Authors: Priyanka Verma; Nishtha Kesswani
Addresses: The IIS University, Jaipur, Rajasthan, India ' Central University of Rajasthan, Bandar Sindri, Rajasthan, India
Abstract: Web logs are files created to store data about users and all accesses made to web pages by various users. It stores various details such as user id and URL accessed. Web usage mining uses these log files to discover user patterns. Web personalisation is personalisation of websites according to user interests. Data collection from log files is the first step to perform personalisation. There are various types of personalisation such as memorisation, guidance, customisation and task performance support. There are various stages of web usage mining amongst them pre-processing is the most important and time consuming stage. It involves removing irrelevant data through data cleaning. It includes identification of users and sessions which is most important for personalisation. In this paper, we would be focusing on memorisation. Memorisation is remembering pages accessed by various users and then personalising pages. User identification is primary step of memorisation. In this paper, we would be identifying users from web logs by creating framework using VB.Net and SQL server. This framework can then be used for memorisation. After user identification, output can then be further used to identify sessions.
Keywords: mining; logs; personalisation; memorisation.
International Journal of Services Technology and Management, 2017 Vol.23 No.4, pp.290 - 298
Received: 22 Jan 2016
Accepted: 15 Apr 2016
Published online: 21 Nov 2017 *