Webview selection from user access patterns

Abstract

The number of Web Usage Mining (WUM) applications is growing continuously, especially due to the business interest in e-commerce Web sites and the related Web-marketing applications. The application of WUM results goes beyond the subject of our thesis since one important part of our thesis deals with the problem of selection of webviews using technics of WUM techniques. View materialization is an important issue if we want to improve the efficiency of many applications like OLAP, Database and Web applications. In this paper, we propose a novel approach for selecting webviews to be materialized in order to optimize the response time of web queries. The selection of webviews to be materialized was mainly based on the estimation of metrics requiring hard collects of multiple statistics [9] that's why, we believe on a solution based on mining an interesting set of webviews to be materialized from realistic data : Web log files. Thus, Web log files will be parsed, analyzed and treated to give a set of webviews, based on frequent closed itemsets.

Cost Model for the Recommendation of Materialized Webviews

“…It consists of maximizing the QoS under the constraint to respect a degree of QoD which is specified by θ. The techniques of data mining have recently been used to the selection of materialized data either on data warehouse [4,5,6,22] or on the web [10,11,23]. In [23], S. Saidi et al have proposed an approach that firstly analyzes the historic of user navigation and then selects the set of materialized webview which improve the query response time and respect maintenance and storage constraints.…”

Web usage mining for the recommendation of materialized webviews

“…The first attempt, to select materialized webviews, based on web usage mining technique and taking into account users' behaviors was proposed in [11]. It consists of two steps: (i) the extraction, from log files and by using association rules, of closed frequent sets of candidate webviews, (ii) the application of maintenance and storage constraints to select, from the list of candidate webviews founded in the previous step, the appropriate ones to materialize.…”

Multi-constraint selection of materialized webviews

“…In this case, the algorithm will dematerialize some webviews. In [10], the authors have proposed an algorithm to select the materialized webviews under two constraints: maintenance cost and webview size. They have applied an algorithm of web usage mining to identify the frequent sets of webviews.…”

“…The selection of materialized webviews, is mainly treated by Labrinidis and Roussopoulos [6,7,8,9]. Then, others webview selection approaches are proposed in [2,10]. In this paper we will be interested on the constraints which are applied to select the appropriate materialized webviews.…”

“…These two constraints are widely used in the database and data warehouse environments. They are applied both in [10]. However in [6], the authors have combined these two constraints in one constraint which represents the number of webviews that can be materialized.…”