Essentially what I am trying to do is boost every document by a certain factor, so that the boost is between 1.0 and 2.0. After this, I we are trying to do a search across multiple fields and have a computation based purely on tf. Example - if (field1) tf = some function else if (field2) tf = some other function ...
Now the boost is getting rounded to 1.0, 1.25, 1.5 or 2.0 due to the norm is stored, whereas I want more precision (e.g. 1.31, 1.45 etc). The boost is used for ranking documents. Thanks. Chris Hostetter wrote: > > > : Thanks Hoss. Suppose, I go ahead and modify Similarity.java from > ... > : Should this work ? > > it depends on your definition of "work" ... if that code is what you want > it to do, then yes: it will do what you want it to do. > > : P.S. This is a very custom implementation. For the specific problem that > I > : have, the lengthNorm > : is set to 1 (independent of numTerms). > > if your length norm is always 1, why do you care what the norm values are? > are you using document and field boosts? ... if "no" then none of this > shoudl matter. if "yes" then why not just change the boost values you use > to get the behavior you want instead of modifying the encoding mechanism? > > > > > -Hoss > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [EMAIL PROTECTED] > For additional commands, e-mail: [EMAIL PROTECTED] > > > -- View this message in context: http://www.nabble.com/Modifying-norms...-tf3671499.html#a10263146 Sent from the Lucene - Java Users mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
