Data Mining for Measuring and Improving the Success of Web Sites

Abstract

For many companies, competitiveness in e-commerce requires a successful presence on the web. Web sites are used to establish the company's image, to promote and sell goods and to provide customer support. The success of a web site affects and reflects directly the success of the company in the electronic market. In this study, we propose a methodology to improve the "success" of web sites, based on the exploitation of navigation pattern discovery. In particular, we present a theory, in which success is modelled on the basis of the navigation behaviour of the site's users. We then exploit WUM, a navigation pattern discovery miner, to study how the success of a site is reflected in the users' behaviour. With WUM we measure the success of a site's components and obtain concrete indications of how the site should be improved. We report on our first experiments with an online catalog, the success of which we have studied. Our mining analysis has shown very promising results, on the basis of which the site is currently undergoing concrete improvements.

Redesigning business processes: a methodology based on simulation and process mining techniques

“…containing information about the yield, (ii) the pages that can lead to fulfilling the site's goal, and (iii) the other pages. Using the notion of concept hierarchies, or service-based hierarchies [20], we determine action pages (a page whose invocation indicates that the user is pursuing the site's goal), and target pages (a page whose invocation indicates that the user has achieved the site's goal).…”

A fast method for discovering critical edge sequences in e-commerce catalogs

“…Web usage mining (e.g., [8,22,26,18,23]) is a sub-area within the area of sequence mining particularly applicable to the MPES-discovery problem. Much work on algorithms for web usage mining (e.g., [15,21,14,27,26,32]) is based on data mining [1,2,4,19] and sequential mining in particular [3,29]. Virtually all approaches in area take filtered web logs (i.e., full traversal data) as input, and output exact sequential patterns matching some criteria.…”

“…To perform the full-data analysis, we chose the Web Utilization Miner (WUM) tool [27] because it incorporates a query processor, allowing the specification of arbitrary patterns of interest (e.g., arbitrary start and end points) in the query language MINT [28], and is known to implement efficient algorithms and provide fast running times [27]. In Section 9, we use WUM as a benchmark, comparing its performance to that of our approach in terms of accuracy.…”

Query-Log Based Authority Analysis for Web Information Search

“…Extracting query sessions from server log files is known to be problematic because of difficulties of identifying the same user in a series of requests (see, e.g., [8,39,54,51,48]). The IP address cannot uniquely identify a user in the course of the massive usage of local caches, firewalls and proxy servers.…”