This short paper addresses the lack of accuracy in social tagging systems, as information retrieval systems, in comparison with traditional search-engines. The lack of accuracy is caused by the vocabulary problems and the nature of tagging systems which rely on lower number of index terms for each resource. Tagraph vocabulary system which is based on a weighted directed graph of tags, and Tag Qualifiers, are proposed to mitigate these problems and increase the precision and the recall of social tagging systems. Both solutions are based on community contributions, therefore specific procedures such as task routing should be used to increase the number of contributions and therefore to achieve a more accurate system.
Keywords
- Information Retrieval System
- Index Term
- Relevance Qualifier
- Weighted Directed Graph
- Information Retrieval Method
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Sen S, Lam S K, Cosley D, Rashid A M, Frankowski D, Harper F, Osterhouse J, Riedl J (2006) tagging, community, vocabulary, evolution. 20th anniversary conference on Computer supported cooperative work, pp. 181–190. ACM Press
Marlow C, Naaman M, Boyd D, Davis M (2006) HT06, Tagging Paper, Taxonomy, Flickr, Academic Article, ToRead., seventeenth ACM conference on Hypertext and hypermedia, pp. 31–40. ACM Press
Golber S, Huberman B A, The Structure of Collaborative Tagging System, Information Dynamics Lab: HP Labs, Palo Alto, USA, http://arxiv.org/abs/cs.DL/0508082
Cosley D, Frankowski D, Terveen L, Riedl J (2007) SuggestBot: using intelligent task routing to help people find work in wikipedia. 12th international Conference on intelligent User interfaces, pp. 181–190. ACM Press.
Korfiatis N (2007) Social and Economic Incentives in Online Social Interactions: A Model and Typology. 30th Information Systems Research Seminar in Scandinavia IRIS.
Ludford P, Cosley D, Frankowski D, Terveen L (2004). Think Different: Increasing Online Community Participation Using Uniqueness and Group Dissimilarity. CHI 2004, pp. 631–638. ACM Press
[7] Furnas G W, Landauer T K, Gomez L M, Dumais S T (1987) The vocabulary problem in human-system communication. Communications, 30 (11), 964 – 971. ACM Press.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this paper
Cite this paper
Nobarany, S., Haraty, M. (2009). Improving Accuracy of Tagging Systems Using Tag Qualifiers and Tagraph Vocabulary System. In: Sicilia, MA., Lytras, M.D. (eds) Metadata and Semantics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77745-0_21
Download citation
DOI: https://doi.org/10.1007/978-0-387-77745-0_21
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-77744-3
Online ISBN: 978-0-387-77745-0
eBook Packages: Computer ScienceComputer Science (R0)