“Hulan-2014-10-31”版本间的差异
来自cslt Wiki
第26行: | 第26行: | ||
:* test the boost keyword weight and extract the synonyms word. | :* test the boost keyword weight and extract the synonyms word. | ||
:* check the word segment for template. | :* check the word segment for template. | ||
− | :* min-segment method improve the accuracy. | + | :* min-segment method improve the accuracy.(0.61->0.66) |
:* check the query method for getting lucene information and to rewrite the score method like the idf value. | :* check the query method for getting lucene information and to rewrite the score method like the idf value. | ||
第34行: | 第34行: | ||
==knowledge structure== | ==knowledge structure== | ||
* structure the default answer using attributes of the entity. | * structure the default answer using attributes of the entity. | ||
+ | ==Knowledge Management and labeling system== | ||
+ | :* prepare the interface and function. | ||
==plan to discuss== | ==plan to discuss== |
2014年10月31日 (五) 05:02的版本
目录
Dialog system
Algorithm
Spell mistake
- using ngram to get candidate sentence.
improve lucene search
- lucene similarity method
method | Default | BM25 | LMDirichlet | DFR | LMJelinekMercer | IB |
---|---|---|---|---|---|---|
Accary | 0.66228 | 0.66228 | 0.4091 | 0.65476 | 0.65476 | 0.6666 |
- our vsm method
- our vsm method re-rank(54%),lucene(67%)
- lucene top50(caoli)
- top10(82.95%),top20(86.34),top50(90.22%)
- need to check the other 10% error
- lucene Optimization(liurong)
- rewrite the method to select the 50 standard question not same template.
- test the boost keyword weight and extract the synonyms word.
- check the word segment for template.
- min-segment method improve the accuracy.(0.61->0.66)
- check the query method for getting lucene information and to rewrite the score method like the idf value.
- IDF(caoli)
- test the different idf vale from baidu sougou in fuzzymatch.
- IDF from train-data performance bad than default IDF,from 0.63->0.69.
knowledge structure
- structure the default answer using attributes of the entity.
Knowledge Management and labeling system
- prepare the interface and function.