Search (13 results, page 1 of 1)

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Abstract

This article examines tagging as knowledge organization. Tagging is a kind of indexing, a process of labelling and categorizing information made to support resource discovery for users. Social tagging generally means the practice whereby internet users generate keywords to describe, categorise or comment on digital content. The value of tagging comes when social tags within a collection are aggregated and shared through a folksonomy. This article examines definitions of tagging and folksonomy, and discusses the functions, advantages and disadvantages of tagging systems in relation to knowledge organization before discussing studies that have compared tagging and conventional library-based knowledge organization systems. Approaches to disciplining tagging practice are examined and tagger motivation discussed. Finally, the article outlines current research fronts.

Theme

Social tagging

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Abstract

This paper describes a survey on how system vendors and libraries handled tagging in OPACs and discovery layers. Tags are user added subject metadata, also called folksonomies. This survey also investigated user behavior when they face the possibility to tag. The findings indicate that legacy/classic systems have no tagging capability. About 47% of the discovery tools provide tagging function. About 49% of the libraries that have a system with tagging capability have turned the tagging function on in their OPACs and discovery tools. Only 40% of the libraries that turned tagging on actually utilized user added subject metadata as access point to collections. Academic library users are less active in tagging than public library users.

Theme

Social tagging

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Abstract

An increasingly difficult challenge in social tagging applications is negotiating the number of existing tags. This article examines the use of facets to facilitate the efficient organization and browsing of tags into manageable and distinct categories. Current and proposed methodologies for the application of facets in social tagging applications are evaluated. Results of this analysis indicate that these methodologies provide insufficient guidelines for the choice, evaluation, and maintenance of the facets. Suggestions are made to guide the design of a more rigorous methodology for the application of facets to social tagging applications.

Theme

Social tagging

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Theme

Social tagging

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Theme

Social tagging

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Abstract

Social Tagging ist eine weitverbreitete Methode, um nutzergenerierte Inhalte in Webdiensten zu indexieren. Dieser Artikel fasst die aktuelle Forschung zu Folksonomies und Effektivität von Tags in Retrievalsystemen zusammen. Es wurde ein TREC-ähnlicher Retrievaltest mit Tags und Ressourcen aus dem Social Bookmarking-Dienst delicious durchgeführt, welcher in Recall- und Precisionwerten für ausschließlich Tag-basierte Suchen resultierte. Außerdem wurden Tags in verschiedenen Stufen bereinigt und auf ihre Retrieval-Effektivität getestet. Testergebnisse zeigen, dass Retrieval in Folksonomies am besten mit kurzen Anfragen funktioniert. Hierbei sind die Recallwerte hoch, die Precisionwerte jedoch eher niedrig. Die Suchfunktion "power tags only" liefert verbesserte Precisionwerte.

Theme

Social tagging

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Theme

Social tagging

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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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Theme

Social tagging

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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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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

The behaviour and lexical quality of the folksonomies is examined by comparing two online social networks: Library-Thing (for books) and Flickr (for photos). We presented a case study that combines quantitative and qualitative elements, singularized by the lexical and functional framework. Our query was made by "Legal History" and by the synonyms "Law History" and "History of Law." We then examined the relevance, consistency and precision of the tags attached to the retrieved documents, in addition to their lexical composition. We identified the difficulties caused by free tagging and some of the folksonomy solutions that have been found to solve them. The results are presented in comparative tables, giving special attention to related tags within each retrieved document. Although the number of ambiguous or inconsistent tags is not very large, these do nevertheless represent the most obvious problem to search and retrieval in folksonomies. Relevance is high when the terms are assigned by especially competent taggers. Even with less expert taggers, ambiguity is often successfully corrected by contextualizing the concepts within related tags. A propinquity to associative and taxonomic lexical semantic knowledge is reached via contextual relationships.