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Conneau, A., Schwenk, H., Barrault, L. and Lecun, Y. (2017) Very Deep Convolutional Networks for Text Classification. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, Valencia, April 2017, 1107-1116.
https://doi.org/10.18653/v1/e17-1104

has been cited by the following article:

• TITLE: A Development of a Knowledge Management System for Water Situation Reports in Thailand

  AUTHORS: Prattana Deeprasertkul

  KEYWORDS: Optical Character Recognition, Text Similarity, FastText, ElasticSearch

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.10, October 10, 2024

  ABSTRACT: The development of a knowledge management system for the National Hydro Data Center of Thailand was described in this paper. The system was created after the major flood event in 2011 to improve water resource management. It addresses the need for easy access to water situation reports, which are crucial for informed decision-making on water usage, allocation, and reservoir management. The system utilizes Optical Character Recognition technique to convert scanned water situation reports into searchable text. It applied FastText and ElasticSearch for advanced search functionalities. FastText identified the documents related to the search query, even with typos or misspelled words. ElasticSearch allows for efficient searching of text data based on relevance. The system also integrates Google Search for additional information access. Therefore, this knowledge management system provides an efficient way to access and analyze water situation data in Thailand.