, website complexity is constantly increasing, making it more difficult for users to quickly locate the information they are looking for. This, on the other hand, becomes more and more important due to the widespread reliance on the many services available on the Internet nowadays. Web mining techniques have been successfully used for quite some time, for example in search engines like Google, to facilitate retrieval of relevant information. This paper takes a different approach, as we believe that not only search engines can facilitate the task of finding the information one is looking for, but also an optimization of a website's internal structure, which is based on previously recorded user behavior. In this paper, we will present a novel approach to identifying problematic structures in websites. This method compares user behavior, derived via web log mining techniques, to an analysis of the website's link structure obtained by applying the Weighted PageRank algorithm (see [19]). We will then show how to use these intermediate results in order to point out problematic website structures to the website owner.