0 Review Ppt Handout

Web-based DataMining in E-Business P. Prasanna Kumar 200536314 ME SEOR Anna University Web-based DataMining in E-Business We Discuss What is E-Business? Scope of Data mining on E-Business Previous Research work on E-Business Proposed Research work on E-Business Web-based DataMining in E-Business What is E-Business? Electronic Business, or "e-Business", may be defined broadly as any business process that relies on an automated information system. Today, this is mostly done with Webbased technologies. The term "e-Business" was coined by Lou Gerstner, CEO of IBM. In practice, e-business is more than just e-commerce. E-commerce seeks to add revenue streams using the World Wide Web or the Internet to build and enhance relationships with clients and partners and to improve efficiency. Often, e-commerce involves the application of knowledge management systems. Web-based DataMining in E-Business E-business involves business processes spanning the entire value chain: electronic purchasing and supply chain management, processing orders electronically, handling customer service, and cooperating with business partners. Special technical standards for e-business facilitate the exchange of data between companies. E-business software solutions allow the integration of intra and inter firm business processes. E-business can be conducted using the Web, the Internet, intranets, extranets, or some combination of these. Web-based DataMining in E-Business Internal business systems: customer relationship management enterprise resource planning document management systems Human resources management Enterprise communication and collaboration: VoIP content management system e-mail Voice mail Web conferencing electronic commerce - business-to-business electronic commerce (B2B) or business-toconsumer electronic commerce (B2C): internet shop supply chain management online marketing Web-based DataMining in E-Business Scope of Data mining on E-Business Web mining - is the application of data mining techniques to discover patterns from the Web. According to analysis targets, web mining can be divided into three different types, which are Web usage mining, Web content mining and Web structure mining. Web Mining is used in E-Business to dig out potential modes and predict customers'

action, to help enterprises’ decision-makers adjust their marketing strategy, reduce the risk, make right decisions and get competitive advantage. Web-based DataMining in E-Business Previous Research work on E-Business Study and Application of Web-based Data Mining in E-Business Mining Online Users’ Access Records for Web Business Intelligence Model Driven Data Warehousing for Business Performance Management A Hybrid Approach for Dynamic Business Process Mining Based On Reconfigurable Nets and Event Types Extraction of Keyterms by Simple Text Mining for Business Information Retrieval Design and Implementation of Commerce Data Mining System Based on Rough Set Theory E-business enterprise data mining An Intelligent Framework (O-SS-E) for Data Mining, Knowledge Discovery and Business Intelligence Mining Web Transaction Patterns in Electronic Commerce Environment Service Pattern Discovery of Web Service Mining in Web Service Registry-Repository. Web-based DataMining in E-Business Proposed Research work on E-Business Based on above papers every one mined data based on query data, server data, online market data, hyperlinks, customer registration information. There is no input of user action behavior on clicks of particular WebPages, hyperlinks, banners and personalized customer requirements, URL statistics, frequent searching terms of customer. Web-based DataMining in E-Business Proposed Research work on E-Business Proposed Work Analysis in segments. Data Gathering The discovery of association rules. The discovery of sequential patterns. Classification and prediction. Cluster analysis. Anomaly detection. Web-based DataMining in E-Business Proposed Research work on E-Business Proposed Work Classification in segments. Feasibility Study Project Feasibility in real world environment. Analysis Analyzing the proposed and current research works. Design Detailed Analysis of core Modules Development Coding and development using Tools Testing with Simulation Testing with real time data and finding feasible outcome. Documentation Documenting and publishing journal paper. Thank You