“Ling Luo 2015-08-31”版本间的差异

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Works in this week:
第20行: 第20行:
 
== Works in this week: ==
 
== Works in this week: ==
  
word similarity(ws):try to use different similarity calculation method
+
word similarity(ws):
 +
try to use different similarity calculation method  
 +
 
 
named entity recognition(ner)
 
named entity recognition(ner)
 +
 
focus on cnn
 
focus on cnn

2015年9月2日 (三) 02:19的版本

Works in the past:

1.Finish training word embeddings via 5 models : using EnWiki dataset(953M): CBOW,Skip-Gram using text8 dataset(95.3M): CBOW,Skip-Gram,C&W,GloVe,LBL and Order(count-based)

2.Use tasks to measure quality of the word vectors with various dimensions(10~200): word similarity(ws) the TOEFL set:small dataset analogy task:9K semantic and 10.5K syntactic analogy questions text classification:IMDB dataset——pos&neg,use unlabeled dataset to train word embeddings sentence-level sentiment classification (based on convolutional neural networks) part-of-speech tagging


Works in this week:

word similarity(ws): try to use different similarity calculation method

named entity recognition(ner)

focus on cnn