lecture18-learning-ranking-handouts-6-per

1541 introducontoinformaonretrieval modiedexample

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Unformatted text preview: Query
term
proximity
   Train
a
machine
learning
model
to
predict
the
class
r of
a
document‐query
pair

 Sec.
15.4.1
 Introduc)on to Informa)on Retrieval Using
classifica)on
for
deciding
relevance
 cosine score α 0.05
 R 0.025
 R R N N 3
 Decision
surface
 Introduc)on to Informa)on Retrieval More
complex
example
of
using
classifica)on
for
 search
ranking

[Nallapa)
2004]
   We
can
generalize
this
to
classifier
func)ons
over
 more
features
   We
can
use
methods
we
have
seen
previously
for
 learning
the
linear
classifier
weights
 N R N N 0
 2
 R N R N R R R R R   …
just
like
when
we
were
doing
text
classifica)on
 N N N 4
 5
 Term proximity ω 3 5/30/11 Introduc)on to Informa)on Retrieval Introduc)on to Informa)on Retrieval An
SVM
classifier
for
relevance
[Nallapa)
2004]
 An
SVM
classifier
for
relevance
   Let

g(r|d,q)
=
wf(d,q)
+
b
   SV...
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