A Review on Mining for Web EngineeringBusiness Intelligence

Abstract

Over the last few years, there has been a remarkable increase in use of World Wide Web for a wide and variety of applications. The web plays a central role in e-commerce applications. As a consequence, there is a need to improve Intelligence of Web Engineering Applications in the context of Business and IT industry. To achieve this objective web engineering tasks must be able to identify some useful insights for business intelligence. The proposed research work attempts to initiate Business Intelligence from Web Based Applications. The issues of research work are uniformly accommodated in five steps. The First step identification of fundamental tasks of Web Engineering, Mining for Software Engineering and its extension to Mining for Web Engineering, Web Mining and Web Based Business Intelligence Applications will be done.. The Second step recent Literature Review will be carried out. The Third Step case studies on present’s business intelligence need of next generation business applications, development of Next Generation Business Intelligence Application Development Technologies (NGBIADT). The NGBIADT covers Web 2.0, Agile Modeling and Web Services. The Fourth step the idea of Mining approaches for Web Engineering and NGBIADT. The Mining approach of Web Engineering consists of 3 phases. In Phase 1, Web Engineering data such as web design, structure of Web, web logs and error reports are collected using a comprehensive algorithm. Phase 2 integrates a various Web Engineering data from phase 1 to develop web mining approach using association rules, classification and clustering techniques. In Phase 3, information generated from web mining approach can be considered as base for developing a web based application that satisfies the need of end user requirements and also satisfying needs of business industry. Thus, phase 3 produces tasks related to web application structure, web services, web architectures, web configuration management data, web classification, web communities, website Navigation and web security. These tasks are very much essential in developing NGBIADT applications. The mining approach of NGBIADT consists of technologies such as Web 2.0 for business intelligence, Agile modeling for business intelligence and Web Services for business intelligence with suitable exemplars. The Fifth Step demonstrates various insights to improve Web Engineering applications for the purpose of Business Intelligence using Secure Stock Market (SSM) web application as an example. Applying Mining strategies to Web Services will provide valuable insights in terms of Service discovery, Service dependency, Service composition etc. Hence this proposed research work investigates the following various areas of research like: The study on Web engineering tasks. Mining techniques related to web engineering Obtain and analyze Mining information in business intelligence Some insights that improve intelligence of web based application.