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====== Conference Papers (Refereed) ======
^ As of 2008/9 ^ **Rank 1**\\ (Top Tier) ^ **Rank 2**\\ (Second Tier) ^ **Rank 3**\\ (Third Tier) ^
| [[http://www.cs.ualberta.ca/~zaiane/htmldocs/ConfRanking.html|CS Conference Rankings I]] | AAAI, CVPR, ICDM, ICML, \\ IJCAI, KDD, NIPS, SIGIR, WWW | CIKM, ICDAR, ICME, ICPR, ICWS, IJCNN, PAKDD | ICONIP |
| [[http://dsl.serc.iisc.ernet.in/publications/CS_ConfRank.htm|CS Conference Ranking II]] | AAAI, CVPR, ICML, IJCAI, \\ KDD, NIPS, SIGIR, WWW | CIKM, ICDAR, ICPR, IJCNN | ICDM, ICME, ICONIP, PAKDD |
| [[http://www3.ntu.edu.sg/home/ASSourav/crank.htm|CS Conference Ranking III]] | AAAI, CIKM, CVPR, ICML, \\ IJCAI, KDD, NIPS, SIGIR, WWW | ICDAR, ICME, ICDM, IJCNN, WIC | ICONIP, PAKDD |
| [[http://cs.conference-ranking.net/Artificial_Intelligence_Conference_Ranking.html|CS Conference Ranking IV (AI, CS, DM, IC)]] | AAAI, IJCAI, ICML, ICDM, \\ KDD, NIPS, WWW | | |
| [[http://www.cs-conference-ranking.org/conferencerankings/alltopics.html|CS Conference Ranking V (All topics)]] | KDD (0.99), ICDE (0.98), NIPS (0.98), SIGIR (0.96), CVPR (0.96), IJCAI (0.96), ICML (0.95),\\ WWW (0.92), CIKM (0.90),\\ ICDM (0.87), WIC (0.82), IJCNN (0.76), ICDAR (0.75), PAKDD (0.64), ICONIP (0.56) | | |
* **2012**: AAAI (2), WWW cQA Workshop (2)
* **2011**: AAAI (1), CIKM (2+2), CPSCom (1), ICONIP (2), IJCNN (1), SIGIR (1+1), SocialCom (1), WSDM (2)
* **2010**: AAAI (3), CIKM (2), ICML (2), ICONIP (3), IJCNN (2), SLT (4), Others (1)
* ML = Machine Learning, Neural Networks, Computational Intelligence, etc.
* SC = Social Computing, Recommender Systems, etc.
* IR = Information Retrieval, Text Processing, etc.
* WI = Web Intelligence, Web Mining, Link Analysis, etc.
* MM = Multimedia, Computer Vision, Image Processing, etc.
/*
[ ML | SC | IR | WI | MM ]
*/
\\ ---- 2012 ----
-
**(AR: 294/1129, 26%)** [ ML | SC | WI ]
**(AR: 294/1129, 26%)** [ ML | SC | WI ]
**(AR: XXX/XXX (XX %))** [ ML | SC | WI ]
**(AR: XXX/XXX (XX %))** [ ML | SC | WI ]
**(AR: XXX/XXX (XX %))** [ ML | SC | WI ]
**(AR: XXX/XXX (XX %))** [ ML | MM ]
**(AR: XXX/XXX (XX %))** [ ML | WI ]
**(AR: 138/917 (15 %))** [ ML | SC | WI ]
**(AR: 138/917 (15 %))** [ ML | SC | WI ]
**(AR: XX (XX%))** [ ML | SC | WI ]
**(AR: XX (XX%))** [ ML | SC | WI ]
**(AR: XX/XX (XX%))** [ SC | WI ]
**(AR: XX/XX (XX%))** [ SC | WI ]
**(AR: XX/XX (XX%))** [ SC | WI ]
**(AR: 242/975 (24.8%))** [ ML | SC | WI ]
**(AR: XX (XX%))** [ ML | SC | WI ]
**(AR: XX (XX%))** [ ML | SC | WI ]
**(AR: 32/372 (8.6%))** [ ML | SC | WI ]
**(AR: 83/372 (22.3%))** [ ML | SC | WI ]
**(AR: XXX/XXX (XXX%))** [ ML | SC | WI ]
**(AR: XXX/XXX (XXX%))** [ ML | SC | WI ]
**(AR: XXX/XXX (XXX%))** [ ML | SC | WI ]
**(AR: XXX/XXX (XXX%))** [ ML | SC ]
**(AR: XXX/XXX (XXX%))** [ ML ]
**(AR: XXX/XXX (XXX%))** [ ML | SC | WI ]
**(AR: 169/945 (17.9%))** [ ML ]
**(AR: 169/945 (17.9%))** [ SC | WI ]
**(AR: 99/954 (10.4%))** [ ML ]
**(AR: XXX/XXX (XXX%))** [ ML ]
**(AR: XXX/XXX (XXX%))** [ ML | SC | WI ]
**(AR: 264/982 (26.9%))** [ ML | SC | WI ]
**(AR: 264/982 (26.9%))** [ ML ]
**(AR: 264/982 (26.9%))** [ ML | SC | WI ]
**(AR: 152/594 (25.5%))** [ ML ]
**(AR: 152/594 (25.5%))** [ ML ]