On 3/18/2016 6:34 AM, jimi.hulleg...@svensktnaringsliv.se wrote: > I'm not sure I follow your logic now. If one can express the popularity as a > value between 0.0 and 1.0, why can't one use that, together with a weight > (indicating how much the popularity should influence the score, in general) > and add that to the text relevance score? And how, exactly, would I achieve > that using any multiplicative formula? > > The logic of the weight, in this case, is that I want to be able to tweak how > much influence the popularity has on the final score (and thus the sort order > of the documents), where a weight of 0.0 would have the same effect as if the > popularity wasn't included in the boost logic at all, and a high enough > weight would have the same effect as if one sorted the documents solely on > popularity.
Restating Walter's point in a different way: The "max score" of a particular query can vary widely, and only has meaning within the context of that query. One query on an index might produce a max score of 0.944, so *every* document has a score less than one, while another query *on the same index* (that might even have some of the same result documents) might produce a max score of 12.7, so the top docs have a score *much* higher than one. If your additive boost is 5, this represents a relative boost of over 500 percent for the top docs of the first query I talked about above, but less than 50% for the top docs of the second. If you have a multiplicative boost of 1.5, then the relative boost for both queries is 150 percent. To use boosting successfully, you must have control of the *relative* effect you are producing. Multiplicative boosts *keep* things relative, additive boosting makes assumptions about the max score, and those assumptions may turn out to be completely wrong. Thanks, Shawn
