“Xingchao work”版本间的差异
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Pre-process corpus, remove the sentence which contains rarely seen words. | Pre-process corpus, remove the sentence which contains rarely seen words. | ||
| − | + | Start at : 2014-09-30 <--> End at : 2014-10-02 <--> Result : | |
| + | Original lines is 8973724, Clean corpus (remove sentences which contain words less than 10) is 6415723 | ||
| + | Train Model. | ||
| + | Start at : 2014-10-02 | ||
2014年10月2日 (四) 09:23的版本
目录
Paper Recommendation
Pre-Trained Multi-View Word Embedding.[1]
Learning Word Representation Considering Proximity and Ambiguity.[2]
Continuous Distributed Representations of Words as Input of LSTM Network Language Model.[3]
WikiRelate! Computing Semantic Relatedness Using Wikipedia.[4]
Japanese-Spanish Thesaurus Construction Using English as a Pivot[5]
Chaos Work
SSA Model
Build 2-dimension SSA-Model. Start at : 2014-09-30 <--> End at : 2014-10-02 Test 25,50-dimension SSA-Model for transform Start at : 2014-10-02 Test All-Belong SSA model for transform Start at : 2014-10-02
SEMPRE Research
Work Schedule
Download SEMPRE toolkit. Start at : 2014-09-30
Semantic Parsing via Paraphrasing [6]
Knowledge Vector
Pre-process corpus. Start at : 2014-09-30
Moses translation model
Pre-process corpus, remove the sentence which contains rarely seen words.
Start at : 2014-09-30 <--> End at : 2014-10-02 <--> Result :
Original lines is 8973724, Clean corpus (remove sentences which contain words less than 10) is 6415723
Train Model.
Start at : 2014-10-02
Non Linear Transform Testing
Work Schedule
Re-train best mse for test data. Start at : 2014-10-01 <--> End at : 2014-10-02 <--> Result : Performance is inconsistent to expectations. Best result for Non-Linear is 1e-2.
