Lucene的.Net和定製得分

Question

我有以下Lucene的說明：

{1.25 = (MATCH) sum of: 

    0.5 = (MATCH) weight(Caption:vrom^0.5 in 0) [MySimilarity], result of: 
    0.5 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.5 = queryWeight, product of: 
     0.5 = boost 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = queryNorm 
     1 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = fieldNorm(doc=0) 

    0.75 = (MATCH) weight(Caption:vroma^0.75 in 0) [MySimilarity], result of: 
    0.75 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.75 = queryWeight, product of: 
     0.75 = boost 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = queryNorm 
     1 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = fieldNorm(doc=0) 
} 

，我想，以過濾由他們的查詢重量匹配結果爲MAX匹配和不匹配的總和。

我需要做的是，從每個文檔中，我想採取在每個條款中給出的最高數字。 （在這個例子中，我想將0.75作爲匹配分數而不是1.25）。這是可能的，甚至是正確的嗎？

我到目前爲止所做的是創建一個相似性，以改變計算得分的方式，但是我仍然錯過了獲取MAX而不是SUM的部分。

我正在使用Lucene .Net版本4.8（測試版）。

預先感謝您！

Answer 1

不需要修改相似性來做到這一點。而不是布爾查詢，請使用DisjunctionMaxQuery。

Answer 2

感謝您的解決方案，但我仍然有一個問題。 當我試圖做到這一點時，我得到了和以前一樣的結果。我的代碼如下（從here我用的例子）：

BooleanQuery finalQuery = new BooleanQuery(); 
DisjunctionMaxQuery q1 = new DisjunctionMaxQuery(0.01f); 
Query query = new FuzzyQuery(new Term("Caption", "roma")); 
q1.Add(query); 
finalQuery.Add(q1, Occur.MUST); 

結果我得到的是（在相同的問題）：

{1.25 = (MATCH) sum of: 

    0.5 = (MATCH) weight(Caption:vrom^0.5 in 0) [MySimilarity], result of: 
    0.5 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.5 = queryWeight, product of: 
     0.5 = boost 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = queryNorm 
     1 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = fieldNorm(doc=0) 

    0.75 = (MATCH) weight(Caption:vroma^0.75 in 0) [MySimilarity], result of: 
    0.75 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.75 = queryWeight, product of: 
     0.75 = boost 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = queryNorm 
     1 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1 = idf(docFreq=1, maxDocs=4) 
     1 = fieldNorm(doc=0) 
} 

我試了一下，並沒有修改相似，但我也一樣。在這種情況下的結果是：

{0.505973 = (MATCH) sum of: 

    0.2023892 = (MATCH) weight(Caption:vrom^0.5 in 0) [DefaultSimilarity], result of: 
    0.2023892 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.3187582 = queryWeight, product of: 
     0.5 = boost 
     1.693147 = idf(docFreq=1, maxDocs=4) 
     0.3765274 = queryNorm 
     0.6349302 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1.693147 = idf(docFreq=1, maxDocs=4) 
     0.375 = fieldNorm(doc=0) 

    0.3035838 = (MATCH) weight(Caption:vroma^0.75 in 0) [DefaultSimilarity], result of: 
    0.3035838 = score(doc=0,freq=1 = termFreq=1 
), product of: 
     0.4781373 = queryWeight, product of: 
     0.75 = boost 
     1.693147 = idf(docFreq=1, maxDocs=4) 
     0.3765274 = queryNorm 
     0.6349302 = fieldWeight in 0, product of: 
     1 = tf(freq=1), with freq of: 
      1 = termFreq=1 
     1.693147 = idf(docFreq=1, maxDocs=4) 
     0.375 = fieldNorm(doc=0) 
}