Download Agents and Data Mining Interaction: 6th International by Sandip Sen (auth.), Longbing Cao, Ana L. C. Bazzan, Vladimir PDF

By Sandip Sen (auth.), Longbing Cao, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, Philip S. Yu (eds.)

ISBN-10: 3642154190

ISBN-13: 9783642154195

This e-book constitutes the refereed lawsuits of the sixth overseas Workshop on brokers and knowledge Mining interplay, ADMI 2010, held in Toronto, Canada, in could 2010. The 15 revised complete papers offered have been conscientiously reviewed and chosen from 37 submissions. The papers are geared up in topical sections on brokers for information mining; info mining for brokers; info mining in brokers; and agent mining purposes.

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Extra resources for Agents and Data Mining Interaction: 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers

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G. the partial query steps have to be processed. g. execution of a SQL statement, is done by the system. To precisely answer a query, an aggregation of certain query results (step 6) based on user specific knowledge, is often required. Therefore, system experts have to interpret the query results and expand or reduce the search space if needed. If search results are ambiguous, 30 S. Pech and P. Goehner step 3 to step 6 can be repeated. In sense of the query, every single data represents a valid search result.

2. Elementary query sequence The procedure of information gathering consists of several steps. g. in the form of an SQL query. Steps 3 and 4, as well as step 6 are carried out manually by the user, whereas step 5 is executed by the system. To solve a query, the identification of the relevant data sources, depends on user knowledge. g. the partial query steps have to be processed. g. execution of a SQL statement, is done by the system. To precisely answer a query, an aggregation of certain query results (step 6) based on user specific knowledge, is often required.

As the environment changes, the capability of recognizing a new norm helps an agent to derive new ways of achieving its intended goals. Such a norm identification mechanism can be useful for software agents that need to adapt to a changing environment. In open agent systems, instead of possessing predetermined notions of what the norms are, agents can infer and identify norms through observing patterns of interactions and their consequences. For example, a new agent joining a virtual environment such as Second Life [5] may have to infer norms when joining a society as each society may have different norms.

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