COLLABORATIVE TAGGING USING CAPTCHA

Me.Jakeera Begum, M.Venkata Rao

Abstract


Tagging is most widely used feature in online networks. There are no of tags are available mainly offline resources based on their feedback, expressed in the form of free-text labels (i.e., tags). Recently there is a problem based on the tagging of feedback, free-text labels etc. Without user permission tags are automatically generated spam scripts. So, users are facing many sensitive problems like privacy. In the existing system, a privacy-preserving collaborative tagging service, by showing how a specific privacy-enhancing technology, namely tag suppression, can be used to protect end-user privacy. Some problems identified in the existing system. To overcome these problems captcha based security in introduced in the proposed system to provide better security for the tagging information. Results will show the performance of the proposed system.


Keywords


Tagging; Captcha; Privacy;

References


P. Mika, “Ontologies Are Us: A Unified Model of Social Networks and Semantics,” Proc. Int’l Semantic Web Conf. (ISWC ’05), Y. Gil, E. Motta, V. Benjamins, and M. Musen, eds., pp. 522-536, 2005.

X. Wu, L. Zhang, and Y. Yu, “Exploring Social Annotations for the Semantic Web,” Proc. 15th Int’l World Wide Web Conf. (WWW), pp. 417-426, 2006.

B. Markines, C. Cattuto, F. Menczer, D. Benz, A. Hotho, and S. Gerd, “Evaluating Similarity Measures for Emergent Semantics of Social Tagging,” Proc. 18th Int’l Conf. World Wide Web (WWW), pp. 641-650, 2009.

C. Marlow, M. Naaman, D. Boyd, and M. Davis, “HT06, Tagging Paper, Taxonomy, Flickr, Academic Article, to Read,” Proc. 17th Conf. Hypertext and Hypermedia (HYPERTEXT), pp. 31-40, 2006.

B. Carminati, E. Ferrari, and A. Perego, “Combining Social Networks and Semantic Web Technologies for Personalizing Web Access,” Proc. Fourth Int’l Conf. Collaborative Computing: Networking, Applications and Worksharing, pp. 126-144, 2008.

J. Voß, “Tagging, Folksonomy & Co - Renaissance of Manual Indexing?” Computer Research Repository, vol. abs/cs/0701072, 2007.

G. Adomavicius and A. Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Trans. Knowledge Data Eng., vol. 17, no. 6, pp. 734-749, June 2005.

P. Heymann, D. Ramage, and H. Garcia-Molina, “Social Tag Prediction,” Proc. 31st Ann. Int’l ACM SIGIR Conf. Research Development Information Retrieval, pp. 531-538, 2008.

E. Frı´as-Martinez, M. Cebria´n, and A. Jaimes, “A Study on the Granularity of User Modeling for Tag Prediction,” Proc. IEEE/ WIC/ACM Int’l Conf. Web Intelligence Intelligent Agent Technology (WIIAT), pp. 828-831, 2008.

Z. Yun and F. Boqin, “Tag-Based User Modeling Using Formal Concept Analysis,” Proc. IEEE Eighth Int’l Conf. Computer Information Technology (CIT), pp. 485-490, 2008.

A. Shepitsen, J. Gemmell, B. Mobasher, and R. Burke, “Personalized Recommendation in Social Tagging Systems Using Hierarchical Clustering,” Proc. ACM Conf. Recommender Systems (RecSys), pp. 259-266, 2008.

M. Bundschus, S. Yu, V. Tresp, A. Rettinger, M. Dejori, and H.-P. Kriegel, “Hierarchical Bayesian Models for Collaborative Tagging Systems,” Proc. IEEE Int’l Conf. Data Mining (ICDM), pp. 728-733, 2009.

X. Li, C.G.M. Snoek, and M. Worring, “Learning Social Tag Relevance by Neighbor Voting,” IEEE Trans. Multimedia, vol. 11, no. 7, pp. 1310-1322, Nov. 2009.

S. Marti and H. Garcia-Molina, “Taxonomy of Trust: Categorizing P2P Reputation Systems,” Computer Networks, vol. 50, pp. 472-484, Mar. 2006.

K. Bischoff, C.S. Firan, W. Nejdl, and R. Paiu, “Can All Tags Be Used for Search?” Proc. 17th ACM Conf. Information and Knowledge Management (CIKM), pp. 193-202, 2008.

P. Heymann, G. Koutrika, and H. Garcia-Molina, “Can Social Bookmarking Improve Web Search?” Proc. Int’l Conf. Web SearchData Mining (WSDM), pp. 195-206, 2008.

http://www.dai-labor.de/en/competence_centers/irml/ datasets/. 2013.


Full Text: PDF

Refbacks

  • There are currently no refbacks.




Copyright © 2012 - 2021, All rights reserved.| ijitr.com

Creative Commons License
International Journal of Innovative Technology and Research is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJITR , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.