III: Small: Issues in the Management of GeoMultimedia Data

互联网的发展导致了信息产生和传递速度的急剧提高。这对于新闻周期来说尤其如此，因为新闻周期已经变得即时化，往往导致社交网络，尤其是Twitter，成为发布最新突发新闻的首选媒体。这通常以链接到更多细节的形式出现，包括新闻文章和多媒体数据（新闻照片和视频）。一个问题在于确定可靠的新闻采集者，这是通过观察他们是否是第一个报道某个话题的人，而不是转贴者和他们的频率来完成的。提供对新闻内容的访问的其他问题包括根据内容（不管创作的语言和媒体的性质）和内容的位置（即地理标记）而不是创建者的位置或隶属关系使新闻自动可索引（而不是通过人工标记）。在定位的情况下，挑战在于设计与语言无关的地理标记技术。基于机器学习的方法被研究并期望比基于规则的方法工作得更好，因为它减少了对特定语言规则的依赖，更多地依赖于示例。通过索引与包含图像的新闻文章相关的单词，方便了对图像的访问。这种索引技术的目的是作为一个过滤器来查找相似或接近重复的图像，其中相似性是基于图像特征的。通过使用地图查询接口，方便了按位置访问。这很重要，因为它对应于启用空间同义词的使用，从而允许提出更大范围的查询。该研究的一个新颖方面是纳入非英语内容，这是通过使用计算机化翻译服务来促进的，这些翻译服务将根据其在不同语言的相似文章聚类的基础上捕获内容的能力进行评估，而不是基于诸如语法正确等因素。在当今瞬息万变的世界中，本项目开发的工具将使这些信息更容易获得，因为用户可以专注于感兴趣的地理区域，并可以访问以自己语言编写的内容。这对许多组织都很有用，并将尝试与潜在用户合作，根据他们的需要定制工具。此外，该项目将为参与开发部分组件的本科生和研究生提供研究经验。这些工具也是计算机新闻这一新兴领域发展的一步。该项目的网站（http://www.cs.umd.edu/~hjs/geomultimedia.html）将提供对本研究和相关研究结果的访问。

The growth of the Internet has led to a dramatic increase in the rate at which information is generated and delivered. This is especially true for the news cycle which has become instantaneous and often resulting in social networks, most notably Twitter, being the medium of choice to deliver late breaking news. This is usually in the form of links to more details which include news articles and multimedia data (news photos and videos). One problem lies in identifying reliable news gatherers which is done by noting if they are the first to report on a topic in contrast to being a re-poster and their frequency. Other issues in providing access to news content involve making the news automatically indexable (instead of by human tagging) both by content (regardless of the language of creation and the nature of the media) and by the location of the content (i.e., geotagging) rather than the location or affiliation of its creator. In the case of location, the challenge lies in devising language-independent geotagging techniques. Machine learning based methods are investigated and are expected to work better than rule-based methods due to a reduced reliance on language-specific rules and a greater reliance on examples. Access to the images is facilitated by indexing them by the words associated with the news articles containing them. This indexing technique is meant to be used as a filter for finding similar or near-duplicate images where the similarity is based on image features. The access by location is facilitated by the use of a map query interface. This is important as it corresponds to enabling the use of spatial synonyms thereby permitting a wider range of queries to be posed. A novel aspect of the research is the incorporation of non-English content which is facilitated by the use of computerized translation services which will be evaluated on their ability to capture the content on the basis of clustering similar articles in different languages rather than on the basis of factors such as proper grammar, etc. In today's rapidly changing world, the tools that are developed in this project will make this information more accessible as users are enabled to focus on a geographical area of interest as well as have access to content in their own language. This is of utility to a number of organizations and attempts will be made to collaborate with potential users on tailoring the tools for their needs. In addition, the project will provide research experience to undergraduate and graduate students who will be involved in developing some of the components. These tools are also a step in the growth of the nascent field of computational journalism. The project web site (http://www.cs.umd.edu/~hjs/geomultimedia.html ) will provide access to results of this and related research.