الفهرس | Only 14 pages are availabe for public view |
Abstract The World Wide Web (WWW) has grown quickly in the past two decades from a small research community to the biggest and most popular infrastructure for communication, information dissemination, search, social interaction and commerce. Today, Web is considering the magical gate for the success of any online business. Unfortunately, the continuous growth in size and use of the WWW makes struggles in benefiting from the valuable available massive of web data. A need for methods to process these wicked volumes of web data becomes necessarily. Web Intelligence (WI), as a research direction, has a broad agenda to deal with the issues that arise around the WWW phenomenon. WI is concerning of mining in web data and user behaviors to explore the valuable hidden knowledge. This creates a demand for using mining technologies to search large volume of data for extracting the hidden knowledge. The discovered knowledge helps greatly in gaining competitive advantages and better customers’ relationships in the wild world of online business. Hence, achieving the intelligence to the web enhances Business Intelligence (BI) for any enterprise. The study proposes an approach to achieve the intelligence to the web and improving the BI level. The proposed approach consists of two main sub approaches which are approach A and approach B. approach A proposes a framework combines the gained knowledge from Web Usage Mining ( WUM )and Opinion Mining( OP). Approach B is about Studying, examining and analyzing the mutual effect between WUM and OP knowledge. Both of the two sub approaches are contributing in achieving intelligence to the web and improving the BI performance. The proposed approach has proven its validity and Effectiveness. The results are promising and help in better BI decisions. |