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Subjective Probabilistic Knowledge Grading and Comprehension
A.Suresh Babu, P.Premchand, A.Govardhan
Pages - 70 - 76     |    Revised - 31-01-2011     |    Published - 08-02-2011
Published in International Journal of Data Engineering (IJDE)
Volume - 1   Issue - 5    |    Publication Date - January / February  Table of Contents
MORE INFORMATION
References   |   Abstracting & Indexing
KEYWORDS
Probability & Statistics, Probabilistic Comprehension, Subjective Grading, Subjective Probability
ABSTRACT
Probabilistic Comprehension and Modeling is one of the newest areas in information extraction, text linguistics. Though much of the research vested in linguistics and information extraction is probabilistic, the importance is disappeared in 80’s. This is just because of the input language is noisy, ambiguous and segmented. Probability theory is certainly normative for solving the problems related to uncertainty. Perhaps human language processing is simply non-optimal, non-rational process. Subjective Probabilistic approach fixes this problem, through scenario, evidence and hypothesis.
ABSTRACTING & INDEXING
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REFERENCES
Dan Jurafsky, "Probabilistic Modeling in Psycholinguistics: Linguistic Comprehension and Production", appeared in ‘Probabilistic Linguistics’, edited by Rens Bod, Jennifer Hay, and Stefanie Jannedy, MIT Press, (C) 2002.
Nic Wilson, "Algorithms for Dempster-Shafer Theory", School of Computing and Mathematical Sciences, Oxford Brookes University.
Rieko Matsuda,Yuzuru Hayashi,Chikako Yomota,Yoko Tagashira,Mari Katsumine and Kazuo Iwaki, "Statistical and probabilistic approaches to confidence intervals of linear calibration in liquid chromatography", The Analyst, www.rsc.org/analyst, (C) 2001.
Steffen Staab, "Grading Knowledge: Extracting Degree Information from Texts", ISBN 3-540-66934-5 (C) Springer-Verlag Berlin Heidelberg 1999.
MANUSCRIPT AUTHORS
Mr. A.Suresh Babu
JNTUANANTAPUR - India
asureshjntu@gmail.com
Dr. P.Premchand
Osmania University - India
Dr. A.Govardhan
JNTUHCEJ,Jagityala - India


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