Named entity recognition on Indonesian Twitter posts using long short-term memory networks

Valdi Rachman, Septiviana Savitri, Fithriannisa Augustianti, Rahmad Mahendra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

The task of Named-Entity Recognition (NER) can support the higher-level tasks such as question answering, text summarization, and information retrieval. This work views NER on Indonesian Twitter posts as a sequence labeling problem using supervised machine learning approach. The architecture used is Long Short-Term Memory Networks (LSTMs), with word embedding and POS tag as the model features. As the result, our model can give a performance with an F1 score of 77.08%.

Original languageEnglish
Title of host publication2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages228-232
Number of pages5
ISBN (Electronic)9781538631720
DOIs
Publication statusPublished - 4 May 2018
Event9th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017 - Jakarta, Indonesia
Duration: 28 Oct 201729 Oct 2017

Publication series

Name2017 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
Volume2018-January

Conference

Conference9th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2017
Country/TerritoryIndonesia
CityJakarta
Period28/10/1729/10/17

Keywords

  • Indonesian language
  • Long Short-Term Memories
  • Named Entity Recognition
  • Twitter

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