EMADS: An extendible multi-agent data miner
نویسندگان
چکیده
In this paper we describe EMADS, an Extendible Multi-Agent Data mining System. The EMADS vision is that of a community of data mining agents, contributed by many individuals, interacting under decentralised control to address data mining requests. EMADS is seen both as an end user application and a research tool. This paper details the EMADS vision, the associated conceptual framework and the current implementation. Although EMADS may be applied to many data mining tasks; the study described here, for the sake of brevity, concentrates on agent based data classification. A full description of EMADS is presented.
منابع مشابه
The EMADS Extendible Multi-Agent Data Mining Framework
In this chapter we describe EMADS, an Extendible Multi-Agent Data mining System. The EMADS vision is that of a community of data mining agents, contributed by many individuals and interacting under decentralized control, to address data mining requests. EMADS is seen both as an end user platform and a research tool. This chapter details the EMADS vision, the associated conceptual framework and ...
متن کاملA Generic and Extendible Multi-Agent Data Mining Framework
A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that it avoids the use of agreed meta-language formats by supporting a system of wrappers. The advantage offered is that the system is easily extendible, so that further data agents and mining agents can simply be added to...
متن کاملAgent Based Frequent Set Meta Mining: Introducing EMADS
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of such agents and demonstrate (by experiment) their application to data mining on distributed data. Although, EMADS is not restricted to one data mining task, the study described here, for the sake of brevity, concentra...
متن کاملAn investigation into the issues of multi-agent data mining
Very often data relevant to one search is not located at a single site, it may be widely-distributed and in many different forms. Similarly there may be a number of algorithms that may be applied to a single Knowledge Discovery in Databases (KDD) task with no obvious “best” algorithm. There is a clear advantage to be gained from a software organisation that can locate, evaluate, consolidate and...
متن کاملAgent-Enriched Data Mining Using an Extendable Framework
An extendable and generic Agent Enriched Data Mining (AEDM) framework, EMADS (the Extendable Multi-Agent Data mining System) is described. The central feature of the framework is that it avoids the use of ontologies or agreed meta-language formats by supporting a system of wrappers. The advantage offered is that the system is easily extendable, further data agents and mining agents can simply b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Knowl.-Based Syst.
دوره 22 شماره
صفحات -
تاریخ انتشار 2009