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A System for Web Widget Discovery Using Semantic Distance between User Intent and Social Tags

机译:使用用户意图和社交标签之间的语义距离的Web窗口小部件发现系统

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Social interaction leverages collective intelligence through user-generated content, social networking, and social annotation. Users are enabled to enrich knowledge representation by rating, commenting, and tagging. The existing systems for service discovery make use of semantic relation among social tags, but ignore the relation between a user information need for services and tags. This paper first provides an overview of how social tagging is applied to discover contents/services. An enhanced web widget discovery model that aims to discover services mostly relevant to users is then proposed. The model includes an algorithm that quantifies the accurate relation between user intent for a service and the tags of a widget, as well as three different widget discovery schemes. Using the online service of Widgetbox.com, we experimentally demonstrate the accuracy and efficiency of our system.
机译:社交互动通过用户生成的内容,社交网络和社会注释来利用集体智能。用户已通过评级,评论和标记来丰富知识表示。服务发现的现有系统利用社交标签之间的语义关系,但忽略了用户信息对服务和标签之间的关系。本文首先概述了社交标记如何应用于发现内容/服务。然后提出了一个增强的Web窗口小部件发现模型,其目的是发现与用户相关的服务。该模型包括一种算法,该算法可以定量用户意图与窗口小部件的标签的准确关系,以及三种不同的小部件发现方案。使用WidgetBox.com的在线服务,我们通过实验展示了我们系统的准确性和效率。

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