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摘要翻译：
语义网络研究在认知科学的早期历史中，随着语义网倡议的出现，出现了一个复兴。语义Web的努力已经在世界范围内提出了一系列支持语义网络数据结构的编码、存储和查询的技术。目前，语义网的流行概念是一种数据建模媒体，在这种媒体中，真实的和概念性的实体以语义上有意义的方式相关联。然而，新的模型已经出现，在语义网络基础上显式地编码过程信息。随着这些新技术的出现，语义网已经从一个数据建模媒体发展成为一个计算媒体。本文提供了现有计算建模工作的分类和支持技术的需求，这些技术将有助于这一新兴领域的进一步发展。
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英文标题：
《Modeling Computations in a Semantic Network》
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作者：
Marko A. Rodriguez and Johan Bollen
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最新提交年份：
2007
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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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英文摘要：
Semantic network research has seen a resurgence from its early history in the cognitive sciences with the inception of the Semantic Web initiative. The Semantic Web effort has brought forth an array of technologies that support the encoding, storage, and querying of the semantic network data structure at the world stage. Currently, the popular conception of the Semantic Web is that of a data modeling medium where real and conceptual entities are related in semantically meaningful ways. However, new models have emerged that explicitly encode procedural information within the semantic network substrate. With these new technologies, the Semantic Web has evolved from a data modeling medium to a computational medium. This article provides a classification of existing computational modeling efforts and the requirements of supporting technologies that will aid in the further growth of this burgeoning domain.
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PDF链接：
https://arxiv.org/pdf/0706.0022
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