DocumentCode
3656416
Title
Academic Writing Support System Using Bayesian Networks
Author
Masaki Uto;Maomi Ueno
Author_Institution
Nagaoka Univ. of Technol., Niigata, Japan
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
385
Lastpage
387
Abstract
For academic writing, elaborating an argument particularly addressing an argument strength is important to establish causal relations between sentences. However, when an argument becomes large or complex, elaborating an argument considering the argument strength is difficult. To solve this problem, this article presents a proposal for an argument elaboration support system using a Bayesian network representation of the Toulmin model. Using that Bayesian network representation, the proposed system can estimate argument strength, sentence validity, and sentence influence. Moreover, it can generate optimal advice for revising the argument.
Keywords
"Indexes","Bayes methods","Writing","Probabilistic logic","Silicon","Sensitivity","Numerical models"
Publisher
ieee
Conference_Titel
Advanced Learning Technologies (ICALT), 2015 IEEE 15th International Conference on
Type
conf
DOI
10.1109/ICALT.2015.16
Filename
7265356
Link To Document