ISSN: 2277-3754 ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 2, Issue 7, January 2013 169 Abstract— Web Usage Mining is application of data mining techniques to discover interesting usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Analyzing data through web usage mining can help effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. The aim of this paper is to emphasize on finding visitor group with common behavior from web log file of website. Web usage mining includes three phases namely preprocessing, pattern discovery and pattern analysis. Web Log file is considered as input here. This paper gives detailed description of how data from Web Log file are used for finding visitor’s having common behavior using DBSCAN clustering algorithm. Index Terms— Clustering, DBSCAN Clustering, Web Usage Mining. I. INTRODUCTION Web mining is the application of data mining techniques to extract knowledge from Web data, in which Web log data is used in the mining process. Researchers have identified three broad categories of Web mining. “Fig 1. Web Mining Classification” 1. Web Content Mining (Examines the content of web pages as well as results of web Searching) Web content mining is a process of picking up information from texts, images and other contents. The technologies that are normally used in web content mining are NLP (Natural language processing) and IR (Information retrieval). 2. Web Structure Mining (Exploiting Hyperlink Structure) Web structure mining is a process of picking up information from linkages of web pages. Web structure mining is the process of using graph theory to analyze the node and connection structure of a web site. This graph structure can provide information about ranking or authoritativeness and enhance search results of a page through filtering. 3. Web Usage Mining (analyzing user web navigation) Web usage mining is a process of picking up information from user how to use web sites. Web usage mining also known as web log mining, aims to discover interesting and frequent user access patterns from web browsing data that are stored in web server logs, proxy server logs or browser logs. Thus, Web usage mining is the application of data mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Application of Web Usage Mining:  Personalization: Restructure website based on user’s profile and usage behavior.  System Improvement: Provide key to understanding web traffic behavior. Advanced load balancing, data distribution or policies for web caching are benefits of such improvements.  Modification of Website: Understanding visitors’ behavior in a web site provides hints for adequate design and update decision.  Business intelligence covers the application of intelligent techniques in order to improve certain businesses, mainly in marketing.  Characterization of use: is based e.g. on models that determine the pages a visitor might visit on a given site. II. WEB USAGE MINING PROCESS Web Usage Mining Process is divided into three phases: Pre-Processing, Pattern Discovery & Pattern Analysis as shown in figure 2. Raw Web Log File collected from server is considered here as input. “Fig 2. Web Usage Mining Process with phases” Web Usage Mining to Discover Visitor Group with Common Behavior Using DBSCAN Clustering Algorithm Shaily G. Langhnoja, Mehul P. Barot, Darshak B. Mehta