-
Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011)
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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
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Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011)
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- Pages
- S.29-53
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Evedove Tartarotti, R. Dal'; Lopes Fujita, M.: ¬The perspective of social indexing in online bibliographic catalogs : between the individual and the collaborative (2016)
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- Source
- Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
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Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011)
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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.
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Matthews, B.; Jones, C.; Puzon, B.; Moon, J.; Tudhope, D.; Golub, K.; Nielsen, M.L.: ¬An evaluation of enhancing social tagging with a knowledge organization system (2010)
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- Date
- 29. 8.2010 11:39:20
-
Lee, D.H.; Schleyer, T.: Social tagging is no substitute for controlled indexing : a comparison of Medical Subject Headings and CiteULike tags assigned to 231,388 papers (2012)
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- Date
- 26. 8.2012 14:29:37
-
Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012)
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- Date
- 25.12.2012 15:22:37
-
Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016)
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- Date
- 21. 4.2016 11:23:22
-
Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019)
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- Date
- 20. 1.2015 18:30:22
-
Naderi, H.; Rumpler, B.: PERCIRS: a system to combine personalized and collaborative information retrieval (2010)
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- Date
- 29. 8.2010 12:59:10
