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首页> 外文会议>2017 International Conference on Emerging Trends amp; Innovation in ICT >Expert search based knowledge sharing system for collaborative environment
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Expert search based knowledge sharing system for collaborative environment

机译：基于专家搜索的协作环境知识共享系统

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摘要

In collaborative environment (CE) multiple members work together to achieve a common goal. But to find person/source that has most relevant information is a challenging part as the information requirement varies from task to task. Today, people are working in a collaborative environment to explore the ever increasing data and have new insights for knowledge sharing. Analyzing these needs we have proposed a system that finds the most appropriate and relevant documents based on the search query. In this system relevancy of document is supported by expert search method. In expert search, various aspects such as author name, hit count (number of downloads) of document, time span of hit count and last hit to that document are considered and clustering of retrieved results with meaningful cluster labels are identified to find whether a search term is used in the intended sense in that document. In this system, documents uploaded by members are analyzed. After analysis, indexing of documents is done. Further based on search query documents are retrieved and labeled clusters of documents are formed. Finally expert search is applied over mined results. This system helps in getting exact knowledge with quick response and repeating efforts for finding same information can be avoided with efficient time utilization. The performance of proposed system is evaluated with respect to response time of system. Thus, the effective use of knowledge sharing (data/information) is achieved with the Expert Search for time efficient systems.
机译：在协作环境（CE）中，多个成员共同努力以实现一个共同的目标。但是，要找到具有最相关信息的人/资源是一项具有挑战性的工作，因为信息要求因任务而异。如今，人们正在协作环境中工作，以探索不断增长的数据并为知识共享提供新见解。分析这些需求后，我们提出了一个系统，该系统可基于搜索查询找到最合适和最相关的文档。在该系统中，专家搜索方法支持文档的相关性。在专家搜索中，考虑了各个方面，例如作者姓名，文档的命中次数（下载次数），命中次数的时间跨度以及对该文档的最后命中，并使用有意义的聚类标签对检索到的结果进行聚类，以确定是否进行搜索该术语在该文档中按预期含义使用。在该系统中，分析成员上传的文档。分析之后，将对文档建立索引。进一步基于搜索查询，检索文档并形成标记的文档簇。最后，将专家搜索应用于挖掘结果。该系统有助于快速响应获得准确的知识，并且可以通过有效的时间利用避免重复寻找相同信息的工作。相对于系统响应时间来评估所提出系统的性能。因此，通过对时间高效系统的专家搜​​索，可以有效地利用知识共享（数据/信息）。

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