A semantic clustering-based approach for searching and browsing tag spaces
Proceedings of the 2011 ACM Symposium on Applied Computing
A local information passing clustering algorithm for tagging systems
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Improving the exploration of tag spaces using automated tag clustering
ICWE'11 Proceedings of the 11th international conference on Web engineering
On kernel information propagation for tag clustering in social annotation systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Mining tag similarity in folksonomies
Proceedings of the 3rd international workshop on Search and mining user-generated contents
APPECT: an approximate backbone-based clustering algorithm for tags
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Methodologies for improved tag cloud generation with clustering
ICWE'12 Proceedings of the 12th international conference on Web Engineering
| Hi-index | 0.00 |
Many of the existing cloud tagging systems are unable to cope with the syntactic and semantic tag variations during user search and browse activities. As a solution to this problem, we propose the Semantic Tag Clustering Search, a framework which is able to cope with these needs. The framework consists of two parts: removing syntactic variations and creating semantic clusters. For removing syntactic variations, we use the normalized Levenshtein distance and the cosine similarity measure based on tag co-occurrences. For creating semantic clusters, we improve an existing non-hierarchical clustering technique. Using our framework, we are able to find more clusters and achieve a higher precision than the original method.