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Event extraction for collective knowledge in multimedia digital EcoSystem

机译:多媒体数字生态系统中集体知识的事件提取

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Emerging technologies like Internet and Web services enable a new form of collaboration. An Internet based collaborative environment allows actors with similar profile or interest to publish and share multimedia content. This results in the availability of massive, distributed, heterogeneous and fast-moving streamed multimedia content. In addition, most of the data in the Web describes events associated to people, activities and locations. An event describing a situation might be initiated by a user, followed by a number of users within a specified time period. Extracting events from user contributed multimedia content in collaborative environments is challenging due to three reasons: 1)the content is heterogeneous in source, size and format; 2)users might use different vocabulary to describe the same event; 3)the collaboration environment contains non-events. In this paper, we have proposed an event extraction approach that will be used to build an event-based collective knowledge management framework that assists the retrieval of multimedia contents from various social media sources. This approach is accompanied by experimental results with future works.
机译:诸如Internet和Web服务之类的新兴技术实现了一种新的协作形式。基于Internet的协作环境允许具有类似个人资料或兴趣的参与者发布和共享多媒体内容。这导致大量,分布式,异构和快速移动的流多媒体内容的可用性。此外,Web中的大多数数据都描述了与人员,活动和位置相关的事件。描述情况的事件可能由用户发起,随后是指定时间段内的多个用户。在协作环境中从用户贡献的多媒体内容中提取事件具有挑战性,这归因于以下三个原因:1)内容的来源,大小和格式是异构的; 2)用户可能使用不同的词汇来描述同一事件; 3)协作环境包含非事件。在本文中,我们提出了一种事件提取方法,该方法将用于建立基于事件的集体知识管理框架,以帮助从各种社交媒体源中检索多媒体内容。这种方法伴随着实验结果和未来的工作。

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