-
Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012)
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- Date
- 25.12.2012 15:22:37
- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2488-2502
-
Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011)
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- Pages
- S.149-161
- 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
-
Weiand, K.; Hartl, A.; Hausmann, S.; Furche, T.; Bry, F.: Keyword-based search over semantic data (2012)
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- Pages
- S.159-192
-
Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014)
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- Source
- Journal of documentation. 70(2014) no.5, S.801-828
-
Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1658-1672
-
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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- Source
- Aslib proceedings. 62(2010) nos.4/5, S.447-465
-
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).
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.12, S.2364-2381
-
Yoon, K.: Conceptual syntagmatic associations in user tagging (2012)
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- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.923-935
-
Knautz, K.; Stock, W.G.: Collective indexing of emotions in videos (2011)
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- Source
- Journal of documentation. 67(2011) no.6, S.975-994
-
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
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1089-1104
-
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
- Source
- Aslib journal of information management. 71(2019) no.2, S.155-175
-
Aagaard, H.: Social indexing at the Stockholm Public Library (2011)
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- Location
- S
- Pages
- S.143-153
-
Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.505-521
-
Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012)
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- Information processing and management. 48(2012) no.4, S.599-617
-
Peters, I.: Benutzerzentrierte Erschließungsverfahren (2013)
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- Pages
- S.229-237
-
Chan, L.M.: Social bookmarking and subject indexing (2011)
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- Pages
- S.127-142
-
Social tagging in a linked data environment. Edited by Diane Rasmussen Pennington and Louise F. Spiteri. London, UK: Facet Publishing, 2018. 240 pp. £74.95 (paperback). (ISBN 9781783303380) (2019)
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- Footnote
- Rez. in: JASIST 72(2021) no.2, S.264-265 (Xuwei Pan).
- Pages
- XII, 212 S
- Type
- s
-
Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011)
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- Pages
- S.29-53
-
Spiteri, L.F.: Extending the scope of library discovery systems via hashtags (2018)
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- Pages
- S.557-564
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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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- Pages
- S.257-264
