lecture18-learning-ranking-handouts-6-per

Akamachinelearnedrelevanceorlearningtorank

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Unformatted text preview: requency,
pivoted
 document
length
normaliza)on,
Pagerank,
…
   How
do
we
combine
these
signals
into
a
good
ranker?
   We’ve
looked
at
methods
for
classifying
documents
 using
supervised
machine
learning
classifiers
   Naïve
Bayes,
Rocchio,
kNN,
SVMs
   Modern
supervised
ML
has
been
around
for
about
15
 years…
   Naïve
Bayes
has
been
around
for
about
45
years…
   Surely
we
can
also
use
machine learning to
figure
out
 how
to
combine
scoring/ranking
signals?
   A.k.a.
“machine‐learned
relevance”
or
“learning
to
rank”
 Introduc)on to Informa)on Retrieval Why
weren’t
early
agempts
very
successful/ influen)al?
   Limited
training
data
   Especially
for
real
world
use
(as
opposed
to
wri)ng
 academic
papers),
it
was
very
hard
to
gather
test
collec)on
 queries
and
relevance
judgments
that
are
representa)ve
of
 real
user
needs
and
judgments
on
documents
returned
   This
has
changed,
both
in
academia
and...
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This document was uploaded on 02/26/2014.

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