About AlphaMiner
Current Release
Previous Release
News & Updates
Service Partner
About Us

AlphaMiner is developed by the E-Business Technology Institute (ETI) of the University of Hong Kong under the support from the Innovation and Technology Fund (ITF) of the Government of the Hong Kong Special Administrative Region (HKSAR). It is an open source data mining platform that provides the best cost-and-performance ratio for data mining applications.

Affordable Business Intelligence

The technology of Business Intelligence (BI) is an important means for companies to improve business decision making. Over the past decade, international companies in the banking, telecommunications, insurances, retails and e-business sectors have successfully used BI to solve numerous business problems in marketing, customer service, cross selling, customer retention, fraud detection and risk management.

BI solutions are costly and only large enterprises can afford them. But small companies are no longer at a disadvantage. AlphaMiner data mining system provides affordable BI technologies by leveraging existing open source technologies which empowers companies with the capability to make better decisions in the fast changing business environment.

AlphaMiner Technologies

  • Workflow style case construction enables general business managers in construction of a data mining case by simple drag-and-drop operations.
  • Plug-able component architecture provides extensibility for adding new BI capabilities in data import and export, data transformations, modeling algorithms, model assessment and deployment. Data mining capabilities from Xelopes and Weka have been incorporated in the first release.
  • Versatile data mining functions offer powerful analytics to conduct industry specific analysis including customer profiling and clustering, product association analysis, classification and prediction.

Related Links

:: J2SDK

:: Eclipse
:: Weka
:: Xelopes

Copy (c) 2005 E-Business Technology Institute, The University of Hong Kong. All rights reserved.
Best View: 1024 x 768
Last modified at 24/08/2005