Bidirectional Growth based Mining and Cyclic Behaviour Analysis of Web Sequential Patterns

TL;DR

This paper introduces BGCAP, a novel bidirectional growth algorithm for mining web sequential patterns with cyclic behavior, improving prefetching rule efficiency and reducing latency in web browsing.

Contribution

The paper presents a new algorithm, BGCAP, that efficiently mines web sequential patterns with cyclic behavior using bidirectional growth, enhancing prefetching rule generation.

Findings

BGCAP is 5-10% faster than TD-Mine for different data sizes.

BGCAP generates 5-15% more prefetching rules than TD-Mine.

BGCAP reduces recursion levels to (log n+1), improving scalability.

Abstract

Web sequential patterns are important for analyzing and understanding users behaviour to improve the quality of service offered by the World Wide Web. Web Prefetching is one such technique that utilizes prefetching rules derived through Cyclic Model Analysis of the mined Web sequential patterns. The more accurate the prediction and more satisfying the results of prefetching if we use a highly efficient and scalable mining technique such as the Bidirectional Growth based Directed Acyclic Graph. In this paper, we propose a novel algorithm called Bidirectional Growth based mining Cyclic behavior Analysis of web sequential Patterns (BGCAP) that effectively combines these strategies to generate prefetching rules in the form of 2-sequence patterns with Periodicity and threshold of Cyclic Behaviour that can be utilized to effectively prefetch Web pages, thus reducing the users perceived latency. As BGCAP is based on Bidirectional pattern growth, it performs only (log n+1) levels of recursion for mining n Web sequential patterns. Our experimental results show that prefetching rules generated using BGCAP is 5-10 percent faster for different data sizes and 10-15% faster for a fixed data size than TD-Mine. In addition, BGCAP generates about 5-15 percent more prefetching rules than TD-Mine.