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Augmenting Web Service Discovery by Cognitive Semantics and Abduction

机译:通过认知语义和绑架增强网络服务发现

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We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.
机译:我们认为Web服务发现技术应该通过提供对自己可能无法制定的服务的建议,帮助用户通过提供自己的建议,以便他缺乏认识资源来实现。服务环境中的免费文本文档提供了一个未开发的信息来源,用于增强用户的认知状态,从而可以有效地搜索服务的能力。以这些自由文本文档计算的语义空间模型的形式采用了语义知识表示的定量方法。从语义空间计算的关联推论促进了用户议程的知识。推论是暗示的,旨在促进人类的绑架推理,以指导用户从模糊搜索目标中更好地理解围绕给定议程的问题空间。基于复杂和现实的规划活动讨论了实验结果。

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