Two scalable algorithms for associative text classification

agreeablesocietyAI and Robotics

Oct 29, 2013 (3 years and 7 months ago)

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Intelligent Database Systems Lab

Presenter
:
Chang,Chun
-
Chih

Authors :
YONGWOOK

YOON,
GARY G. LEE

2012 IPM

Two scalable algorithms for associative text
classification

Intelligent Database Systems Lab

Outlines


Motivation


Objectives


Methodology


Experiments


Conclusions


Comments

Intelligent Database Systems Lab

Motivation


Associative classification methods have been
recently applied to various
categorization tasks.



some associative classifiers generate
a huge number
of association
rules

during the mining
step.

Intelligent Database Systems Lab

Objectives











We present two algorithms to increase the
computational
efficiency of
associative classification:




1.
To
store rules very
efficiently


2. Increase
the speed of rule matching



Intelligent Database Systems Lab

Methodology


Associative text classification


Intelligent Database Systems Lab

Methodology


Intelligent Database Systems Lab

Methodology


Intelligent Database Systems Lab

Methodology


Intelligent Database Systems Lab

Methodology


Intelligent Database Systems Lab

Methodology


Intelligent Database Systems Lab

Experiments


Intelligent Database Systems Lab

Experiments


Intelligent Database Systems Lab

Experiments


Intelligent Database Systems Lab

Experiments


Intelligent Database Systems Lab

Experiments


Intelligent Database Systems Lab

Conclusions



If these two algorithms are applied, the use

of associative classifiers becomes
feasible

for


large
-
scale text classification.

Intelligent Database Systems Lab

Comments


Advantages


-

store

rules very
efficiently


-

increase the
speed

of rule
matching



Applications


-

Association
rule mining