Darren Kuo

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2011-147

December 16, 2011

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-147.pdf

This paper evaluates prediction and topic modelling methods through the task of word prediction. In our word prediction experiment, we compare some existing and two novel methods, including a version of Cooccurrence, two versions of K-Nearest-Neighbor method and Latent semantic indexing, against a baseline algorithm. Furthermore, we explore the effects of using different similarity functions on the accuracies of our prediction methods. Finally, without much modifications to the framework, we were also able to perform tag classification on StackOverflow posts.

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BibTeX citation:

@techreport{Kuo:EECS-2011-147,
    Author= {Kuo, Darren},
    Title= {On Word Prediction Methods},
    Year= {2011},
    Month= {Dec},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-147.html},
    Number= {UCB/EECS-2011-147},
    Abstract= {This paper evaluates prediction and topic modelling methods through the task of word prediction. In our word prediction experiment, we compare some existing and two novel methods, including a version of Cooccurrence, two versions of K-Nearest-Neighbor method and Latent semantic indexing, against a baseline algorithm. Furthermore, we explore the effects of using different similarity functions on the accuracies of our prediction methods. Finally, without much modifications to the  framework, we were also able to perform tag classification on StackOverflow posts.},
}

EndNote citation:

%0 Report
%A Kuo, Darren 
%T On Word Prediction Methods
%I EECS Department, University of California, Berkeley
%D 2011
%8 December 16
%@ UCB/EECS-2011-147
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2011/EECS-2011-147.html
%F Kuo:EECS-2011-147