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The Scientific World Journal
Volume 2014 (2014), Article ID 832638, 10 pages
Research Article

Security Techniques for Prevention of Rank Manipulation in Social Tagging Services including Robotic Domains

1Department of Computer Engineering, Sejong University, Seoul 143-747, Republic of Korea
2Department of Knowledge Information Engineering, Graduate School of Ajou University, Suwon 443-749, Republic of Korea

Received 14 March 2014; Accepted 11 May 2014; Published 9 July 2014

Academic Editor: Sang-Soo Yeo

Copyright © 2014 Okkyung Choi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With smartphone distribution becoming common and robotic applications on the rise, social tagging services for various applications including robotic domains have advanced significantly. Though social tagging plays an important role when users are finding the exact information through web search, reliability and semantic relation between web contents and tags are not considered. Spams are making ill use of this aspect and put irrelevant tags deliberately on contents and induce users to advertise contents when they click items of search results. Therefore, this study proposes a detection method for tag-ranking manipulation to solve the problem of the existing methods which cannot guarantee the reliability of tagging. Similarity is measured for ranking the grade of registered tag on the contents, and weighted values of each tag are measured by means of synonym relevance, frequency, and semantic distances between tags. Lastly, experimental evaluation results are provided and its efficiency and accuracy are verified through them.