Knowledge Extraction Through Page Rank Using Web-Mining Techniques for E-Business: A Review

Knowledge Extraction Through Page Rank Using Web-Mining Techniques for E-Business: A Review

Mahesh Kumar Singh (University of Kota, India), Om Prakash Rishi (University of Kota, India), Anukrati Sharma (University of Kota, India), and Zaved Akhtar (Vishveshwarya Institute of Engineering and Technology, India)
DOI: 10.4018/978-1-5225-2234-8.ch001
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Internet plays a vital role for doing the business. It provides platform for creating huge number of customers for ease of business. E-business organizations are growing rapidly and doubly in every minute; World Wide Web (WWW) provides huge information for the Internet users. The accesses of user's behavior are recorded in web logs. This information seems to be very helpful in an E-business environment for analysis and decision making. Mining of web data come across many new challenges with enlarged amount of information on data stored in web logs. The search engines play key role for retrieving the relevant information from huge information. Nowadays, the well-known search engines, like Google, MSN, Yahoo, etc. have provided the users with good search results worked on special search strategies. In web search services the web page ranker component plays the main factor of the Google. This paper discusses the new challenges faced by web mining techniques, ranking of web pages using page ranking algorithms and its application in E-business analysis to improve the business operations.
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1. Introduction

Today the Internet has changed the rules for doing businesses; this revolution towards E-business has changed the conventional way of doing businesses. This technique also faces some new challenges both for companies as well as customers. Customer confuse with multiple choice of specific product which results lost state. The big issue in front of the companies is to sustain their performance output in this competitive business environment. A promising solution to overcome this issue is recommended system which provides and guides the customer with the types of product he or she is buying or purchasing. If it is to be consider that each product or service have different page then page rank provide the rating of the similar product of different companies by using the ranking the page it can be calculated the popularity of the product or service.

Modern telecommunication technologies connect people distributed at different places in the world and ease the delivery of information. Therefore, users are enabled to share the knowledge with other people by available communication methods. However, it becomes very inefficient for a web surfer to navigate the sequence of web pages one by one due to the large amount of the unstructured web. Thus, search engines have been adopted as a solution to overcome from such problems over the past few years. Behind the search engine, web mining plays a key role since it can accelerate the exchange of knowledge hidden in volatile collections of data on the Internet.

1.1. Motivation

Nowadays the Internet has been well known as a big data repository consisting of different data types as well as a large amount of hidden informative knowledge, which can be discovered via a wide range of data mining techniques. All these kinds of techniques are based on intelligent computing approaches, or so-called computational intelligence, which is widely used in the research of web database, web data mining and information retrieval and so on. Although the progress of the web-based database management system research results in developments of different useful web applications or services, like Web search engines, users are still facing the problems of information overload and complexity due to the significant and rapid growth in the amount of information and the number of users. The web users usually experience from the difficulties of finding desirable and accurate information on the web due to low precision and low recall caused by the above reasons. For example, if a user wants to search the desired information by utilizing a web search engine such as Google, the search engine may provide to the user not only the information related to the query topic, but also a large amount of irrelevant /noisy information. The emerging of Internet has given research issues and challenges to web researchers for web-based information retrieval and information management. Web research academia is required to develop effective and efficient techniques to fulfill the increasing demands of web users, creating good quality Web communities (Zhang, Y., 2006, and Kleinberg, J. 1998), extracting the informative knowledge from the available information (Craven, M., 1998, pp 509-516), capturing the underlying usage pattern from the Web observation data (Srivastava, J., et al. 2000, pp 12-23), recommending user customized information to offer better Internet service (Mobasher, B., et al., 2002, pp 61-82), and in addition mining valuable business information from the common or individual customer navigational behaviour as well (Ghani, R. & Fano, A,. 2002,pp 11-19).

Every relevant information is collected around the mining results which now represent actionable knowledge. These data are arranged according to different aspects, where each aspect represents a particular aspect of the objects represented in the web mining results. By using these information business analyst interprets the mining results and make informed business decisions.


2. World Wide Web (Www)

Terminology related to WWW as shown in figure 1.

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