集体智慧中的隐性知识探索--以语言语用学和量子逻辑处理大众分类法的不确定性本体论
Search for Hidden Knowledge in Collective Intelligence dealing Indeterminacy Ontology of Folksonomy with Linguistic Pragmatics and Quantum Logic
摘要：
信息检索不仅是Web上最常见的应用，而且是各种应用的基础。考虑到集体智慧的群体的个人作为一个框架，评估和纳入新的经验和信息，我们往往不能检索这样的知识是隐性的。隐性知识是许多竞争能力的基础，在离散的本体结构上很难表达。它是非结构化或无组织的，因此仍然是隐藏的。开发能够找到隐藏知识的通用解决方案是非常复杂的。这对语义技术的开发者来说也是一个巨大的挑战。这项工作的目的是探索如何使隐性知识隐藏在组织内的协作环境的集体智慧明确和可用。该环境由多面语义搜索支持的大众分类法定义。采用向量空间模型来表示和操作大众分类法的意义，该模型与量子理论的数学工具相类似。向量空间检索是一种有效的数据检索方法，在不存在数据行为的情况下，向量空间检索的排序算法涉及的元素类型少，运算量小。当提出查询时，找到用户心中所想的解决方案可以基于被理解为内容的创建者和内容的读者的联合联系的“联合意义”。联合意义的提出是为了解决大众分类法在本体论上的不确定性、集体智慧上的不完全性和不一致性。随着实际社交网络（如Facebook、LinkedIn等）的发展，为协作环境构建了一个概念验证原型。在RIA应用程序上使用语义Web技术和技术的信息可视化。
英文摘要：
Information retrieval is not only the most frequent application executed on the Web but it is also the base of different types of applications. Considering collective intelligence of groups of individuals as a framework for evaluating and incorporating new experiences and information we often cannot retrieve such knowledge being tacit. Tacit knowledge underlies many competitive capabilities and it is hard to articulate on discrete ontology structure. It is unstructured or unorganized, and therefore remains hidden. Developing generic solutions that can find the hidden knowledge is extremely complex. Moreover this will be a great challenge for the developers of semantic technologies. This work aims to explore ways to make explicit and available the tacit knowledge hidden in the collective intelligence of a collaborative environment within organizations. The environment was defined by folksonomies supported by a faceted semantic search. Vector space model which incorporates an analogy with the mathematical apparatus of quantum theory is adopted for the representation and manipulation of the meaning of folksonomy. Vector space retrieval has been proven efficiency when there isn't a data behavioural because it bears ranking algorithms involving a small number of types of elements and few operations. A solution to find what the user has in mind when posing a query could be based on "joint meaning" understood as a joint construal of the creator of the contents and the reader of the contents. The joint meaning was proposed to deal with vagueness on ontology of folksonomy indeterminacy, incompleteness and inconsistencies on collective intelligence. A proof-of concept prototype was built for collaborative environment as evolution of the actual social networks (like Facebook, LinkedIn,..) using the information visualization on a RIA application with Semantic Web techniques and technologies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
