Ahhhh...I brushed over your example too fast...looked like normal
counting to me...I see now what you mean. So OMIT_NORMS probably did
work. Are you getting the results through hits? Hits will normalize. Use
topdocs or a hitcollector.
- Mark
Vagelis Kotsonis wrote:
But i don't want to get the frequency of each term in the doc.
what I want is 1 if the term exists in the doc and 0 if it doesn't. After
this, I want all thes 1s and 0s to be summed and give me a number to use as
a score.
If I set the TF value as 1 or 0, as I described above, I get the right
number, but this number is normalized to 1.0 and smaller numbers.
It is the normalization that I want to avoid.
Thanks again!
Vagelis
markrmiller wrote:
Dont return 1 for tf...just return the tf straight with no
changes...return freq. For everything else return 1. After that
OMIT_NORMS should work. If you want to try a custom reader:
public class FakeNormsIndexReader extends FilterIndexReader {
byte[] ones = SegmentReader.createFakeNorms(maxDoc());
public FakeNormsIndexReader(IndexReader in) {
super(in);
}
public synchronized byte[] norms(String field) throws IOException {
System.out.println("returning fake norms...");
return ones;
}
public synchronized void norms(String field, byte[] result, int
offset) {
System.out.println("writing fake norms...");
System.arraycopy(ones, 0, result, offset, maxDoc());
}
}
The beauty of this reader is that you can flip between it and your
custom similarity and Lucene's default implementations live on the same
index.
- Mark
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