Question

我有以下Lucene说明：

{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)
}

我希望通过查询权重过滤匹配结果作为MAX匹配，而不是匹配的总和。

我需要做的是，从每个文件中，我想采用每个条款中给出的最高数字。（在这个例子中，我想取0.75作为匹配分数而不是1.25）。这可能，甚至是正确的吗？

到目前为止，我所做的是创建一个相似度以改变分数的计算方式，但我仍然缺少获得MAX而不是SUM的部分。

我正在使用Lucene .Net版本4.8（测试版）。

提前谢谢！

Answer 1

无需修改相似性即可。使用DisjunctionMaxQuery。

代替布尔查询

Answer 2

感谢您的解决方案，但我仍有问题。当我尝试这样做时，我得到与以前相同的结果。我的代码如下（我使用了here中的示例）：

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);

我得到的结果（与问题中的相同）：

{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)
}

我尝试了它而没有修改相似性，但我有相同的。在这种情况下的结果是：

{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)
}

Lucene .Net，自定义评分

2 个答案: