Textual data mining

This paper proposed a hybrid GA rule based categorization method, named genetic algorithm rule based categorization (GARC), to enhance the accuracy of categorization rules and to produce accurate classifier for text mining.

14p tohitohi 22-05-2020 11 1   Download

We present a novel application of NLP and text mining to the analysis of financial documents. In particular, we describe an implemented prototype, Maytag, which combines information extraction and subject classification tools in an interactive exploratory framework. We present experimental results on their performance, as tailored to the financial domain, and some forward-looking extensions to the approach that enables users to specify classifications on the fly.

4p bunthai_1 06-05-2013 42 2   Download

Weblogs and message boards provide online forums for discussion that record the voice of the public. Woven into this mass of discussion is a wide range of opinion and commentary about consumer products. This presents an opportunity for companies to understand and respond to the consumer by analyzing this unsolicited feedback. Given the volume, format and content of the data, the appropriate approach to understand this data is to use large-scale web and text data mining technologies.

10p doiroimavanchuadc 06-02-2013 65 7   Download

Tetlock, Saar-Tsechansky and Macskassy (2008) describe a news-based automated trading strategy based on relative occurrence of negative words in firm specific financial news in an effort to predict firms’ accounting earnings and stock returns. A simplified bag of words representation was used to interpret textual data according to the relative frequency of negative words defined by the Harvard psychosocial dictionary. Key findings of Tetlock et al.

7p quaivattim 04-12-2012 47 2   Download