Wednesday, November 5, 2014 — 2:00 PM to 3:00 PM EST

You are invited to attend our next UW CPAMI Graduate Seminar, which will include:

Dr. Rushdi Shams, Ph.D. Researcher, Computational Linguistics Lab, Western University.
He will speak on "Identification of Informativeness in Text using Natural Language Stylometry"

  All are welcome to attend!

 *Refreshments will be provided


Identification of Informativeness in Text using
Natural Language Stylometry

Abstract :
Today, written text is growing rapidly and over-abundantly. This plethora of texts is now widely used to develop and optimize statistical natural  language processing (NLP) systems. Surprisingly, the use of more fragments of text to train these statistical NLP systems may not necessarily lead to improved performance. We hypothesize that those fragments that help the most with training are those that contain the desired information. Therefore, determining informativeness in text has become a central issue in our view of NLP. We take a different approach to this problem by considering the underlying theme of a linguistic theory known as the Code Quantity Principle that suggests that humans codify information in text by changing their writing style so that readers can retrieve this information more efficiently. In another vein, Stylometry is a modern method to analyze literary style. With this as background, we model text using a set of stylometric attributes to characterize variations in writing style present in it. We explore their effectiveness to determine informativeness in texts of different genres, viz., scientific papers, technical reports, emails and newspaper articles, that are selected from assorted domains like agriculture, physics, and biomedical science. In addition, the potential
of stylometric attributes is also explored in some NLP application areas including biomedical relation mining, automatic keyphrase indexing, spam classification, and text summarization---where performance improvement is both important and challenging. The success of the attributes in all these areas further highlights their usefulness.

For more information, please refer to the pdf file:
identification_of_informativeness_in_text_using_natural_language_stylometry.pdf

Location 
E5 - Engineering 5
Room 5106
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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