“Search method”版本间的差异

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our method
Lr讨论 | 贡献
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* add boost keyword
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== boost keyword ==
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* boost the query keyword using IDF
 
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|+ boost keyword  in lucene
 
|+ boost keyword  in lucene
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* TFIDF Formula
 
* TFIDF Formula
 
:* coord(q,d)*query_boost*query_norm*sum(idf^2 * tf * term_boost * norm(t,d)) [http://lucene.apache.org/core/4_3_0/core/org/apache/lucene/search/similarities/TFIDFSimilarity.html]
 
:* coord(q,d)*query_boost*query_norm*sum(idf^2 * tf * term_boost * norm(t,d)) [http://lucene.apache.org/core/4_3_0/core/org/apache/lucene/search/similarities/TFIDFSimilarity.html]
  
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* add the new keyword value from proMe method
 
==our method==
 
==our method==
 
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2014年11月5日 (三) 15:05的版本

lucene method

  • data set
  • jiangkaipeng:
  • different method result
different result in lucene
method Default BM25 LMDirichlet DFR LMJelinekMercer IB
Accary 0.66228 0.66228 0.4091 0.65476 0.65476 0.6666

boost keyword

  • boost the query keyword using IDF
boost keyword in lucene
method Default idf_train idf_train_norm idf_baidu idf_baidu_norm
Accary 0.66228 0.651629 0.57644 0.647869 0.65288
  • TFIDF Formula
  • coord(q,d)*query_boost*query_norm*sum(idf^2 * tf * term_boost * norm(t,d)) [1]
  • add the new keyword value from proMe method

our method

different result in lucene
method lucene vsm_idf(haiguan) VSM_idf(baidu) vsm_idf(tain) vsm_idf(calculate)
Accary 0.6628 0.6228 0.6197 0.5827 0.5426

synonyms method

  • fuzzy match
  • calculate the similarity value = 1/(5-5*av_value).where av_value = average(word2vec+Synonyms forest+hownet).
  • lucene
  • lucene4.6 already added synonyms method (org.apache.lucene.analysis.synonym[2]) like :(a -> x) (a b -> y) (b c d -> z) or extend the query.

find

  • 采用最细粒度分词(对于标准问题在建立索引时,模板不用),可以提高正确率。61=>66.对于标准问题建索引时.
  • 对输入的问题不应用细粒度分词(细粒度的59%,不用66%)。
  • lucene4.6 已经增加了同义词拓展[3]