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The Transition Point (TP) is a frequency value that splits the vocabulary of a
text into two sets of terms (low and high frequency). This technique
is based on the Zipf Law of Word Ocurrences [10] and also on the refined
studies of Booth [1], as well as of Urbizagástegui
[9]. These
studies are meant to demonstrate that midfrequency terms, of a text , are
closely related to the conceptual content of . Therefore, it is
possible to establish the hypothesis that terms closer to TP can be used as index terms of
. A typical formula used to obtain
this value is:
where represents the number of words with frequency equal to ; see
[5] [9].
Alternatively,
TP can be localized by identifying the lowest frequency (from the highest
frequencies) that
it is not repeated in the text; this characteristic comes from the properties of the Booth's
law of low frequency words [1]. In our experiments we have used this approach.
Let us consider a frequencysorted vocabulary
of a document; i.e.,
, with
,
then , iif . The most important words are
those nearest to the TP, i.e.,

(1) 
where is a lower threshold obtained by a given neighbourhood
percentage of TP (NTP), thus,
. is the
upper threshold and it is calculated in a similar way (
).
Either in WebCLEF2005 and in the current competition, we have used , considering that the TP technique
is language independent.
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David Pinto
20070508