solr 评分 - fieldnorm [英] solr scoring - fieldnorm
问题描述
当我搜索iphone"时，我有以下记录和分数 -
I have the following records and the scores against it when I search for "iphone" -
记录1:字段名称 - 显示名称:iPhone"字段名称 - 名称:Iphone"
Record1: FieldName - DisplayName : "Iphone" FieldName - Name : "Iphone"
11.654595 = (MATCH) sum of:
11.654595 = (MATCH) max plus 0.01 times others of:
7.718274 = (MATCH) weight(DisplayName:iphone^10.0 in 915195), product of:
0.6654692 = queryWeight(DisplayName:iphone^10.0), product of:
10.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
11.598244 = (MATCH) fieldWeight(DisplayName:iphone in 915195), product of:
1.0 = tf(termFreq(DisplayName:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
1.0 = fieldNorm(field=DisplayName, doc=915195)
11.577413 = (MATCH) weight(Name:iphone^15.0 in 915195), product of:
0.99820393 = queryWeight(Name:iphone^15.0), product of:
15.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
11.598244 = (MATCH) fieldWeight(Name:iphone in 915195), product of:
1.0 = tf(termFreq(Name:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
1.0 = fieldNorm(field=Name, doc=915195)
记录2:字段名称 - 显示名称:Iphone Book"字段名称 - 名称:Iphone Book"
Record2: FieldName - DisplayName : "The Iphone Book" FieldName - Name : "The Iphone Book"
7.284122 = (MATCH) sum of:
7.284122 = (MATCH) max plus 0.01 times others of:
4.823921 = (MATCH) weight(DisplayName:iphone^10.0 in 453681), product of:
0.6654692 = queryWeight(DisplayName:iphone^10.0), product of:
10.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
7.2489023 = (MATCH) fieldWeight(DisplayName:iphone in 453681), product of:
1.0 = tf(termFreq(DisplayName:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.625 = fieldNorm(field=DisplayName, doc=453681)
7.2358828 = (MATCH) weight(Name:iphone^15.0 in 453681), product of:
0.99820393 = queryWeight(Name:iphone^15.0), product of:
15.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
7.2489023 = (MATCH) fieldWeight(Name:iphone in 453681), product of:
1.0 = tf(termFreq(Name:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.625 = fieldNorm(field=Name, doc=453681)
记录3:字段名称 - 显示名称:iPhone"字段名称 - 名称:iPhone"
Record3: FieldName - DisplayName: "iPhone" FieldName - Name: "iPhone"
7.284122 = (MATCH) sum of:
7.284122 = (MATCH) max plus 0.01 times others of:
4.823921 = (MATCH) weight(DisplayName:iphone^10.0 in 5737775), product of:
0.6654692 = queryWeight(DisplayName:iphone^10.0), product of:
10.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
7.2489023 = (MATCH) fieldWeight(DisplayName:iphone in 5737775), product of:
1.0 = tf(termFreq(DisplayName:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.625 = fieldNorm(field=DisplayName, doc=5737775)
7.2358828 = (MATCH) weight(Name:iphone^15.0 in 5737775), product of:
0.99820393 = queryWeight(Name:iphone^15.0), product of:
15.0 = boost
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.0057376726 = queryNorm
7.2489023 = (MATCH) fieldWeight(Name:iphone in 5737775), product of:
1.0 = tf(termFreq(Name:iphone)=1)
11.598244 = idf(docFreq=484, maxDocs=19431244)
0.625 = fieldNorm(field=Name, doc=5737775)
当record2有3个单词而record3只有一个单词时，为什么Record2和Record3得分相同.所以Record3应该比record 2具有更高的相关性.为什么Record2和Record3的fieldNorm是一样的?
Why is Record2 and Record3 have the same score when record2 has 3 words and record3 has just one word. So Record3 should have higher relevancy than record 2. Why are the fieldNorm of both Record2 and Record3 the same?
