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In this paper, we propose a new probabilistic generative model, called Topic-Perspective Model, for simulating the generation process of social annotations. Different from other generative models, in our model, the tag generation process is separated from the content term generation process. While content terms are only generated from resource topics,… (More)
—Social tagging is a major characteristic of Web 2.0. A social tagging system can be modeled with a tripartite network of users, resources, and tags. In this paper, we investigate how to enhance Web clustering by leveraging the tripartite network of social tagging systems. We propose a clustering method called " Tripartite Clustering " which clusters the… (More)
Social tagging, as a recent approach for creating metadata, has caught the attention of library and information science researchers. Many researchers recommend incorporating social tagging into the library environment and combining folksonomies with formal classification. However, some researchers are concerned with the quality issues of social annotation… (More)
A Collection of 17 Scholarly Titles There are many facets of online social practices, including, but not limited to, generational, gender, and cultural aspects. With the explosive growth of contemporary online social culture, a new and increasingly important area of study on online social behavior emerges. The Online Social Behavior collection is a… (More)
The purpose of this paper is to examine the interoperability of the Dublin Core metadata element set across a selection of digital video repositories. To explore how the metadata was applied and analyze its overall quality, 150 records were selected, 25 from each of 6 collections, and evaluated for use of the original 15 Dublin Core elements. Each record… (More)
The Internet Public Library (IPL) is crosswalking its metadata to Dublin Core. The quality of the crosswalked metadata will be unknown. The IPL is therefore developing a tool for metadata quality control suitable for use by LIS students who have little previous metadata quality control experience.