Web mining: information and pattern discovery on the World Wide Web

Abstract

Two important and active areas of current research are data mining and the World Wide Web. A natural combination of the two areas, sometimes referred to as Web mining, has been the focus of several recent research projects and papers. As with any emerging research area there is no established vocabulary, leading to confusion when comparing research efforts. Different terms for the same concept or different definitions being attached to the same word are commonplace. The term Web mining has been used in two distinct ways. The first, which is referred to as Web content mining in this paper, describes the process of information or resource discovery from millions of sources across the World Wide Web. The second, which we call Web usage mining, is the process of mining Web access logs or other user information user browsing and access patterns on one or more Web localities. In this paper we define Web mining and, in particular, present an overview of the various research issues, techniques, and development efforts in Web content mining and Web usage mining. We focus mainly on the problems and proposed techniques associated with Web usage mining as an emerging research area. We also present a general architecture for Web usage mining and briefly describe the WEBMINER, a system based on the proposed architecture. We conclude this paper by listing issues that need the attention of the research community.

Visualizing e-Government portal and its performance in WEBVS

“…In the context of Web usage mining, it is used to discover the correlations among references to various pages available on the server by a given client. Each transaction is comprised of a set of URLs accessed by a visitor [12]. Conventional Association Rule Mining (ARM) algorithms usually deal with datasets with categorical values and expect any numerical values to be converted to categorical ones using ranges.…”

Cut-and-Pick Transactions for Proxy Log Mining

“…Web logs are usually very large in size, and the analysis of these logs calls for more advanced methods such as data mining techniques. Recently, the application of data mining techniques to the Web logs, referred to as Web Log Mining, has draw extensively attention from researchers from various disciplines [CSM97]. From Web logs, one can identify user access patterns which can be used for various purposes such as Web site design [SPF99], page recommendation [PPR96,DH99], Web caching and prefetching [PM96,PM98,SKS98,PP99,YZL01].…”

An evolutionary algorithm to optimize web document retrieval

“…It is still the users' job to evaluate the quality of the information retrieved by the search engine in order to select the ones that are of greatest interest. The use of information filtering and data mining techniques in search engines is generically termed web mining [10].…”

“…In the last twenty years or so, research communities all over the world have been benefiting from the use of the Internet [10]- [13]. For instance, forty years ago it was very hard to share ideas with researchers in other continents and even researchers in the same country, but living in distant places.…”