NEXT WORD PREDICTION USING LSTM

Authors

  • Afika Rianti Indonesia University of Education
  • Suprih Widodo Indonesia University of Education
  • Atikah Dhani Ayuningtyas Syarif Hidayatullah State Islamic University Jakarta
  • Fadlan Bima Hermawan Syarif Hidayatullah State Islamic University Jakarta

DOI:

https://doi.org/10.56873/jitu.5.1.4748

Keywords:

Machine learning, Next word prediction, LSTM

Abstract

Next word prediction which is also called as language modelling is one field of natural language processing that can help to predict the next word. It’s one of the uses of machine learning. Some researchers before had discussed it using different models such as Recurrent Neural Networks and Federated Text Models. Each researcher used their own models to make the prediction and so the researcher here. Researchers here chose to make the model using  Long Short Term Memory (LSTM) model with 200 epoch for the training. For the dataset, the researcher used web scraping. The dataset contains 180 Indonesian destinations from nine provinces. For the libraries, researchers used  tensorflow, keras, numpy, and matplotlib. To download the model in json format, the researcher used tensorflowjs. Then for the tool to code, the researcher used Google Colab. The last result is 8ms/step, loss: 55%, and accuracy: 75% which means it’s good enough and can be used to predict next words.

References

Jordan, Michael I., and Tom M. Mitchell. "Machine learning: Trends, perspectives, and prospects." Science 349, no. 6245 (2015): 255-260.

Sahoo, Abhaya Kumar, Chittaranjan Pradhan, and Himansu Das. "Performance evaluation of different machine learning methods and deep-learning based convolutional neural network for health decision making." In Nature inspired computing for data science, pp. 201-212. Springer, Cham, 2020.

Prajapati, Gend Lal, and Rekha Saha. "REEDS: Relevance and enhanced entropy based Dempster Shafer approach for next word prediction using language model." Journal of Computational Science 35 (2019): 1-11.

Ambulgekar, Sourabh, Sanket Malewadikar, Raju Garande, and Bharti Joshi. "Next Words Prediction Using Recurrent NeuralNetworks." In ITM Web of Conferences, vol. 40, p. 03034. EDP Sciences, 2021.

Stremmel, Joel, and Arjun Singh. "Pretraining federated text models for next word prediction." In Future of Information and Communication Conference, pp. 477-488. Springer, Cham, 2021.

Xiaoyun, Qu, Kang Xiaoning, Zhang Chao, Jiang Shuai, and Ma Xiuda. "Short-term prediction of wind power based on deep long short-term memory." In 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), pp. 1148-1152. IEEE, 2016.

Vargiu, Eloisa, and Mirko Urru. "Exploiting web scraping in a collaborative filtering-based approach to web advertising." Artif. Intell. Res. 2, no. 1 (2013): 44-54.

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Published

2022-06-30

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Section

Artikel

How to Cite

NEXT WORD PREDICTION USING LSTM. (2022). Journal of Information Technology and Its Utilization, 5(1), 10-13. https://doi.org/10.56873/jitu.5.1.4748