Context-sensitive normalization of social media text in bahasa Indonesia based on neural word embeddings

Author:

Kusumawardani Renny Pradina,Priansya Stezar,Atletiko Faizal Johan

Publisher

Elsevier BV

Subject

General Engineering

Reference28 articles.

1. “Unsupervised Modelling of Twitter Conversations,”;Ritter;Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Los Angeles,,2010

2. “Lexical Normalization for Social Media Text,”;Han;ACM Transactions on Intelligent Systems and Technology (TIST),2013

3. “Exploring Word Embeddings for Unsupervised User-generated Content Normalization,”;Bertaglia;Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka,2016

4. “Chinese Informal Word Normalization: an Experimental Study,”;Wang;IJCNLP, Nagoya,2013

5. “Adaptating the Levenshtein Distance to Contextual Spelling Correction,”;Lhoussain;International Journal of Computer Science and Application,2015

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1. Text Normalization for Indonesian Text-to-Speech (TTS) using Rule-Based Approach: A Dataset and Preliminary Study;2021 4th International Conference of Computer and Informatics Engineering (IC2IE);2021-09-14

2. Bahasa Indonesia pre-trained word vector generation using word2vec for computer and information technology field;Journal of Physics: Conference Series;2021-06-01

3. Correcting Polish Bigrams and Diacritical Marks;Advances in Intelligent Systems and Computing;2019

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