Search (12 results, page 1 of 1)

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Abstract

Folksonomy is the result of describing Web resources with tags created by Web users. Although it has become a popular application for the description of resources, in general terms Folksonomies are not being conveniently integrated in metadata. However, if the appropriate metadata elements are identified, then further work may be conducted to automatically assign tags to these elements (RDF properties) and use them in Semantic Web applications. This article presents research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies and to propose an application profile for DC Social Tagging. The work provides information that may be used by software applications to assign tags to metadata elements and, therefore, means for tags to be conveniently gathered by metadata interoperability tools. Despite the unquestionably high value of DC and the significance of the already existing properties in DC Terms, the pilot study show revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties, such as Action, Depth, Rate, and Utility was determined. Those potential new properties will have to be validated in a later stage by the DC Social Tagging Community.

Pages

S.14-22

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Date

22. 9.2007 15:41:14

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Abstract

The field of subject analysis enjoyed a flurry of interest in the 1970s, and has recently become a focus of attention again. The scholarly community doing work in this area has become more diffuse, and has grown to include new groups, such as information architects. Changes in information services and information seeking have led to reexamination of the nature and role of subject analysis tools and practices. This selective review looks at thesauri, guided navigation, and folksonomy as three activity areas in which subject analysis researchers have been attempting to address rapidly changing new environments.

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Date

5. 1.2008 19:22:48

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Date

1. 8.2008 12:39:22

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Abstract

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies. I also want to convince you that what we're seeing when we see the Web is actually a radical break with previous categorization strategies, rather than an extension of them. The second part of the talk is more speculative, because it is often the case that old systems get broken before people know what's going to take their place. (Anyone watching the music industry can see this at work today.) That's what I think is happening with categorization. What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units -- the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging -- free-form labeling, without regard to categorical constraints -- seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

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Abstract

Social tagging systems, known as "folksonomies," represent an important part of web resource discovery as they enable free and unrestricted browsing through information space. Folksonomies consisting of subject designators (tags) assigned by users, however, have one important drawback: they do not express semantic relationships, either hierarchical or associative, between tags. As a consequence, the use of tags to browse information resources requires moving from one resource to another, based on coincidence and not on the pre-established meaningful or logical connections that may exist between related resources. We suggest that the semantic structure of the Universal Decimal Classification (UDC) may be used in complementing and supporting tag-based browsing. In this work, two specific questions were investigated: 1) Are terms used as tags in folksonomies included in the UDC?; and, 2) Which facets of UDC match the characteristics of documents or information objects that are tagged in folksonomies? A collection of the most popular tags from Amazon, LibraryThing, Delicious, and 43Things was investigated. The universal nature of UDC was examined through the universality of topics and facets covering diverse human interests which are at the same time interconnected and form a rich and intricate semantic structure. The results suggest that UDC-supported folksonomies could be implemented in resource discovery, in particular in library portals and catalogues.

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Abstract

This paper proposes a conceptual framework to recast a folksonomy as a Web classification and to use this to explore the ways in which people work with it in assessing, sharing, and navigating Web resources. The author uses information scent and foraging theory as a context to discuss how folksonomy is constructed through interactions among users, a folksonomic system, and a given domain that consists of a group of users who share the same interest or goals. The discussion centers on two dimensions of folksonomies: (1) folksonomy as a Web classification which puts like information together in a Web context; and (2) folksonomy as information scent which helps users to find related resources and users, and obtain desired information. This paper aims to integrate these two dimensions with a conceptual framework that addresses the structure of a folksonomy shaped by users' interactions. A proposed framework consists of three components of users' interactions with a folksonomy: (a) tagging - cognitive categorization of Web accessible resources by an individual user; (b) navigation - exploration and discovery of Web accessible resources in the folksonomic system; and (c) knowledge sharing - representation and communication of knowledge within a domain. This understanding will help us motivate possible future directions of research in folksonomy. This initial framework will frame a number of research questions and help lay the groundwork for future empirical research which focuses on qualitative analysis of a folksonomy and users' tagging behaviors.

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Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

What is the role of controlled vocabulary in a Web 2.0 world? Can we have the best of both worlds: balancing folksonomies and controlled vocabularies to help communities of users find and share information and resources most relevant to them? education.au develops and manages Australian online services for education and training. Its goal is to bring people, learning and technology together. education.au projects are increasingly involved in exploring the use of Web 2.0 developments building on user ideas, knowledge and experience, and how these might be integrated with existing information management systems. This paper presents work being undertaken in this area, particularly in relation to controlled vocabularies, and discusses the challenges faced. Education Network Australia (edna) is a leading online resource collection and collaborative network for education, with an extensive repository of selected educational resources with metadata created by educators and information specialists. It uses controlled vocabularies for metadata creation and searching, where users receive suggested related terms from an education thesaurus, with their results. We recognise that no formal thesaurus can keep pace with user needs so are interested in exploiting the power of folksonomies. We describe a proof of concept project to develop community contributions to managing information and resources, using Taxonomy-Directed Folksonomy. An established taxonomy from the Australian education sector suggests terms for tagging and users can suggest terms. Importantly, the folksonomy will feed back into the taxonomy showing gaps in coverage and helping us to monitor new terms and usage to improve and develop our formal taxonomies. This model would initially sit alongside the current edna repositories, tools and services but will give us valuable user contributed resources as well as information about how users manage resources. Observing terms suggested, chosen and used in folksonomies is a rich source of information for developing our formal systems so that we can indeed get the best of both worlds.

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Abstract

In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.

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Date

3. 5.1997 8:44:22