Scalable E-business social network using multiCrawler agent

Abstract

Social networking is a big buzz phrase nowadays. It refers to the practice of interacting with others online via blogs, forums, social media sites and other outlets. The importance of social networking is to let others know that we are exists. Social network can show how people in our extended network are related to each other. In this paper, we are focusing on e-business network since e-business is sprouting on the Internet these days like wild mushrooms. Moreover, with the rapid growth of the e-business in the Web, searching the popular web page of e-business and its relationship with others web page becomes an interesting and important issue for the user especially for the firms. Currently, we realized which of the e-business having the highest popularity via the newspaper, magazines and Internet. However, the e-business having a lack of information - the quality of the connection. In order to collect the e-business web sites from the Internet, crawler agent is used. The crawler will obtain information in the links and keeps the information in the repository for later processing. Here, we proposed the MultiCrawler agent to develop a scalable e-business social network. The genetic algorithm is used to optimize the e-business web pages fetched by the crawler based on the user profiles. The result is the visualization of e-business social network mapping that related to the Multimedia Super Corridor (MSC) companies in Malaysia.