Novel Causal Network Modeling Method Integrating Process Knowledge with Modified Transfer Entropy: A Case Study of Complex Chemical Processes

2017 ◽  
Vol 56 (48) ◽  
pp. 14282-14289 ◽  
Author(s):  
Qun-Xiong Zhu ◽  
Qian-Qian Meng ◽  
Ping-Jiang Wang ◽  
Yan-Lin He
Keyword(s):  
Network Modeling ◽  
Chemical Processes ◽  
Modeling Method ◽  
Transfer Entropy ◽  
Causal Network ◽  
Process Knowledge ◽  
Complex Chemical ◽  
Integrating Process

scholarly journals Research and application of causal network modeling based on process knowledge and modified transfer entropy

2018 ◽  
Vol 51 (18) ◽  
pp. 303-308
Author(s):  
Zhu Qunxiong ◽  
Ya Sitai ◽  
Geng Zhiqiang ◽  
Xu Yuan ◽  
Han Yongming ◽  
...  
Keyword(s):  
Network Modeling ◽  
Transfer Entropy ◽  
Causal Network ◽  
Process Knowledge

One small step for MIP towards automated metaphor identification?

2013 ◽  
Vol 3 (1) ◽  
pp. 77-99 ◽  
Author(s):  
Aletta G. Dorst ◽  
W.Gudrun Reijnierse ◽  
Gemma Venhuizen
Keyword(s):  
Large Scale ◽  
Chemical Processes ◽  
Small Step ◽  
Lexical Unit ◽  
Basic Meaning ◽  
General Rules ◽  
Natural Discourse ◽  
Authentic Data ◽  
Large Corpus

The manual annotation of large corpora is time-consuming and brings about issues of consistency. This paper aims to demonstrate how general rules for determining basic meanings can be formulated in large-scale projects involving multiple analysts applying MIP(VU) to authentic data. Three sets of problematic lexical units — chemical processes, colours, and sharp objects — are discussed in relation to the question of how the basic meaning of a lexical unit can be determined when human and non-human senses compete as candidates for the basic meaning; these analyses can therefore be considered a detailed case study of problems encountered during step 3.b. of MIP(VU). The analyses show how these problematic cases were tackled in a large corpus clean-up project in order to streamline the annotations and ensure a greater consistency of the corpus. In addition, this paper will point out how the formulation of general identification rules and guidelines could provide a first step towards the automatic detection of linguistic metaphors in natural discourse.

scholarly journals Causal Network Modeling of the Determinants of Drinking Behavior in Comorbid Alcohol Use and Anxiety Disorder

2018 ◽  
Vol 43 (1) ◽  
pp. 91-97 ◽  
Author(s):  
Justin J. Anker ◽  
Erich Kummerfeld ◽  
Alexander Rix ◽  
Scott J. Burwell ◽  
Matt G. Kushner
Keyword(s):  
Anxiety Disorder ◽  
Alcohol Use ◽  
Network Modeling ◽  
Drinking Behavior ◽  
Causal Network

32.1 Machine Learning and Causal Network Modeling for Research on PTSD and Suicide

2018 ◽  
Vol 57 (10) ◽  
pp. S319
Author(s):  
Glenn N. Saxe ◽  
Sisi Ma ◽  
Leah J. Morales ◽  
Constantin Aliferis
Keyword(s):  
Machine Learning ◽  
Network Modeling ◽  
Causal Network
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