Indexing Techniques for Web Access Logs

Abstract

Access histories of users visiting a web server are automatically recorded in web access logs.Conceptually, the web-log data can be regarded as a collection of clients' access-sequences where each sequence is a list of pages accessed by a single user in a single session. This chapter presents novel indexing techniques that support efficient processing of so-called pattern queries, which consist in finding all access sequence s that contain a given subsequence. Pattern queries are a key element of advanced analyses of web-log data, especially those concerning typical navigation schemes. In this chapter, we discuss the particularities of efficiently processing user access-sequences with pattern queries, compared to the case of searching unordered sets. Extensive experimental results are given, which examine a variety of factors and illustrate the superiority of the proposed methods over indexing techniques for unordered data adapted to access sequences.

A Plausible Comprehensive Web Intelligent System for Investigation of Web User Behaviour Adaptable to Incremental Mining

“…The website designer can use this information to improve the website design. Most of the researches focused on Full Scan algorithm and Selective Scan algorithm [9] etc. However, these algorithms have the limitations that they can only discover the simple path traversal pattern, i.e., a page cannot repeat in the pattern.…”