III-COR-small: Harvesting Concept Hierarchies from Social Data

社交网络正在改变人们创造和使用信息的方式。Flickr, del。icio等网站。我们，Digg和其他网站，使用户能够发布和组织内容并参与社区。他们在与内容和其他用户交互时创建的信息被称为社交元数据。标签是社会元数据的一个例子，它的引入是为了让个人通过为其分配自由选择的关键字来组织其内容。一些社交网站现在还允许用户按层次组织内容。例如，照片共享网站Flickr允许用户将相关的照片分组为集，并将相关的集分组为集。尽管社会元数据缺乏正式的结构，但它捕获了社区的集体知识。这种集体知识一旦从众多用户留下的痕迹中提取出来，将为社交网络的内容增添丰富的语义层。该项目将开发一个概率框架，将不同类型的社会元数据结合起来，构建一个共同的概念层次结构。此外，该项目开发的方法将以社区参与的形式利用社会关系来发现社区特有的词汇和概念，并确定多维概念的各个方面。将来，社交网站和数据管理工具将允许用户表达更丰富的知识类型，包括复杂的谓词和语义关系。将单独表达的知识聚合成一个统一整体的能力将改变人们使用信息的方式。例如，全局概念层次结构可以帮助用户可视化他们的内容与他人的内容之间的关系，并允许更有效的浏览、搜索和发现。通过将内容链接到公共概念层次结构，项目开发的方法还可以用于集成不同的数据并跨域对齐。因此，拟议的工作解决了人工智能中一个更重要的新问题，即如何利用集体智慧的力量。有关该项目的进一步信息，请访问该项目的网站http://www.isi.edu/~lerman/projects/folksonomy.html。

The Social Web is changing the way people create and use information. Sites like Flickr, Del.icio.us, Digg, and others, enable users to publish and organize content and participate in communities. The information they create while interacting with content and other users is called social metadata. Tags, one example of social metadata, were introduced as a means for individuals to organize their content by assigning freely-chosen keywords to it. Some Social Web sites now also allow users to organize content hierarchically. The photosharing site Flickr, for example, allows users to group related photos in sets, and related sets in collections. Althoughsocial metadata lacks formal structure, it captures the collective knowledge of the community. Once extracted from the traces left by many users, such collective knowledge will add a rich semantic layer to the content of the Social Web. This project will develop a probabilistic framework to combine diverse types of social metadata to construct a common concept hierarchy. In addition, the methods developed by the project will use social relations, in the form of community participation, to discover community-specific vocabularies and concepts, and identify facets of multi-dimensional concepts.In the future, Social Web sites and data management tools will allow users to express ever richer types of knowledge, including complex predicates and semantic relations. The ability to aggregate individually expressed knowledge into a unified whole will transform the way people use information. Global concept hierarchies, for instance, can help users visualize how their content relates to that of others and allow for more efficient browsing, search and discovery. By linking content to a common concept hierarchy, the methods developed by the project could also be used to integrate disparate data and align it across domains. The proposed work, therefore, addresses one of the more important emerging questions in AI, namely, how to harness the power of collective intelligence.For further information about this project, please see the project Web site at http://www.isi.edu/~lerman/projects/folksonomy.html.