Difference between revisions of "Ling Luo 2015-08-31"

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(Works in this week:)
(Works in this week:)
 
Line 29: Line 29:
 
== Works in this week: ==
 
== Works in this week: ==
  
word similarity:
+
semantic&syntactic analogy:
 
try to use different similarity calculation methods  
 
try to use different similarity calculation methods  
  

Latest revision as of 02:24, 2 September 2015

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

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:

semantic&syntactic analogy: try to use different similarity calculation methods

named entity recognition

focus on cnn