0
欲計算其中具有3個不同的字段每一個文檔的文檔集合(filed1,FIELD2,字段3)計算平均文檔長度使用Lucene
這是計算平均長度時只有一個字段是程序平均文檔長度那裏。
private byte[] normsDocLengthArr = null;
private double avgDocLength;
normsDocLengthArr = indexReader.norms("filed1");
//norms-Returns the byte-encoded normalization factor for the named field of every document.
double sumLength = 0;
for (int i = 0; i < normsDocLengthArr.length; i++) {
double encodeLength = DefaultSimilarity.decodeNorm(normsDocLengthArr[i]);
//decodeNorm -Decodes a normalization factor stored in an index.
double length = 1/(encodeLength * encodeLength);
sumLength += length;
}
this.avgDocLength = sumLength/normsDocLengthArr.length;
這就是我如何擴展它的所有3個領域。
private byte[] normsDocLengthArrField1 = null;
private byte[] normsDocLengthArrField2 = null;
private byte[] normsDocLengthArrField3 = null;
private double avgDocLength;
normsDocLengthArrField1 = indexReader.norms("filed1");
normsDocLengthArrField2 = indexReader.norms("filed2");
normsDocLengthArrField3 = indexReader.norms("filed3");
//norms-Returns the byte-encoded normalization factor for the named field of every document.
double sumLength = 0;
for (int i = 0; i < normsDocLengthArrField1.length; i++) {
double encodeLengthF1 = DefaultSimilarity.decodeNorm(normsDocLengthArrField1[i]);
double encodeLengthF2 = DefaultSimilarity.decodeNorm(normsDocLengthArrField2[i]);
double encodeLengthF3 = DefaultSimilarity.decodeNorm(normsDocLengthArrField3[i]);
//decodeNorm -Decodes a normalization factor stored in an index.
double length = 1/{(encodeLengthF1 * encodeLengthF1)+(encodeLengthF2 * encodeLengthF2)+(encodeLengthF3 * encodeLengthF3)};
sumLength += length;
}
this.avgDocLength = sumLength/(normsDocLengthArrField1.length+ normsDocLengthArrField2.length+normsDocLengthArrField3.length;
我只是想知道我的實現計算3場督平均長度是否正確?