Real Time Generalized Log File Management and Analysis using Pattern Matching and Dynamic Clustering

Abstract

The past decade saw an exponential rise in the amount of information available on the World Wide Web. Almost every business organization today uses web based technology to wield its huge client base. Consequently, managing the large data and mining pertinent content has become the need of the hour. This is where the field of big data analytics sows its seeds. The linchpin for this is the process of knowledge discovery. Analyzing server logs and other data footprints, aggregated from clients, can facilitate the building of a concrete knowledge base. Querying the knowledge base can help supplement business and other managerial decisions. The approach herein proposes a real time, generalized alternative to log file management and analysis. It incorporates the development of a sustainable platform which would enable the analysts to understand the essence of the data available.