الفهرس 
صفحة العنوانOnly 14 pages are availabe for public view
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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.