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摘要翻译：
语义网信息处于人类所掌握的长长的管道的末端。他们是信息的源头，他们会显式地消费信息，因为信息将以可读的方式传递给他们，或者隐式地消费信息，因为消费这些信息的计算机进程会影响他们。计算机特别能够处理提供给它们的信息。然而，人们可能会给他们提供的信息分配一个比语义技术可能考虑的更窄的含义。当人们不认为他们的断言模棱两可时，通常会发生这种情况。模型理论用于为语义web上的信息提供语义，它特别适合于保持歧义性并将其传递到管道的另一边。事实上，它保留了尽可能多的解释。这种对推理效率的要求，成为准确交流和保持意义的不足。克服它可能需要交互式反馈或保存源上下文。社会科学和人文科学的工作可能有助于解决这个特殊的问题。
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英文标题：
《Evolving knowledge through negotiation》
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作者：
J\'er\^ome Euzenat
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最新提交年份：
2012
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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：Human-Computer Interaction 人机交互
分类描述：Covers human factors, user interfaces, and collaborative computing. Roughly includes material in ACM Subject Classes H.1.2 and all of H.5, except for H.5.1, which is more likely to have Multimedia as the primary subject area.
包括人为因素、用户界面和协作计算。大致包括ACM学科课程H.1.2和所有H.5中的材料，除了H.5.1，它更有可能以多媒体作为主要学科领域。
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英文摘要：
Semantic web information is at the extremities of long pipelines held by human beings. They are at the origin of information and they will consume it either explicitly because the information will be delivered to them in a readable way, or implicitly because the computer processes consuming this information will affect them. Computers are particularly capable of dealing with information the way it is provided to them. However, people may assign to the information they provide a narrower meaning than semantic technologies may consider. This is typically what happens when people do not think their assertions as ambiguous. Model theory, used to provide semantics to the information on the semantic web, is particularly apt at preserving ambiguity and delivering it to the other side of the pipeline. Indeed, it preserves as much interpretations as possible. This quality for reasoning efficiency, becomes a deficiency for accurate communication and meaning preservation. Overcoming it may require either interactive feedback or preservation of the source context. Work from social science and humanities may help solving this particular problem.
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PDF链接：
https://arxiv.org/pdf/1207.6224
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