Multi query in multi field
来自cslt Wiki
目录
check the detail of Lucene score
data
d0 [{如何，怎么}} {办理，办} {户口，户口本} # 到当地派出所办理 # 如何办理户口
d1 {办理，办} {户口，户口本} [{流程，步骤}] # 到当地派出所办理 # 如何办理户口
d2 [{如何，怎么}} {办理，办} {身份证，身份} # 到当地派出所办理 # 如何办理身份证
d3 {办理，办} {身份证} [{流程，步骤}] # 到当地派出所办理 # 如何办理身份证
搜索
query:"如何办理户口" => question:如何 question:办理户口
result
doc=0 score=0.114656925 shardIndex=-1|0.114656925 = (MATCH) product of:
0.22931385 = (MATCH) sum of:
0.22931385 = (MATCH) weight(question:如何 in 0) [DefaultSimilarity], result of:
0.22931385 = score(doc=0,freq=1.0 = termFreq=1.0
), product of:
0.4748871 = queryWeight, product of:
1.287682 = idf(docFreq=2, maxDocs=4)
0.3687922 = queryNorm
0.48288077 = fieldWeight in 0, product of:
1.0 = tf(freq=1.0), with freq of:
1.0 = termFreq=1.0
1.287682 = idf(docFreq=2, maxDocs=4)
0.375 = fieldNorm(doc=0)
0.5 = coord(1/2)
- 详细计算流score(query,d0)
- 参考公式：[1]
- tf("如何" in d0)=sqrt{frequency}= sqrt{1}=1
- idf("如何")=<math>1+ln( {numDocs}/{docFreq+1})=1+ln( {4}/{2+1} )
- 如何".getboost=1
- coord(如何，d0) : 0.5 = coord(1/2)
coord(t,d)=overlap /maxOverlap . overlap - the number of query terms matched in the document maxOverlap - the total number of terms in the query
- queryNorm(q)= 1/sqrt(sumOfSquaredWeights)=1/sqrt(sum(idf("如何")*1+idf("办理户口")))=1/sqrt(1*(1.287682*1.287682+2.386*2.386))=0.3687.
sumOfSquaredWeights = q.getBoost()*q.getBoost()*∑( idf(t) *t.getBoost() )^2
mutli
data
d0 [{如何，怎么}} {办理，办} {户口，户口本} # 到当地派出所办理 # 如何办理户口
d1 {办理，办} {户口，户口本} [{流程，步骤}] # 到当地派出所办理 # 如何办理户口
d2 [{如何，怎么}} {办理，办} {身份证，身份} # 到当地派出所办理 # 如何办理身份证
d3 {办理，办} {身份证} [{流程，步骤}] # 到当地派出所办理 # 如何办理身份证
搜索
code
BooleanQuery query = new BooleanQuery(); query.add(paternQuery, Occur.MUST); // or Occur.SHOULD if this clause is optional query.add(ansQuery, Occur.SHOULD); // or Occur.MUST if this clause is required query.add(sqQuery, Occur.SHOULD);
search:
+((question:如何 question:办理户口)^0.8) ((answer:如何 answer:办理户口)^0.2) ((standardq:如何 standardq:办理户口)^0.2)
result
- 计算公式
- score(Q)=score(q_PTN)+score(q_ANS)+score(q_STD)
- querynorm(Q),Q=q_PTN+q_ANS+q_STD
- sumOfSquaredWeights = ∑{q.getBoost()*q.getBoost()*∑( idf(t) *t.getBoost() )^2},q={q_PTN , q_STD, q_ANS}
- queryNorm(Q)= 1/sqrt(sumOfSquaredWeights)
- field patern
- tf("如何" in d0)=sqrt{frequency}= sqrt{1}=1
- idf("如何")=<math>1+ln( {numDocs}/{docFreq+1})=1+ln( {4}/{2+1} )
- 如何".getboost=1
- coord(如何，d0) : 0.5 = coord(1/2)
coord(t,d)=overlap /maxOverlap . overlap - the number of query terms matched in the document maxOverlap - the total number of terms in the query
- queryNorm(q_PTN)=querynorm(Q)*boost(q_PTN)
- Norm
- detail
- filed: answer+pattern
score(q,filed-pattern)+score(q,filed-answer)
doc=0 score=0.15459718 shardIndex=-1|0.1545972 = (MATCH) product of:
0.23189577 = (MATCH) sum of:[all]
0.108532876 = (MATCH) product of:[filed:pattern]
0.21706575 = (MATCH) sum of:
0.21706575 = (MATCH) weight(question:如何 in 0) [DefaultSimilarity], result of:
0.21706575 = score(doc=0,freq=1.0 = termFreq=1.0
), product of:
0.44952247 = queryWeight, product of:
1.287682 = idf(docFreq=2, maxDocs=4)
0.3490943 = queryNorm
0.48288077 = fieldWeight in 0, product of:
1.0 = tf(freq=1.0), with freq of:
1.0 = termFreq=1.0
1.287682 = idf(docFreq=2, maxDocs=4)
0.375 = fieldNorm(doc=0)
0.5 = coord(1/2)
0.12336289 = (MATCH) sum of:[field:answer]
0.032918826 = (MATCH) weight(answer:如何 in 0) [DefaultSimilarity], result of:
0.032918826 = score(doc=0,freq=1.0 = termFreq=1.0
), product of:
0.06779904 = queryWeight, product of:
0.7768564 = idf(docFreq=4, maxDocs=4)
0.087273575 = queryNorm
0.48553526 = fieldWeight in 0, product of:
1.0 = tf(freq=1.0), with freq of:
1.0 = termFreq=1.0
0.7768564 = idf(docFreq=4, maxDocs=4)
0.625 = fieldNorm(doc=0)
0.090444066 = (MATCH) weight(answer:办理户口 in 0) [DefaultSimilarity], result of:
0.090444066 = score(doc=0,freq=1.0 = termFreq=1.0
), product of:
0.11238062 = queryWeight, product of:
1.287682 = idf(docFreq=2, maxDocs=4)
0.087273575 = queryNorm
0.8048013 = fieldWeight in 0, product of:
1.0 = tf(freq=1.0), with freq of:
1.0 = termFreq=1.0
1.287682 = idf(docFreq=2, maxDocs=4)
0.625 = fieldNorm(doc=0)
0.6666667 = coord(2/3)
