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What and Who
Title:Exploring new feature space for Sentiment Analysis
Speaker:Kashyap Popat
coming from:International Max Planck Research School for Computer Science - IMPRS
Speakers Bio:
Event Type:IMPRS Research Seminar
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Monday, 9 November 2015
Duration:-- Not specified --
Building:E1 4
Expensive feature engineering based on word senses has been shown to be useful for document level sentiment classification.

A plausible reason for such a performance improvement is the reduction in data sparsity. However, such a reduction could be
achieved with a lesser effort through the means of syntagma based word clustering which addresses the problem of data sparsity
in sentiment analysis, both monolingual and cross-lingual.

In this talk, I will present the evolution of features in document level sentiment classification along with the brief introduction of
my current research work.

Name(s):Andrea Ruffing
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
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Attachments, File(s):
  • Andrea Ruffing, 11/05/2015 05:36 PM -- Created document.