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Tech Report kmi-00-06 Abstract


Profiling your Customers using Bayesian Networks
Techreport ID: kmi-00-06
Date: 2000
Author(s): Paola Sebastiani, Marco Ramoni and Alexander Crea
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This report describes a complete Knowledge Discovery session using Bayesware Discoverer, a program for the induction of Bayesian networks from incomplete data. We build two causal models to help an American Charitable Organization understand the characteristics of respondents to direct mail fund raising campaigns. The first model is a Bayesian network induced from the database of 96,376 Lapsed donors to the June '97 renewal mailing. The network describes the dependency of the probability of response to the renewal mail on a subset of the variables in the database. The second model is a Bayesian network representing the dependency of the dollar amount of the gift on the variables in the same reduced database. This model is induced from the 5% of cases in the database corresponding to the respondents to the renewal campaign. The two models are used for both predicting the expected gift of a donor and understanding the characteristics of donors. These two uses can help the charitable organization to maximize the profit.

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Also in ACM SIGKDD Explorations, 1(2), 2000
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Future Internet is...


Future Internet
With over a billion users, today's Internet is arguably the most successful human artifact ever created. The Internet's physical infrastructure, software, and content now play an integral part of the lives of everyone on the planet, whether they interact with it directly or not. Now nearing its fifth decade, the Internet has shown remarkable resilience and flexibility in the face of ever increasing numbers of users, data volume, and changing usage patterns, but faces growing challenges in meetings the needs of our knowledge society. Globally, many major initiatives are underway to address the need for more scientific research, physical infrastructure investment, better education, and better utilisation of the Internet. Within Japan, USA and Europe major new initiatives have begun in the area.

To succeed the Future Internet will need to address a number of cross-cutting challenges including:

  • Scalability in the face of peer-to-peer traffic, decentralisation, and increased openness

  • Trust when government, medical, financial, personal data are increasingly trusted to the cloud, and middleware will increasingly use dynamic service selection

  • Interoperability of semantic data and metadata, and of services which will be dynamically orchestrated

  • Pervasive usability for users of mobile devices, different languages, cultures and physical abilities

  • Mobility for users who expect a seamless experience across spaces, devices, and velocities