collaborative tagging :-by Er. Priyanka Pradhan
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The document summarizes techniques for improving collaborative tagging. It discusses tag suppression, tripartite clustering, and a proposed web-based social network (WBSN) architecture. The proposed techniques aim to address privacy and enhance functionality in collaborative tagging systems. Tripartite clustering simultaneously clusters resources, users, and tags using links in the social tagging network. The WBSN architecture incorporates a bookmarking service and additional services for tag suppression and privacy preservation to broaden collaborative tagging capabilities while preserving user privacy.
![8. REFERENCE
[1] Javier Parra-Arnau, Andrea Perego, Elena Ferrari, Jordi Forne, and
David Rebollo-Monedero, “Privacy-Preserving Enhanced Collaborative
Tagging” Proc. IEEE Transaction on Knowledge and Data Engineering,
vol. 26, no. 1, January 2014.
[2] Caimei Lu, Xiaohua Hu and Jung-ran Park, “Exploiting the Social Tagging
Network
For Web Clustering” Proc. IEEE Transactions on systems, man, and
Cybernetics—part a: systems and humans, vol. 41, no. 5, September 2011.
[3] 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
work sharing, pp. 126-144, 2008.
[4]J. Parra-Arnau, D. Rebollo-Monedero, and J. Forne´
, “A Privacy- Preserving Architecture for the Semantic Web Based on
Tag Suppression,” Proc. Seventh Int’l Conf. Trust, Privacy, Security,
Digital Business (Trust Bus), pp. 58-68, Aug. 2010.
10](https://image.slidesharecdn.com/paprppt-140613233807-phpapp02/85/collaborative-tagging-by-Er-Priyanka-Pradhan-10-320.jpg)
collaborative tagging :-by Er. Priyanka Pradhan
- 1. “Some Observation on Collaborative Tagging Techniques”: A Review 1
- 2. CONTENT 1. INTRODUCTION 2. COLLABORATIVE TAGGING 3. TECHNIQUIES USED 4. TAG SUPPRESION 5. TRIPARTTITE CLUSTERING 6. PROPOSED WBSN ARCHITECTURE 7. CONCLUSION 8. REFERENCE 2
- 3. 1. INTRODUCTION Social Tagging, also known as Social Annotation or Collaborative Tagging. Social annotation is one of the most diffused and popular services available online that allows users to annotate resources with free-form tags. The main purpose of social annotation is to loosely classify resources based on end-user’s feedback, expressed in the form of free- text labels (i.e., tags). 3
- 4. Collaborative tagging is one of the most diffused and popular services available online. First provided by social bookmarking sites only for example, Delicious (http://delicious.comby nearly any type of social web application, and it is used to annotate any kind of online and offline resources. 2. COLLABORATIVE TAGGING 4
- 5. 3. PROPOSED WORK Authors provided their proposed work for improving the many aspects of collaborative tagging. The Proposed techniques are: 1.Tag Suppression 2.Tripartite Clustering 3.Proposed WBSN Architecture 5
- 7. 5. TRIPARTTITE CLUSTERING “Tripartite Clustering” which clusters the three types of nodes (resources, users, and tags) simultaneously by only utilizing the links in the social tagging network. 7
- 8. The system we propose is based on a Web-based Social Network, where members are able not only to specify labels, but also to rate existing labels. Both labels and ratings are then used to assess the trustworthiness of resources’ descriptions and to enforce Web access personalization. 6. WBSN Proposed Architecture 8
- 9. 7. CONCLUSION The proposed techniques provided here are widely acceptable and improved the current scenario of social annotation. An architecture that incorporates two layers on support of enhanced and private collaborative tagging. More pecifically, the proposed architecture consists of a bookmarking service and two additional services built on it.The latter implements tag suppression, a privacy- Preserving technology based on data perturbation. The combination of these two services allows us then to broaden the functionality of collaborative tagging systems and, at the same time, provide users with a mechanism to preserve their privacy while tagging. 9
- 10. 8. REFERENCE [1] Javier Parra-Arnau, Andrea Perego, Elena Ferrari, Jordi Forne, and David Rebollo-Monedero, “Privacy-Preserving Enhanced Collaborative Tagging” Proc. IEEE Transaction on Knowledge and Data Engineering, vol. 26, no. 1, January 2014. [2] Caimei Lu, Xiaohua Hu and Jung-ran Park, “Exploiting the Social Tagging Network For Web Clustering” Proc. IEEE Transactions on systems, man, and Cybernetics—part a: systems and humans, vol. 41, no. 5, September 2011. [3] 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 work sharing, pp. 126-144, 2008. [4]J. Parra-Arnau, D. Rebollo-Monedero, and J. Forne´ , “A Privacy- Preserving Architecture for the Semantic Web Based on Tag Suppression,” Proc. Seventh Int’l Conf. Trust, Privacy, Security, Digital Business (Trust Bus), pp. 58-68, Aug. 2010. 10
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Editor's Notes
- #6: The tags posted by a user in a collaborative tagging service are frequently depicted as a tag cloud. This representation is equivalent to the model of user profile assumed. The tag cloud shown here is also represented as a PMF.