Interoperable Web-based data mining system by Java distributed object computing

Sheng Tun Li, Tan Sheng Li

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


The development of Web-based data mining systems has received a lot of attention in recent years. It plays the key-enabling role for competitive businesses in E-commerceera. A cost-effective and prompt approach for this task is to integrate and coordinate existing data mining applications in a seamless manner. In this paper, we propose a new methodology for developing a Web-based data mining system. This system relies on the Java distributed object computing to tackle the issues of interoperability in heterogeneous environments, namely, language, platform, visual object model, and data access. The effectiveness of the proposed system is demonstrated by integrating two powerful data mining tools, SOM_PAK and Nenet, and the experiment on the iris data. The methodology can facilitate the collaboration of intelligent components seamlessly in a "plug-N-work" manner but without re-engineering.

Original languageEnglish
Article number128
Number of pages1
JournalProceedings of the Hawaii International Conference on System Sciences
Publication statusPublished - 2001 Jan 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)


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