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'What does my classifier learn?':A visual approach to understanding natural language text classifiers
- Source :
- Natural Language Processing and Information Systems ISBN: 9783319595689, NLDB
- Publication Year :
- 2017
- Publisher :
- Technische Universität Berlin, 2017.
-
Abstract
- Neural Networks have been utilized to solve various tasks such as image recognition, text classification, and machine translation and have achieved exceptional results in many of these tasks. However, understanding the inner workings of neural networks and explaining why a certain output is produced are no trivial tasks. Especially when dealing with text classification problems, an approach to explain network decisions may greatly increase the acceptance of neural network supported tools. In this paper, we present an approach to visualize reasons why a classification outcome is produced by convolutional neural networks by tracing back decisions made by the network. The approach is applied to various text classification problems, including our own requirements engineering related classification problem. We argue that by providing these explanations in neural network supported tools, users will use such tools with more confidence and also may allow the tool to do certain tasks automatically.
- Subjects :
- Machine translation
Computer science
02 engineering and technology
Tracing
Machine learning
computer.software_genre
Convolutional neural network
Visual approach
Classifier (linguistics)
0202 electrical engineering, electronic engineering, information engineering
natural language processing
004 Datenverarbeitung
Informatik
visual feedback
Requirements engineering
Artificial neural network
business.industry
020207 software engineering
neural networks
artificial intelligence
machine learning
ComputingMethodologies_PATTERNRECOGNITION
explanations
020201 artificial intelligence & image processing
requirements engineering
Artificial intelligence
ddc:004
business
computer
Natural language
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-319-59568-9
- ISBNs :
- 9783319595689
- Database :
- OpenAIRE
- Journal :
- Natural Language Processing and Information Systems ISBN: 9783319595689, NLDB
- Accession number :
- edsair.doi.dedup.....951abd45740d5620f94afeef19d52cd4