Web Mining Research: A Survey

TL;DR

This survey reviews Web mining research, clarifies terminology, categorizes Web mining approaches, and discusses their connections to agent paradigms, highlighting key issues and future directions.

Contribution

It introduces a clear categorization of Web mining, clarifies terminology, and relates Web mining to agent paradigms, providing a comprehensive overview of recent research.

Findings

Proposes three categories of Web mining.

Connects Web mining with agent paradigms.

Identifies key research issues and challenges.

Abstract

With the huge amount of information available online, the World Wide Web is a fertile area for data mining research. The Web mining research is at the cross road of research from several research communities, such as database, information retrieval, and within AI, especially the sub-areas of machine learning and natural language processing. However, there is a lot of confusions when comparing research efforts from different point of views. In this paper, we survey the research in the area of Web mining, point out some confusions regarded the usage of the term Web mining and suggest three Web mining categories. Then we situate some of the research with respect to these three categories. We also explore the connection between the Web mining categories and the related agent paradigm. For the survey, we focus on representation issues, on the process, on the learning algorithm, and on the application of the recent works as the criteria. We conclude the paper with some research issues.