Hierarchical tag visualization and application for tag recommendations

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2011, Pages 1331-1340

  Song, Yang ^a   Qiu, Baojun ^b   Farooq, Umer ^c  

^a MICROSOFT RESEARCH   (United States)

^b The Pennsylvania State University   (United States)

^c MICROSOFT   (United States)

Author keywords

hierarchical tag visualization; minimum evolution criteria; tag recommendation

Indexed keywords

CONTENT-BASED METHODS; GREEDY ALGORITHMS; MINIMUM EVOLUTION; RANKING METHODS; RECOMMENDATION ALGORITHMS; RELATIVE FREQUENCIES; SOCIAL BOOKMARKING; STRUCTURE-BASED; TAG RECOMMENDATION; TREE STRUCTURES; USER STUDY;

ALGORITHMS; CLOUDS; FORESTRY; KNOWLEDGE MANAGEMENT; TAXONOMIES; VISUALIZATION;

TREES (MATHEMATICS);

ALGORITHMS; BOOK MARKS; COMPUTER PROGRAMS; FORESTRY; PROBLEM SOLVING;

EID: 83055179412     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2063576.2063769     Document Type: Conference Paper

References (18)

1. A. Barron, J. Rissanen, and B. Yu. The minimum description length principle in coding and modeling (invited paper). pages 699-716, 2000.
2. G. Begelman. Automated tag clustering: Improving search and exploration in the tag space. In In Proc. of the Collaborative Web Tagging Workshop at WWW̌S06, 2006.
3. P. A. Chirita, S. Costache, W. Nejdl, and S. Handschuh. P-tag: large scale automatic generation of personalized annotation tags for the web. In WWW '07, pages 845-854.
4. P. Cimiano, A. Hotho, and S. Staab. Learning concept hierarchies from text corpora using formal concept analysis. Journal of Artificial Intelligence research, 24:305-339, 2005. (Pubitemid 43130939)
5. P. De Meo, G. Quattrone, and D. Ursino. Exploitation of semantic relationships and hierarchical data structures to support a user in his annotation and browsing activities in folksonomies. Inf. Syst., 34(6):511-535, 2009.
6. R. Desper and O. Gascuel. Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. Journal of Computational Biology, 9(5):687-705.
7. M. Dubinko, R. Kumar, J. Magnani, J. Novak, P. Raghavan, and A. Tomkins. Visualizing tags over time. In WWW '06, pages 193-202, New York, NY, USA, 2006.
8. S. A. Golder and B. A. Huberman. Usage patterns of collaborative tagging systems. J. Inf. Sci., 32(2):198-208, 2006.
9. Y. Hassan-montero and V. H. solana A. Improving tag-clouds as visual information retrieval interfaces. In Merída, InSciT2006 conference, 2006.
10. P. Heymann and H. Garcia-Molina. Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical Report 2006-10, April 2006.
11. P. Heymann, D. Ramage, and H. Garcia-Molina. Social tag prediction. In SIGIR '08, pages 531-538, 2008.
12. A. Hotho, R. Jäschke, C. Schmitz, and G. Stumme. Folkrank: A ranking algorithm for folksonomies. In University of Hildesheim, Institute of Computer Science, pages 111-114, 2006.
13. D. Liu, X.-S. Hua, L. Yang, M. Wang, and H.-J. Zhang. Tag ranking. In WWW '09, pages 351-360, 2009.
14. T.-Y. Liu. Learning to rank for information retrieval. pages 225-331, 2009.
15. B. Markines, C. Cattuto, F. Menczer, D. Benz, A. Hotho, and G. Stumme. Evaluating similarity measures for emergent semantics of social tagging. In WWW '09, pages 641-650, New York, NY, USA, 2009. ACM.
16. Y. Song, Z. Zhuang, H. Li, Q. Zhao, J. Li, W.-C. Lee, and C. L. Giles. Real-time automatic tag recommendation. In SIGIR '08, pages 515-522, New York, NY, USA, 2008.
17. M. Toomim, S. M. Drucker, M. Dontcheva, A. Rahimi, B. Thomson, and J. A. Landay. Attaching ui enhancements to websites with end users. In CHI '09, pages 1859-1868.
18. H. Yang and J. Callan. Metric-based ontology learning. In ONISW '08, pages 1-8. ACM, 2008.