Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discover...Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discovery applications.In this paper we present the design of a mobile agent system which couples service discovery,using a logical language based application programming interface,and database access.Combining mobility with database access provides a means to create more efficient data mining applications.The processing of data is moved to network wide data locations instead of the traditional approach of bringing huge amount of data to the processing location.Our proposal aims at implementing system tools that will enable intelligent mobile Agents to roam the Internet searching for distributed data services.Agents access the data,discover patterns,extract useful information from facts recorded in the databases,then communicate local results back to the user.The user then generates a global data model through the aggregation of results provided by all Agents.This overcomes barriers posed by network congestion,poor security,and unreliability.展开更多
针对已有基于模式结构的模式匹配方法的局限性,提出了一种利用模式结构信息和已有匹配知识的模式匹配模——SKM(schema and reused knowledge based matching model).在该模型中,借鉴神经网络元之间的影响过程实现语义匹配推理;通过重...针对已有基于模式结构的模式匹配方法的局限性,提出了一种利用模式结构信息和已有匹配知识的模式匹配模——SKM(schema and reused knowledge based matching model).在该模型中,借鉴神经网络元之间的影响过程实现语义匹配推理;通过重用已有匹配知识深入挖掘模式元素之间的深层语义关系;基于已有匹配知识自动缩减不确定阈值区之间来确定匹配阈值,有效减少人工干涉;给出了简单的确定模式元素之间匹配关系的方法;同时通过自适应式迭代模型,进一步挖掘求精已有匹配知识.实验结果表明,SKM模型切实可行.展开更多
文摘Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discovery applications.In this paper we present the design of a mobile agent system which couples service discovery,using a logical language based application programming interface,and database access.Combining mobility with database access provides a means to create more efficient data mining applications.The processing of data is moved to network wide data locations instead of the traditional approach of bringing huge amount of data to the processing location.Our proposal aims at implementing system tools that will enable intelligent mobile Agents to roam the Internet searching for distributed data services.Agents access the data,discover patterns,extract useful information from facts recorded in the databases,then communicate local results back to the user.The user then generates a global data model through the aggregation of results provided by all Agents.This overcomes barriers posed by network congestion,poor security,and unreliability.
文摘针对已有基于模式结构的模式匹配方法的局限性,提出了一种利用模式结构信息和已有匹配知识的模式匹配模——SKM(schema and reused knowledge based matching model).在该模型中,借鉴神经网络元之间的影响过程实现语义匹配推理;通过重用已有匹配知识深入挖掘模式元素之间的深层语义关系;基于已有匹配知识自动缩减不确定阈值区之间来确定匹配阈值,有效减少人工干涉;给出了简单的确定模式元素之间匹配关系的方法;同时通过自适应式迭代模型,进一步挖掘求精已有匹配知识.实验结果表明,SKM模型切实可行.