QueryParser:DismaxFieldType:solrconfig.xml 中默认的文本字段类型
QueryParser: Dismax FieldType: text fieldtype as default in solrconfig.xml
添加数据馈送:
记录 1:iPhone
Record1: Iphone
{
"ListPrice":1184.526,
"ShipsTo":1,
"OID":"190502",
"EAN":"9780596804299",
"ISBN":"0596804296",
"Author":"Pogue, David",
"product_type_fq":"Books",
"ShipmentDurationDays":"21",
"CurrencyValue":"24.9900",
"ShipmentDurationText":"NORMALLY SHIPS IN 21 BUSINESS DAYS",
"Availability":0,
"COD":0,
"PublicationDate":"2009-08-07 00:00:00.0",
"Discount":"25",
"SubCategory_fq":"Hardware",
"Binding":"Paperback",
"Category_fq":"Non Classifiable",
"ShippingCharges":"0",
"OIDType":8,
"Pages":"397",
"CallOrder":"0",
"TrackInventory":"Ingram",
"Author_fq":"Pogue, David",
"DisplayName":"Iphone",
"url":"/iphone-pogue-david/books/9780596804299.htm",
"CurrencyType":"USD",
"SubSubCategory":"Handheld Devices",
"Mask":0,
"Publisher":"Oreilly & Associates Inc",
"Name":"Iphone",
"Language":"English",
"DisplayPriority":"999",
"rowid":"books_9780596804299"
}
Record2:Iphone Book
Record2: The Iphone Book
{
"ListPrice":1184.526,
"ShipsTo":1,
"OID":"94694",
"EAN":"9780321534101",
"ISBN":"0321534107",
"Author":"Kelby, Scott/ White, Terry",
"product_type_fq":"Books",
"ShipmentDurationDays":"21",
"CurrencyValue":"24.9900",
"ShipmentDurationText":"NORMALLY SHIPS IN 21 BUSINESS DAYS",
"Availability":1,
"COD":0,
"PublicationDate":"2007-08-13 00:00:00.0",
"Discount":"25",
"SubCategory_fq":"Handheld Devices",
"Binding":"Paperback",
"BAMcategory_src":"Computers",
"Category_fq":"Computers",
"ShippingCharges":"0",
"OIDType":8,
"Pages":"219",
"CallOrder":"0",
"TrackInventory":"Ingram",
"Author_fq":"Kelby, Scott/ White, Terry",
"DisplayName":"The Iphone Book",
"url":"/iphone-book-kelby-scott-white-terry/books/9780321534101.htm",
"CurrencyType":"USD",
"SubSubCategory":" Handheld Devices",
"BAMcategory_fq":"Computers",
"Mask":0,
"Publisher":"Pearson P T R",
"Name":"The Iphone Book",
"Language":"English",
"DisplayPriority":"999",
"rowid":"books_9780321534101"
}
记录 3:iPhone
Record 3: iPhone
{
"ListPrice":278.46,
"ShipsTo":1,
"OID":"694715",
"EAN":"9781411423527",
"ISBN":"1411423526",
"Author":"Quamut (COR)",
"product_type_fq":"Books",
"ShipmentDurationDays":"21",
"CurrencyValue":"5.9500",
"ShipmentDurationText":"NORMALLY SHIPS IN 21 BUSINESS DAYS",
"Availability":0,
"COD":0,
"PublicationDate":"2010-08-03 00:00:00.0",
"Discount":"25",
"SubCategory_fq":"Hardware",
"Binding":"Paperback",
"Category_fq":"Non Classifiable",
"ShippingCharges":"0",
"OIDType":8,
"CallOrder":"0",
"TrackInventory":"BNT",
"Author_fq":"Quamut (COR)",
"DisplayName":"iPhone",
"url":"/iphone-quamut-cor/books/9781411423527.htm",
"CurrencyType":"USD",
"SubSubCategory":"Handheld Devices",
"Mask":0,
"Publisher":"Sterling Pub Co Inc",
"Name":"iPhone",
"Language":"English",
"DisplayPriority":"999",
"rowid":"books_9781411423527"
}
推荐答案
fieldnorm 考虑了字段长度，即术语的数量.
使用的字段类型是字段显示名称的文本 &名称，其中包含停用词和单词分隔符过滤器.
fieldnorm takes into account the field length i.e. the number of terms.
The fieldtype used is text for the fields display name & name, which would have the stopwords and the word delimiter filters.
记录 1 - Iphone
将生成单个令牌 - IPhone
记录 2 - Iphone Book
将生成 2 个令牌 - Iphone, Book
将被停用词删除.
Record 2 - The Iphone Book
Would generate 2 tokens - Iphone, Book
The would be removed by the stopwords.
记录 3 - iPhone
还将生成 2 个令牌 - i,phone
由于 iPhone 有大小写更改，带有 splitOnCaseChange 的单词分隔符过滤器现在会将 iPhone 拆分为 2 个标记 i，Phone 并生成与 Record 2 相同的字段规范
Record 3 - iPhone
Would also generate 2 tokens - i,phone
As iPhone has a case change, the word delimiter filter with splitOnCaseChange would now split iPhone into 2 tokens i, Phone and would produce the field norm same as Record 2
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