Application of Decisional DNA in Web Data Mining

نویسندگان

  • Peng Wang
  • Cesar Sanín
  • Edward Szczerbicki
چکیده

Web data mining techniques are becoming popular and valuable components of web data analysis systems. It assists website’s owners to estimate their website’s performance and make explicit and precise business strategies. The main features of Decisional DNA are related to knowledge representation structures. They are dealing with noisy and incomplete data, learning from experience, making precise decision, and predicting. This paper presents a proposal for development of web data mining techniques with Decisional DNA at its core. Integrating Decisional DNA with web data mining techniques involves retrieval, clustering, storage, sharing, and transporting of knowledge and day-to-day explicit experience in a new structure. A set of experiments is also included in this paper to illustrate usage of Decisional DNA applied to decisional domain in web data mining as well as re-usage of such knowledge to facilitate decision making process.

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تاریخ انتشار 2011