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Evaluation in Web Mining (English)
| Description: |
September 20, 2004
In conjunction with Statistical Approaches to Web Mining workshop.
Web mining has become a critical tool for competitive application intelligence. Understanding the behavior of a site's visitors requires creative extensions of KDD techniques for e-commerce and clickstream data: patterns must be discovered from a variety of data sources, and these patterns must be interpreted and transformed into actionable knowledge for redesigns that bring revenue. Redesigns encompass general improvements to information architecture and navigation options, as well as the offering of personalized recommendations and services. At the same time, a reliable discovery and interpretation of patterns cannot ignore the Web content itself. This leads to challenges on Web content mining, including text categorisation, content analysis and extraction of implicit semantics.
These issues are already broadly recognized: The research on Web mining is intensive and, in some cases, goes hand-in-hand with deployment in the market. This leads to the challenge of incorporating Web mining to the internal evaluation processes of the site operator. Web mining can be used to derive indicators that describe marketing success, the appropriateness of distribution channel mixes, or other indicators of a site's or service's success. At the same time, Web mining itself constitutes a major investment and therefore needs to be subjected to a cost-benefit evaluation. Both of these aspects, "Web mining for evaluation" and "Evaluation of Web mining" require systematic methods and a context of project management. The owners of Web sites and Web applications need a complete evaluation framework, in order to derive well-informed decisions for the extend of using Web mining as a tool for data analysis and for the deployment of its results in site and service design.
In this tutorial, we investigate the current state of Web mining evaluation from both viewpoints of evaluating a Web site and evaluating Web mining projects themselves. In particular, we address
- methodologies to derive interesting patterns and success indicators from the data
- integration of the derived patterns with the goals of the institution
- problems related to the development of the web mining project in order to evaluate its success
- computational and application-oriented frameworks for determining costs and benefits, and the role of different perspectives on "success";
- project management frameworks for integrating these and other measures of application success, and for accommodating their respective strengths and weaknesses; and
- infrastructures for deploying Web mining results.
The tutorial draws from the core domains of KDD, covering issues of data preparation, pattern discovery, and pattern analysis. We also draw on the domain of Web marketing that contributes the requirements and the economic measures, on human-computer interaction for user-centric success evaluation, and on project management dealing with gaps to be filled in order to evaluate the impact of a web mining project and having a measure of its success.
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| Lecturer: |
Berendt, Bettina
Menasalvas, Ernestina
Spiliopoulou, Myra
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| Language: |
English |
| URL: |
http://www.wiwi.hu-berlin.de/~berendt/evaluation04/ |
| Matrial: |
evaluation_in_web_mining_tutorial_2004.pdf (2941 KB) |
| Date: |
2004
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| Address: |
ECML/PKDD2004
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