About Related Terms

For example, your similar query probably looks like:

similar:(264 328 579 628 730 782 806 847 853 871 955 1064 1071 1073 1074 1134 1137 1177 1194 1270 1285 1362
 1390 1391 1474 1537 1539 1560 1579 1585)

This generates the following ELLQL query, which defines the similarity virtual field and assigns a weight to each keyword lookup according to its corpus frequency.

#query{nbdocs=934, score.expr="@term.score * @proximity + @b",
 similarity.expr="(#length(keyword) >= 5) * ((score >= 332925) * score / #sqrt(30* #length(keyword))) 
/ 0.083231266666667",
 proximity.maxDistance=1000,
 term.score=RANK_TFIDF}(#or(#num{b=53646}(keyword,==,264)
 #num{b=70688}(keyword,==,328) #num{b=75574}(keyword,==,579)
 #num{b=74506}(keyword,==,628) #num{b=34317}(keyword,==,730)
 #num{b=40264}(keyword,==,782) #num{b=107885}(keyword,==,806)
 #num{b=143583}(keyword,==,847) #num{b=76695}(keyword,==,853)
 #num{b=80417}(keyword,==,871) #num{b=60146}(keyword,==,955)
 #num{b=88194}(keyword,==,1064) #num{b=61715}(keyword,==,1071)
 #num{b=30021}(keyword,==,1073) #num{b=46950}(keyword,==,1074)
 #num{b=61715}(keyword,==,1134) #num{b=143583}(keyword,==,1137)
 #num{b=96514}(keyword,==,1177) #num{b=90061}(keyword,==,1194)
 #num{b=51783}(keyword,==,1270) #num{b=130086}(keyword,==,1285)
 #num{b=90061}(keyword,==,1362) #num{b=83255}(keyword,==,1390)
 #num{b=161950}(keyword,==,1391) #num{b=161950}(keyword,==,1474)
 #num{b=43783}(keyword,==,1537) #num{b=92059}(keyword,==,1539)
 #num{b=76695}(keyword,==,1560) #num{b=99010}(keyword,==,1579)
 #num{b=69832}(keyword,==,1585) ))