An Improved Web Page Recommendation Technique for Better Surfing Experience

An Improved Web Page Recommendation Technique for Better Surfing Experience

Rajnikant Bhagwan Wagh (Department of Computer Engineering, R. C. Patel Institute of Technology, Shirpur, India) and Jayantrao Bhaurao Patil (Department of Computer Engineering, R. C. Patel Institute of Technology, Shirpur, India)
Copyright: © 2018 |Pages: 13
DOI: 10.4018/IJKBO.2018100101

Abstract

Recommendation systems are growing very rapidly. While surfing, users frequently miss the goal of their search and lost in information overload problem. To overcome this information overload problem, the authors have proposed a novel web page recommendation system to save surfing time of user. The users are analyzed when they surf through a particular web site. Authors have used relationship matrix and frequency matrix for effectively finding the connectivity among the web pages of similar users. These webpages are divided into various clusters using enhanced graph based partitioning concept. Authors classify active users more accurately to found clusters. Threshold values are used in both clustering and classification stages for more appropriate results. Experimental results show that authors get around 61% accuracy, 37% coverage and 46% F1 measure. It helps in improved surfing experience of users.
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2. Elements And Steps Of Web Personalization

Web Personalization is a technique that learns preferences, habits and patterns of users. It is primarily used in applications which support E-Business. It aims at achieving two objectives from E-business point of view, first to improve the usability of website and another to retain the users of website.

2.1. Elements

The key elements of it include categorization and preprocessing of Web data, extraction of relationship between these data and finding the actions to be done by the system. Web data can be one of the following (Eirinaki & Vazirgiannis, 2003):

  • User Profile Data: It Provides information about users of a Web site. It contains name, age, sex, country, state, marital status, education, interest, etc. for each user of a Web site. It also contains information about user’s preferences and interests. Such information is collected through questionnaires or registration forms or can be generated by analysis of Web server logs;

  • Content Data: It can be simple text, images or structured data such as information retrieved from databases. The content data is presented to the end user;

  • Structure Data: It refers to the way content is organized. They can be XML or HTML tags (data entities used within a Web page) or it can also be a hyperlink connecting one page to another (data entities to put a Web site together). It is an existence of links between various pages to restrict navigation performed by the user to predefined paths;

  • Usage Data: It represents a Web site’s usage. It includes parameters like visitor’s IP address, date and time of access, complete path (directories or files) accessed, and referrer’s.

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