Eduardo S. Vera

Using Self Organizing Feature Maps to Acquire Knowledge about Visitor Behavior in a Web Site

When a user visits a web site, important information concerning his/her preferences and behavior is stored implicitly in the associated log files. This information can be revealed by using data mining techniques and can be used in order to improve both, content and structure of the respective web site.

Using SOFM to improve web site text content

We introduce a new method to improve web site text content by identifying the most relevant free text in the web pages. In order to understand the variations in web page text, we collect pages during a period. The page text content is then transformed into a feature vector and is used as input of a clustering algorithm (SOFM), which groups the vectors by common text content. In each cluster, a centroid and its neighbor vectors are extracted. Then using a reverse clustering analysis, the pages represented by each vector are reviewed in order to find the similar. Furthermore, the proposed method was tested in a real web site, proving the effectiveness of this approach.

Intelligent Web Site: Understanding the Visitor Behavior

Intelligent web site is a new portal generation, able to improve its structure and content based on the analysis of the user behavior. This paper focuses on modeling the visitor behavior, assuming that the only source available is his/her browsing behavior. A framework to acquire and maintain knowledge extracted from web data is introduced. This framework allows to give online recommendations about the navigation steps, as well as offline recommendations for changing the structure and contents of the web site. The proposed methodology is applied to the web site of a commercial bank.

Establishing Guidelines on How to Improve the Web Site Content Based on the Identification of Representative Pages

The Internet has become a big battlefield where organizations are trying to keep their present clients and to gain new ones. Two important weapons that the organizations have are to make a good Web site design and to have a content interesting for the visitors. To improve the Web site content, many tools have been developed. However, it is hard to figure out how to apply these changes. Furthermore, in complex Web sites, this is a non trivial task. We propose a novel approach that helps to improve a Web site content using a SOFM and performing a reverse clustering analysis that allows us to gather the most representative Web pages from a Web site, using this small set of pages as a guideline of how these enhancements should be performed. The effectiveness of the method was tested in a real Web site.

Improving the Web text content by extracting significant pages into a Web site

Web systems have reached a very important role in todays business world. Every day organizations fight to keep their present clients and to gain new ones. In order to accomplish this goal it is very important to make precise changes in the Web site content. However, the development of these improvements is a complex and specialized task because of the nature of the Web data itself. We propose a novel approach to successfully make changes to improve the Web site content using text mining. We use a self organizing feature map (SOFM) to find the most relevant text content, and then we propose a reverse clustering analysis in order to extract the most significant pages of the whole Web site. The effectiveness of this method was experimentally tested in a real Web site.

AccessNova: Broadband networks and multimedia services experiments in Chile

We describe the technology platform of AccessNova, an advanced communications project to develop high speed networks and to promote the early use of broadband applications in Chile, as the initial step in the implementation of this research and development program. In its first stage (1995–1996), this project has been a joint effort of the University of Chile and the Nippon Telegraph and Telephone Corporation (NTT). In its second stage (1997–1999), AccessNova will be expanded to include other national and international organizations as well.