Using Web server logs to improve site design
Proceedings of the 16th annual international conference on Computer documentation
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Data Mining for Measuring and Improving the Success of Web Sites
Data Mining and Knowledge Discovery
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
ACM SIGIR Forum
Measuring e-Commerce effectiveness: a conceptual model
SAICSIT '03 Proceedings of the 2003 annual research conference of the South African institute of computer scientists and information technologists on Enablement through technology
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Guidance Performance Indicator " Web Metrics for Information Driven Web Sites
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Web performance indicator by implicit user feedback – application and formal approach
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
Improving semantic consistency of web sites by quantifying user intent
ICWE'05 Proceedings of the 5th international conference on Web Engineering
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The evaluation of information driven websites by analysis of serverside available data is the objective of our approach. In our former work we developed techniques for evaluation of non-transactional websites by regarding the author's intentions and using only based on implicit user feedback. In several case studies we got aware that in single cases unsatisfied users had been evaluated positively. This divergence could be explained by not having considered the user's intentions. We propose in this approach to integrate search queries within referrer informaiton as freely available information about the user's intentions. By integrating this new source of information into our meta model of website structure, content and author intention, we enhance the formerly developed web success metric GPI. We apply well understood techniques such as PLSA for text categorization. Based on the latent semantic we construct a new indicator evaluating the website with respect to the user intention. By ranking all webpages with respect to the user intention manifested in the search query, we acchieve an individualized measure to evaluate a session by the user's initial intention. In contrast to manual assignments of weights by the website author, our proposed measure is purely calculated allowing a generic assessment of websites without manual intervention.In a case study we can show, that this indicator evaluates the quality and usability of a website more accurately by taking the user's goals under consideration. We can also show, that the initially mentioned diverging user sessions, can now be assessed according to the user's perception.Due to limited information on the host side, without direct access to the client side, still some assumptions remain to be made.