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Employ Transfer Learning Approach for Sentiment Classification at TenPoint7

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Universal Language Model Fine-tuning (ULMFiT)1 is an effective transfer learning approach for solving variety tasks in Natural Language Processing (NLP). The authors shed some light on the three common tasks of text classification: sentiment analysis, question classification, and topic classification. Their work especially achieves state-of-the-art results on six text classification tasks.
  1. Jeremy Howard and Sebastian Ruder, Universal Language Model Fine-tuning for Text Classification, 2018 
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A Simplified Framework for Air Route Clustering Based on ADS-B Data

Published in The 2019 IEEE-RIVF International Conference on Computing and Communication Technology, 2019

Proposed a simplified framework that can support to detect the typical air routes between airports based on ADS-B data Read more

Recommended citation: Quan Duong, Tan Tran, Duc-Thinh Pham, An Mai (2019). "A Simplified Framework for Air Route Clustering Based on ADS-B Data." The 2019 IEEE-RIVF International Conference on Computing and Communication Technology. https://ieeexplore.ieee.org/document/8713685

An Adaptive Hash-Based Text Deduplication for ADS-B Data-Dependent Trajectory Clustering Problem

Published in The 2019 IEEE-RIVF International Conference on Computing and Communication Technology, 2019

Applied LSH-based algorithm for the problem of trajectory clustering. Read more

Recommended citation: Tan Tran, Quan Duong, Duc-Thinh Pham, An Mai (2019). "An Adaptive Hash-Based Text Deduplication for ADS-B Data-Dependent Trajectory Clustering Problem." The 2019 IEEE-RIVF International Conference on Computing and Communication Technology. https://ieeexplore.ieee.org/document/8713722

Hub and Spoke Logistics Network Design for Urban Region with Clustering-Based Approach

Published in The 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), 2021

Offer an efficient flow distribution network as a competitive strategy Read more

Recommended citation: Quan Duong, Dang Nguyen, Quoc Nguyen (2021). "Hub and Spoke Logistics Network Design for Urban Region with Clustering-Based Approach." In: Fujita H., Selamat A., Lin J.CW., Ali M. (eds) Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices. IEA/AIE 2021. Lecture Notes in Computer Science, vol 12798. Springer, Cham. https://doi.org/10.1007/978-3-030-79457-6_51. https://link.springer.com/chapter/10.1007/978-3-030-79457-6_51

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