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  • × theme_ss:"Social tagging"
  1. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.02 
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    Abstract
    Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.
    Date
    1. 8.2010 12:35:22
  2. Santini, M.: Zero, single, or multi? : genre of web pages through the users' perspective (2008) 0.01 
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    Date
    30. 7.2008 10:29:54
    Source
    Information processing and management. 44(2008) no.2, S.702-737
  3. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.01 
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.2, S.155-175
  4. Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008) 0.01 
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    Date
    21. 6.2009 9:55:29
    Pages
    S.15-22
  5. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.01 
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    Date
    29. 5.2012 13:58:08
    29. 5.2012 14:15:36
    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
  6. Hammond, T.; Hannay, T.; Lund, B.; Flack, M.: Social bookmarking tools (II) : a case study - Connotea (2005) 0.01 
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    Abstract
    Connotea is a free online reference management and social bookmarking service for scientists created by Nature Publishing Group. While somewhat experimental in nature, Connotea already has a large and growing number of users, and is a real, fully functioning service. The label 'experimental' is not meant to imply that the service is any way ephemeral or esoteric, rather that the concept of social bookmarking itself and the application of that concept to reference management are both recent developments. Connotea is under active development, and we are still in the process of discovering how people will use it. In addition to Connotea being a free and public service, the core code is freely available under an open source license. Connotea was conceived from the outset as an online, social tool. Seeing the possibilities that del.icio.us was opening up for its users in the area of general web linking, we realised that scholarly reference management was a similar problem space. Connotea was designed and developed late in 2004, and soft-launched at the end of December 2004. Usage has grown over the past several months, to the point where there is now enough data in the system for interesting second-order effects to emerge. This paper will start by giving an overview of Connotea, and will outline the key concepts and describe its main features. We will then take the reader on a brief guided tour, show some of the aforementioned second-order effects, and end with a discussion of Connotea's likely future direction.
  7. Kuchler, T.; Pawlowski, J.M.; Zimmermann, V.: Social Tagging and Open Content : a concept for the future of e-learning and knowledge management? (2008) 0.01 
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    Abstract
    Open Content is a promising concept for e-learning and knowledge management. It can improve sharing and re-using educational resources and create new business opportunities. However, in contrast to open source software, these opportunities have not yet been adopted by a wide community. This article discusses barriers and opportunities. The Content Explosion Model shows how content can be re-used and adapted to increase sharing and distributing Open Content. Social tagging is discussed, on the basis of an implementation example (SLIDESTAR), as a means of fostering content exchange on a content community platform.
  8. Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008) 0.01 
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    Date
    20. 2.2009 10:29:07
    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
  9. Tennis, J.T.: Measured time : imposing a temporal metric to classificatory structures 0.01 
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    Abstract
    Describes three units of time helpful for understanding and evaluating classificatory structures: long time (versions and states of classification schemes), short time (the act of indexing as repeated ritual or form), and micro-time (where stages of the interpretation process of indexing are separated out and inventoried). Concludes with a short discussion of how time and the impermanence of classification also conjures up an artistic conceptualization of indexing, and briefly uses that to question the seemingly dominant understanding of classification practice as outcome of scientific management and assembly line thought.
  10. Komus, A.; Wauch, F.: Wikimanagement : was Unternehmen von Social-Software und Web 2.0 lernen können (2008) 0.01 
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    Content
    Inhalt: I. Wie funktionieren Social Software-Angebote? II. Welchen Erklärungsbeitrag leisten bestehende Organisationsansätze und welche Schlüsse muss die Organisationslehre aus den Erfahrungen ziehen? III. Welches sind die Erfolgsfaktoren von Social Software und wie lassen sich Technologie und Erfolgsfaktoren in das Management übertragen und in Unternehmen nutzen?
    RSWK
    Management / Soziale Software / Leitbild
    Subject
    Management / Soziale Software / Leitbild
  11. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.01 
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    Source
    Information processing and management. 46(2010) no.1, S.58-70
  12. Konkova, E.; Göker, A.; Butterworth, R.; MacFarlane, A.: Social tagging: exploring the image, the tags, and the game (2014) 0.01 
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    Abstract
    Large image collections on the Web need to be organized for effective retrieval. Metadata has a key role in image retrieval but rely on professionally assigned tags which is not a viable option. Current content-based image retrieval systems have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. We present two social tagging alternatives in the form of photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view, investigating the management of social tagging for indexing. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as in terpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.
  13. Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012) 0.01 
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    Source
    Information processing and management. 48(2012) no.4, S.599-617
  14. Hänger, C.: Knowledge management in the digital age : the possibilities of user generated content (2009) 0.00 
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  15. Heckner, M.: Tagging, rating, posting : studying forms of user contribution for web-based information management and information retrieval (2009) 0.00 
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  16. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.00 
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    Abstract
    Social tagging or collaborative tagging has become a new trend in the organization, management, and discovery of digital information. The rapid growth of shared information mostly controlled by social tags poses a new challenge for social tag-based information organization and retrieval. A plausible approach for this challenge is linking social tags to a controlled vocabulary. As an introductory step for this approach, this study investigates ways of predicting relevant subject headings for resources from social tags assigned to the resources. The prediction of subject headings was measured by five different similarity measures: tf-idf, cosine-based similarity (CoS), Jaccard similarity (or Jaccard coefficient; JS), Mutual information (MI), and information radius (IRad). Their results were compared to those by professionals. The results show that a CoS measure based on top five social tags was most effective. Inclusions of more social tags only aggravate the performance. The performance of JS is comparable to the performance of CoS while tf-idf is comparable with up to 70% less than the best performance. MI and IRad have inferior performance compared to the other methods. This study demonstrates the application of the similarity measuring techniques to the prediction of correct Library of Congress subject headings.
  17. Rorissa, A.: ¬A comparative study of Flickr tags and index terms in a general image collection (2010) 0.00 
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    Abstract
    Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.
  18. Tsui, E.; Wang, W.M.; Cheung, C.F.; Lau, A.S.M.: ¬A concept-relationship acquisition and inference approach for hierarchical taxonomy construction from tags (2010) 0.00 
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    Source
    Information processing and management. 46(2010) no.1, S.44-57
  19. Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011) 0.00 
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    Abstract
    As the web has grown into an integral part of daily life, social annotation has become a popular manner for web users to manage resources. This method of management has many potential applications, but it is limited in applicability by the cold-start problem, especially for new resources on the web. In this article, we study automatic tag prediction for web pages comprehensively and utilize the predicted tags to improve search performance. First, we explore the stabilizing phenomenon of tag usage in a social bookmarking system. Then, we propose a two-stage tag prediction approach, which is efficient and is effective in making use of early annotations from users. In the first stage, content-based ranking, candidate tags are selected and ranked to generate an initial tag list. In the second stage, random-walk re-ranking, we adopt a random-walk model that utilizes tag co-occurrence information to re-rank the initial list. The experimental results show that our algorithm effectively proposes appropriate tags for target web pages. In addition, we present a framework to incorporate tag prediction in a general web search. The experimental results of the web search validate the hypothesis that the proposed framework significantly enhances the typical retrieval model.
  20. Heckner, M.; Mühlbacher, S.; Wolff, C.: Tagging tagging : a classification model for user keywords in scientific bibliography management systems (2007) 0.00 
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