Service-Oriented Data Mining

• 2006-07-07: Anteater: A Service-Oriented Architecture for High-Performance Data Mining
  Data mining focuses on extracting useful information from large volumes of data, and thus has been the center of much attention in recent years. Building scalable, extensible,and easy-to-use data mining systems,however,has proved to be difficult. In response, the authors developed Anteater, a service-oriented architecture for data mining that relies on Web services to achieve extensibility and interoperability, offers simple abstractions for users, and supports computationally intensive processing on large amounts of data through massive parallelism.
• 2006-07-07: Service-Oriented Distributed Data Mining
  Data mining research currently faces two great challenges: how to embrace data mining services with just-in-time and autonomous properties and how to mine distributed and privacy-protected data. To address these problems, the authors adopt the Business Process Execution Language for Web Services in a service oriented distributed data mining (DDM) platform to choreograph DDM component services and fulfill global data mining requirements. They also use the learning-from-abstraction methodology to achieve privacy-preserving DDM. Finally,they illustrate how localized autonomy on privacy-policy enforcement plusa bidding process can help the service-oriented system self-organize.

in IEEE Internet Computing July/August 2006, special focus on Distributed Data Mining

via Digital Library related RSS news feeds