K4: Data Mining Meets E-Business: Opportunities and Challenges

Umeshwar Dayal, Hewlett-Packard Laboratories

In the first wave of Internet-based e-commerce, data mining has been used primarily in a business-to-consumer (B2C) setting, e.g., for making product recommendations, or for personalized delivery of content. The next wave is widely expected to see the increasing automation of business functions and business-to-business (B2B) interactions. The richer e-business scenarios present numerous opportunities for applying data mining technologies. These range from making business processes such as customer relationship management and supply chain management smarter, to content management for portals and trading hubs. Business ecosystems are evolving into communities of e-services built on infrastructures such as IBM Websphere, HP e-Speak, and UDDI, which support the dynamic creation, registration, provisioning, and discovery of e-services. In the context of e-services, additional opportunities for data mining present themselves. First, data mining can be applied to the problems of intelligent discovery, brokering, and optimization of e-services. Second, one can postulate that data analysis and mining functions themselves will be offered as business intelligence e-services that accept operational data from clients, and return models or rules. In this talk, I will describe some data mining requirements and challenges for content management, e-service discovery, and business process intelligence that we have identified at Hewlett-Packard Laboratories, and some approaches that we are taking to address these requirements.

Presenter Bio

Umesh Dayal is Principal Laboratory Scientist for Information Management in the Software Technology Laboratory at Hewlett-Packard Laboratories, Palo Alto, California, where he currently leads research programs in data mining solutions and business process management. Umesh has over 20 years of research experience in data management. Prior to joining HP Labs., he was a senior researcher at DEC's Cambridge Research Lab., Chief Scientist at Xerox Advanced Information Technology and Computer Corporation of America, and on the faculty at the University of Texas-Austin. He obtained his Ph.D. in Applied Mathematics from Harvard University in 1979. Umesh has published extensively and holds several patents in the areas of database systems, transaction management, workflow systems, and data mining. He is on the Editorial Board of four international journals, has co-edited two books, and has chaired and served on the Program Committees of numerous conferences. Most recently, he served as Program Co-Chair of the International Conference on Cooperative Information Systems, September 1999; as Industry Track Program Chair of the International Conference on Very Large Data Bases, September 2000; and as Area Vice-Chair of the IEEE International Conference on Data Engineering, April 2001. He is a member of the Board of the VLDB Endowment, the Board of the International Foundation for Cooperative Information Systems, and the Steering Committee of the SIAM Data Mining Conference.