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Publication detail
ŠŮSTEK, M. ZBOŘIL, F.
Original Title
Obtaining word embedding from existing classification model
Type
conference paper
Language
English
Original Abstract
This paper introduces a new technique to inspect relations between classes in classification model. The method is built on the assumption that it is easier to distinguish some classes than others. The harder the distinction is, the more similar the objects are. Simple application demonstrating this approach was implemented and obtained class representations in a vector space are discussed. Created representation can be treated as word embedding where the words are represented by the classes. As an addition, potential usages and characteristics are discussed including a knowledge base.
Keywords
unsupervised learning, artificial intelligence, word embedding, word2vec, CNN
Authors
ŠŮSTEK, M.; ZBOŘIL, F.
Released
22. 3. 2018
Publisher
Springer International Publishing
Location
Cham
ISBN
978-3-319-76347-7
Book
Intelligent Systems Design and Applications
Edition
ISDA 2017 Intelligent Systems Design and Applications
2194-5357
Periodical
Advances in Intelligent Systems and Computing
Year of study
2018
Number
736
State
Swiss Confederation
Pages from
540
Pages to
547
Pages count
8
URL
https://www.fit.vut.cz/research/publication/11546/
BibTex
@inproceedings{BUT147178, author="Martin {Šůstek} and František {Zbořil}", title="Obtaining word embedding from existing classification model", booktitle="Intelligent Systems Design and Applications", year="2018", series="ISDA 2017 Intelligent Systems Design and Applications", journal="Advances in Intelligent Systems and Computing", volume="2018", number="736", pages="540--547", publisher="Springer International Publishing", address="Cham", doi="10.1007/978-3-319-76348-4\{_}52", isbn="978-3-319-76347-7", issn="2194-5357", url="https://www.fit.vut.cz/research/publication/11546/" }