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projects:swe:start [2015/05/29 15:15] hjprojects:swe:start [2015/09/22 01:20] (current) hj
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 into the popular data-driven learning process of word embeddings to improve the into the popular data-driven learning process of word embeddings to improve the
 quality of them. Under this framework, we represent semantic knowledge as many quality of them. Under this framework, we represent semantic knowledge as many
-ordinal ranking inequalities and formulate the learning of semantic word embeddings+**ordinal ranking inequalities** and formulate the learning of semantic word embeddings
 (SWE) as a constrained optimization problem, where the data-derived objective (SWE) as a constrained optimization problem, where the data-derived objective
 function is optimized subject to all ordinal knowledge inequality constraints function is optimized subject to all ordinal knowledge inequality constraints
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 **Project website:** **Project website:**
  
-  * Code and resource download at [[http://home.ustc.edu.cn/~quanliu/research-SWE.html|USTC]] +  * Code and resource download at [[http://home.ustc.edu.cn/~quanliu|USTC]]  or [[ https://github.com/iunderstand/SWE|GitHub site]]
-  [[ https://github.com/iunderstand/SWE|GitHub site]]+
    
  
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-[1] //Quan Liu, Hui Jiang, Si Wei, Zhen-Hua Ling and Yu Hu//, "Learning SemanticWord Embeddings based on Ordinal Knowledge Constraints," Proceedings of Proc. of The 53th Annual Meeting of the Association for Computational Linguistics (ACL 2015), July, 2015.  +[1] //Quan Liu, Hui Jiang, Si Wei, Zhen-Hua Ling and Yu Hu//, "Learning SemanticWord Embeddings based on Ordinal Knowledge Constraints," Proceedings of The 53th Annual Meeting of the Association for Computational Linguistics (ACL 2015), July, 2015. ([[https://aclweb.org/anthology/P/P15/P15-1145.pdf|here]]) 
  
projects/swe/start.1432912521.txt.gz · Last modified: 2015/05/29 15:15 by hj