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- The user query is turned into an ElasticSearch query and applied across the cluster.
- The number of documents returned from ElasticSearch is capped at a "large" number (default 1000, eg 10x the documents to return). The documents are ordered by their Lucene score (or optionally just by descending date).
- Each returned document is then assigned a INF:Significance score as described below.
- The significance and relevance scores are then normalized against each other based on a relative importance specified by the user (default 2:1 in favor of significance) and combined, with the mean score set to 100 (like the "+" stats in baseball, eg 120 is 20% higher than average).
- (All three scores are attached to the documents, as "queryRelevance", "aggregateSignif", and "score" respectively)
- The top scoring documents or entities are returned to the client.
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"decay" is the "half life" of the decay (ie the duration from "time" at which the score is halved). It is in the format "N[INF:dmwy]" where N is an integer and d,m,w,y denote "day", "month", "week" or "year" (eg "1w", "1m"; note currently if "m" is used, then the duration is always 1 month).
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