P2P中基于模式和本体变化的协议维护 环境

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摘要翻译：
本文研究了一种基于语义距离的语义一致性维护方法，该方法通过计算局部模式或本体的变化来实现语义一致性维护。这种方法在动态自治环境中非常重要，而现有的方法都是在静态环境中假设协议或映射。本研究的贡献在于开发了一个基于P2P环境下语义协议维护方法的框架。该框架基于两级混合P2P模型体系结构，由两种对等体类型组成：（1）超级对等体，用于注册和管理其他对等体；（2）简单对等体，作为简单对等体，导出并与其他对等体共享其内容。本文提出了一种P2P环境下语义一致性的维护模型，由于现有的方法假设本体和局部模式是静态的，而在动态的情况下是不同的，因此没有了解变化的机制。主要问题是如何计算局部模式或公共本体的变化，并根据计算结果确定哪种算法来维护协议。在印度尼西亚的工作匹配领域进行了实验，以表明该方法的性能有多大。从实验结果来看，主要结果是:①变化越大，F测度值有减小的趋势；②不同的修改类型（添加、删除、重命名），F测度值没有显著性差异；③正确选择算法可以提高F测度值。
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英文标题：
《Agreement Maintenance Based on Schema and Ontology Change in P2P
  Environment》
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作者：
L.Y. Banowosari, I.W.S. Wicaksana, and A.B. Mutiara
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最新提交年份：
2010
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Databases        数据库
分类描述：Covers database management, datamining, and data processing. Roughly includes material in ACM Subject Classes E.2, E.5, H.0, H.2, and J.1.
涵盖数据库管理、数据挖掘和数据处理。大致包括ACM学科类E.2、E.5、H.0、H.2和J.1中的材料。
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英文摘要：
  This paper is concern about developing a semantic agreement maintenance method based on semantic distance by calculating the change of local schema or ontology. This approach is important in dynamic and autonomous environment, in which the current approach assumed that agreement or mapping in static environment. The contribution of this research is to develop a framework based on semantic agreement maintenance approach for P2P environment. This framework based on two level hybrid P2P model architecture, which consist of two peer type: (1) super peer that use to register and manage the other peers, and (2) simple peer, as a simple peer, it exports and shares its contents with others. This research develop a model to maintain the semantic agreement in P2P environment, so the current approach which does not have the mechanism to know the change, since it assumed that ontology and local schema are in the static condition, and it is different in dynamic condition. The main issues are how to calculate the change of local schema or common ontology and the calculation result is used to determine which algorithm in maintaining the agreement. The experiment on the job matching domain in Indonesia have been done to show how far the performance of the approach. From the experiment, the main result are (i) the more change so the F-measure value tend to be decreased, (ii) there is no significant different in F-measure value for various modification type (add, delete, rename), and (iii) the correct choice of algorithm would improve the F-measure value.
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PDF链接：
https://arxiv.org/pdf/1003.3082

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关键词：p2p Modification Presentation Contribution Intelligence approach 研究 测度 本体 添加