IPTEK Journal of Proceedings Series
No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015

Parsing Indonesian Syntactic with Recursive Neural Network

Putra, Karisma Trinanda (Institut Teknologi Sepuluh Nopember, Surabaya)
Purwanto, Djoko (Institut Teknologi Sepuluh Nopember, Surabaya)
Mardiyanto, Ronny (Institut Teknologi Sepuluh Nopember, Surabaya)



Article Info

Publish Date
28 Jan 2016

Abstract

Sentence is a form of human communication which is closely related to language system. Sentence is one of the recursive structures that are often found in daily conversation. Learning syntactic structure is useful to explore the meaning of the sentence contained on it or translated it into another language such as machine language. The problem is meaning, ambiguity, and the language that is not according to the rules of syntax, causing the command translation become more complex. This research is about parsing Indonesian syntax based on natural language rules for applications in the field of human-machine interaction. Each word that is a part of the sentence, is mapped into vector-space model. To estimate the potential connection of two words, we use the recursive neural network. The potential connection of two words translated into a higher structure to obtain a complete sentence structure. We obtain 93% accuracy, with 50 data-set are given in the learning process to represent a hundred vocabularies.

Copyrights © 2015






Journal Info

Abbrev

jps

Publisher

Subject

Computer Science & IT

Description

IPTEK Journal of Proceedings Series publishes is a journal that contains research work presented in conferences organized by Institut Teknologi Sepuluh Nopember. ISSN: 2354-6026. The First publication in 2013 year from all of full paper in International Conference on Aplied Technology, Science, and ...