[csmcwil] 下周讨论班论文
- From: Wu Yuanbin <wuyuanbin.fdu@xxxxxxxxx>
- To: cs_mcwil <cs_mcwil@xxxxxxxxxxxx>
- Date: Fri, 17 Sep 2010 17:21:48 +0800
Hi all
以下为讨论班论文
Title: Identifying Text Polarity Using Random Walks
Abstract:
Automatically identifying the polarity of words is a very important task in
Natural Language Processing. It has applications in text classification,
text filtering, analysis of product review, analysis of responses to
surveys, and mining online discussions. We propose a method for identifying
the polarity of words. We apply a Markov random walk model to a large word
relatedness graph, producing a polarity estimate for any given word. A key
advantage of the model is its ability to accurately and quickly assign a
polarity sign and magnitude to any word. The method could be used both in a
semi-supervised setting where a training set of labeled words is used, and
in an unsupervised setting where a handful of seeds is used to define the
two polarity classes. The method is experimentally tested using a manually
labeled set of positive and negative words. It out- performs the state of
the art methods in the semi-supervised setting. The results in the
unsupervised setting is comparable to the best reported values. However, the
pro- posed method is faster and does not need a large corpus.
thanks
yuanbin
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