Efficient and Anonymous Web-Usage Mining for Web Personalization

Abstract

The world-wide web (WWW) is the largest distributed information space and has grown to encompass diverse information resources. Although the web is growing exponentially, the individual's capacity to read and digest content is essentially fixed. The full economic potential of the web will not be realized unless enabling technologies are provided to facilitate access to web resources. Currently web personalization is the most promising approach to remedy this problem, and web mining, particularly web-usage mining, is considered a crucial component of any efficacious web-personalization system. In this paper, we describe a complete framework for web-usage mining to satisfy the challenging requirements of webpersonalization applications. For on-line and anonymous web personalization to be effective, web usage mining must be accomplished in real time as accurately as possible. On the other hand, web-usage mining should allow a compromise between scalability and accuracy to be applicable to real-life websites with numerous visitors. Within our web-usage-mining framework, we introduce a distributed user-tracking approach for accurate, scalable, and implicit collection of the usage data. We also propose a new model, the feature-matrices (FM) model, to discover and interpret users' access patterns. With FM, various spatial and temporal features of usage data can be captured with flexible precision so that we can trade off accuracy for scalability based on the specific application requirements. Moreover, tunable complexity of the FM model allows real-time and adaptive access pattern discovery from usage data. We define a novel similarity measure based on FM that is specifically designed for accurate classification of partial navigation patterns in real time. Our extensive experiments with both synthetic and real data verify correctness and efficacy of our webusage-mining framework for anonymous and efficient web personalization.

A New Web Usage Mining Approach for Website Recommendations Using Concept Hierarchy and Website Graph

“…A session is a sequence of requests made by a single user with a unique IP address on a particular web domain during a specified period of time. Several methods to identify sessions are discussed in [13]- [15]. We are combining two trivial approaches (time & navigation oriented) with our concept name match approach.…”

GEOSO - A Geo-Social Model: From Real-World Co-occurrences to Social Connections

“…That is, all zeros are eliminated from the vector. Subsequently, we can improve the computation efficiency by employing the Projected Pure Euclidean Distance (PPED) proposed in [2].…”

“…Consequently, we can apply distance metrics, such as the cosine similarity [2] to calculate the distance between two patterns represented by vectors. However, we show in Section 2.2 that there are two major drawbacks with this approach.…”

Characteristics of B2B adoption and planning of online marketing communications

“…More advanced methods use automated web usage mining systems that deliver personalised content and services. [59][60] • SMS was not intended either for heavy personal communications or for mobile marketing, even though the adoption has been explosive. SMS has already proven its effectiveness in online marcom, both as an individual element and integrated with television.…”