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Machine Learning for Natural Language

Named Entity Recognition on Indonesian Microblog Messages


This paper describes a model to address the task of named-entity recognition on Indonesian microblog messages due to its usefulness for higher-level tasks or text mining applications on Indonesian microblogs. We view our task as a sequence labeling problem using machine learning approach. We also propose various word-level and orthographic features, including the ones that are specific to the Indonesian language. Finally, in our experiment, we compared our model with a baseline model previously proposed for Indonesian formal documents, instead of microblog messages.

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Authors:
Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani
Submitted On:
22 November 2016 - 7:42am
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IALP2016 - Named Entity Recognition on Indonesian Microblog Messages.pdf

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[1] Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani, "Named Entity Recognition on Indonesian Microblog Messages", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1293. Accessed: May. 26, 2019.
@article{1293-16,
url = {http://sigport.org/1293},
author = {Natanael Taufik; Alfan F. Wicaksono; Mirna Adriani },
publisher = {IEEE SigPort},
title = {Named Entity Recognition on Indonesian Microblog Messages},
year = {2016} }
TY - EJOUR
T1 - Named Entity Recognition on Indonesian Microblog Messages
AU - Natanael Taufik; Alfan F. Wicaksono; Mirna Adriani
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1293
ER -
Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani. (2016). Named Entity Recognition on Indonesian Microblog Messages. IEEE SigPort. http://sigport.org/1293
Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani, 2016. Named Entity Recognition on Indonesian Microblog Messages. Available at: http://sigport.org/1293.
Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani. (2016). "Named Entity Recognition on Indonesian Microblog Messages." Web.
1. Natanael Taufik, Alfan F. Wicaksono, Mirna Adriani. Named Entity Recognition on Indonesian Microblog Messages [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1293

An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction


Semantic role labeling (SRL) is a task to as- sign semantic role labels to sentence elements. This pa- per describes the initial development of an Indonesian semantic role labeling system and its application to extract event information from Tweets. We compare two feature types when designing the SRL systems: Word-to-Word and Phrase-to-Phrase. Our experiments showed that the Word- to-Word feature approach outperforms the Phrase-to-Phrase approach. The application of the SRL system to an event extraction problem resulted overlap-based accuracy of 0.94 for the actor identification.

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Authors:
Ayu Purwarianti, Lisa Madlberger
Submitted On:
21 November 2016 - 10:37pm
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presentation_IALP2016_Ade.pdf

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[1] Ayu Purwarianti, Lisa Madlberger, "An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction ", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1289. Accessed: May. 26, 2019.
@article{1289-16,
url = {http://sigport.org/1289},
author = {Ayu Purwarianti; Lisa Madlberger },
publisher = {IEEE SigPort},
title = {An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction },
year = {2016} }
TY - EJOUR
T1 - An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction
AU - Ayu Purwarianti; Lisa Madlberger
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1289
ER -
Ayu Purwarianti, Lisa Madlberger. (2016). An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction . IEEE SigPort. http://sigport.org/1289
Ayu Purwarianti, Lisa Madlberger, 2016. An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction . Available at: http://sigport.org/1289.
Ayu Purwarianti, Lisa Madlberger. (2016). "An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction ." Web.
1. Ayu Purwarianti, Lisa Madlberger. An Initial Study of Indonesian Semantic Role Labeling and Its Application on Event Extraction [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1289

Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity


In this paper, we study language models based on recurrent neural networks on three databases in two languages. We implement basic recurrent neural networks (RNN) and refined RNNs with long short-term memory (LSTM) cells. We use the corpora of Penn Tree Bank (PTB) and AMI in English, and the Academia Sinica Balanced Corpus (ASBC) in Chinese. On ASBC, we investigate wordbased and character-based language models. For characterbased language models, we look into the cases where the inter-word space is treated or not treated as a token.

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Authors:
Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen
Submitted On:
21 November 2016 - 10:21am
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40_RNN

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[1] Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen, "Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1285. Accessed: May. 26, 2019.
@article{1285-16,
url = {http://sigport.org/1285},
author = {Tzu-Hsuan Yang; Tzu-Hsuan Tseng; Chia-Ping Chen },
publisher = {IEEE SigPort},
title = {Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity},
year = {2016} }
TY - EJOUR
T1 - Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity
AU - Tzu-Hsuan Yang; Tzu-Hsuan Tseng; Chia-Ping Chen
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1285
ER -
Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen. (2016). Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity. IEEE SigPort. http://sigport.org/1285
Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen, 2016. Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity. Available at: http://sigport.org/1285.
Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen. (2016). "Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity." Web.
1. Tzu-Hsuan Yang, Tzu-Hsuan Tseng, Chia-Ping Chen. Recurrent Neural Network-based Language Models with Variation in Net Topology, Language, and Granularity [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1285

Verifying the Long-range Dependency of RNN Language Models


It has been argued that recurrent neural network language models are better in capturing long-range dependency than n-gram language models. In this paper, we attempt to verify this claim by investigating the prediction accuracy and the perplexity of these language models as a function of word position, i.e., the position of a word in a sentence. It is expected that as word position increases, the advantage of using recurrent neural network language models over n-gram language models will become more and more evident.

Paper Details

Authors:
Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen
Submitted On:
21 November 2016 - 10:24am
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41_ngram_rnn

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[1] Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen, "Verifying the Long-range Dependency of RNN Language Models", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1284. Accessed: May. 26, 2019.
@article{1284-16,
url = {http://sigport.org/1284},
author = {Tzu-Hsuan Tseng; Tzu-Hsuan Yang; Chia-Ping Chen },
publisher = {IEEE SigPort},
title = {Verifying the Long-range Dependency of RNN Language Models},
year = {2016} }
TY - EJOUR
T1 - Verifying the Long-range Dependency of RNN Language Models
AU - Tzu-Hsuan Tseng; Tzu-Hsuan Yang; Chia-Ping Chen
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1284
ER -
Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen. (2016). Verifying the Long-range Dependency of RNN Language Models. IEEE SigPort. http://sigport.org/1284
Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen, 2016. Verifying the Long-range Dependency of RNN Language Models. Available at: http://sigport.org/1284.
Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen. (2016). "Verifying the Long-range Dependency of RNN Language Models." Web.
1. Tzu-Hsuan Tseng, Tzu-Hsuan Yang, Chia-Ping Chen. Verifying the Long-range Dependency of RNN Language Models [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1284