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  1. Home
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  4. Using Probability Theory to Identify the Unsure Value of an Incomplete Sentence
 
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Using Probability Theory to Identify the Unsure Value of an Incomplete Sentence

Journal
Proceedings - UKSim-AMSS 17th International Conference on Computer Modelling and Simulation, UKSim 2015
Date Issued
2016
Author(s)
Nur Fatin Nabila Mohd Rafei Heng 
Universiti Sains Islam Malaysia 
Nurlida Basir 
Universiti Sains Islam Malaysia 
Madihah Mohd Saudi 
Universiti Sains Islam Malaysia 
Sakinah Ali Pitchay 
Universiti Sains Islam Malaysia 
Farida Hazwani Mohd Ridzuan 
Universiti Sains Islam Malaysia 
Mamat A.
Deris M.M.
DOI
10.1109/UKSim.2015.90
Abstract
Most of the existing techniques on relation extraction focus on extracting relation between subject, predicate and object in a single sentence. However, these techniques unable to handle the situation when the text has sentences that are incomplete: either does not have or unclear subject or object in sentence (i.e. 'unsure' value). Thus this does not properly represent the domain text. This paper proposes an approach to predict and identify the unsure value to complete the sentences in the domain text. The proposed approach is based on the probability theory to identify terms (i.e., subject or object) that are more likely to replace the 'unsure' value. We use voting machine domain text as a case study. 2015 IEEE.
Subjects

Incomplete informatio...

most dominant

non-taxanomic

predicate

probability theory

Circuit simulation

Computer science

Computers

Software engineering

Incomplete informatio...

most dominant

non-taxanomic

predicate

Probability theory

Probability

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