Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)

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Learning to Follow Directions with Untagged Data

Authors
Zhidan Yang, Zhiting Yang
Corresponding Author
Zhidan Yang
Available Online November 2017.
DOI
10.2991/amms-17.2017.15How to use a DOI?
Keywords
component; untagged;lexicon; interpreter;program; semantic; directions; corpus
Abstract

We describe a program learns to follow directions using a corpus, without human preprocessing. The program only build a semantic lexicon instead of semantic grammar to learn from an untagged corpus. Without grammar, the program uses a language-independent parser to find the boundaries between steps, then parse the steps. The rest of paper explains semantic interpreter and genetic algorithm.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
Series
Advances in Intelligent Systems Research
Publication Date
November 2017
ISBN
10.2991/amms-17.2017.15
ISSN
1951-6851
DOI
10.2991/amms-17.2017.15How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Zhidan Yang
AU  - Zhiting Yang
PY  - 2017/11
DA  - 2017/11
TI  - Learning to Follow Directions with Untagged Data
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 70
EP  - 73
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.15
DO  - 10.2991/amms-17.2017.15
ID  - Yang2017/11
ER  -