Group items tagged

User profiles can be used to identify persons inside a community with similar interests. Folksonomy systems allow users to individually tag the objects of a common set (e.g., web pages). In this paper, we propose to create user profiles from the data available in such folksonomy systems by letting users specify the most relevant objects in the system. Instead of using the objects directly to represent the user profile, we propose to use the tags associated with the specified objects to build the user profile. We have designed a prototype for the research domain to use such tag-based profiles in finding persons with similar interests. The combination of tag-based profiles with standard recommender system technology has resulted in a new kind of recommender system to recommend related publications, keywords, and persons.

user profiles based on tagging

This paper examines user-generated metadata as implemented and applied in two web services designed to share and organize digital me- dia to better understand grassroots classification. Metadata - data about data - allows systems to collocate related information, and helps users find relevant information.

another article about folksonomies and tagging..

another paper on collaborative tagging.. interesting..

This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.

This paper explores the system of categories that is used to classify articles in Wikipedia. It is compared to collaborative tagging systems like del.icio.us and to hierarchical classification like the Dewey Decimal Classification (DDC). Specifics and commonalitiess of these systems of subject indexing are exposed. Analysis of structural and statistical properties (descriptors per record, records per descriptor, descriptor levels) shows that the category system of Wikimedia is a thesaurus that combines collaborative tagging and hierarchical subject indexing in a special way.

comparison of Dewey's system of categorization and Wikipedia's mixed model.

Tagging has arisen as way to enable users to contribute to a loose taxonomy characterizing web pages, pictures, products and other things. We propose tagging people in order to help individuals keep track of each other while contributing to a loose characterization of their friends and colleagues. "Fringe Contacts" is a reference system designed to test whether people- tagging is a viable and useful approach.

people tagging.. we need that too?

This paper presents a novel approach to Tag-Cloud's tags selection, and proposes the use of clustering algorithms for visual layout, with the aim of improve browsing experience. The results suggest that presented approach reduces the semantic density of tag set, and improves the visual consistency of Tag-Cloud layout.

handig.. een alternative manier om tag-clouds te maken. makes sense.

Yahoo! employee describes and defines criteria and algorithms for a collaborative tag system: Since tags are created by individual users in a free form, one important problem facing tagging is to identify most appropriate tags, while eliminating noise and spam. For this purpose, we define a set of general criteria for a good tagging system. These criteria include high coverage of multiple facets to ensure good recall, least effort to reduce the cost involved in browsing, and high popularity to ensure tag quality. We propose a collaborative tag suggestion algorithm using these criteria to spot high-quality tags.

another one about tagging: describes criteria for a good tagging system.