Advanced Uses of FIRST
How FIRST proceed to Differential Statistic Analysis
Users’ Jargon Generation (Jargon atoms and Jargon Agreggates)


This is a registered procedure of Intag, the proprietors of DARWIN and FIRST. In essence it’s equivalent to a data mining algorithm but instead of working with millions of “ex post” transactions it works on a differential strategy processing transactions at the right moment they are generated. In each user session we may distinguish two kinds of events: inquiries and “instances”. An inquiry is made by pairs (keyword, subject) and instances represent all possible navigation circumstances. So the first step is to split the session in two strings, one for the sequence of queries and other for the sequence of instances.

In the figure below we present the n-ads generation from queries strings. An n-ad is a set of n k’s, which are pairs (keywords, subject). In some extent these strings are like “Tarzan conversations” with a virtual Oracle, but anyhow conversations!. With clever users these conversations are extremely efficient in terms of searching convergence. For instance in the figure, the first session becomes [k k k k], a sequence of four queries that splits in four monads (1-ads) k k k k, six dyads (2-ads) kk kk kk kk kk kk, and three triads (3-ads) kkk kkk kkk.





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