-
Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009)
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- Date
- 1. 8.2010 12:35:22
-
Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012)
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- Date
- 25.12.2012 15:22:37
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Regulski, K.: Aufwand und Nutzen beim Einsatz von Social-Bookmarking-Services als Nachweisinstrument für wissenschaftliche Forschungsartikel am Beispiel von BibSonomy (2007)
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-
Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008)
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- Pages
- S.15-22
-
Hidderley, R.; Rafferty, P.: Flickr and democratic indexing : disciplining desire lines (2006)
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- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
-
Tschetschonig, K.; Ladengruber, R.; Hampel, T.; Schulte, J.: Kollaborative Tagging-Systeme im Electronic Commerce (2008)
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-
Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008)
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- 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
-
Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008)
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- Date
- 21. 6.2009 12:22:44
-
Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009)
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- Date
- 10. 9.2000 17:38:22
-
Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009)
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- Date
- 10. 9.2000 17:38:22
-
Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011)
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- 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
-
Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014)
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-
Munk, T.B.; Moerk, K.: Folksonomies, tagging communities, and tagging strategies : an empirical study (2007)
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-
Chopin, K.: Finding communities : alternative viewpoints through weblogs and tagging (2008)
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-
Simon, J.: Interdisciplinary knowledge creation : using wikis in science (2006)
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- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
-
Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010)
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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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-
Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011)
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- Abstract
- Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).
-
Yoon, K.: Conceptual syntagmatic associations in user tagging (2012)
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-
Knautz, K.; Stock, W.G.: Collective indexing of emotions in videos (2011)
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