Dang Pham - Academia.edu (original) (raw)
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Papers by Dang Pham
International Journal of Computational Vision and Robotics
Sentiment analysis has been emerging recently as one of the major natural language processing (NL... more Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.
Ieice Transactions, 2006
In this paper, an adaptive array antenna is implemented to enhance the performance of digital TV ... more In this paper, an adaptive array antenna is implemented to enhance the performance of digital TV ISDB-T reception. Issues of realizing the proposed array antenna and its implementation by a joint hardware-software solution are also presented in this paper. Instead of using known reference signals, the proposed method utilizes the GI (Guard Interval) and a periodic property of OFDM signal as a constraint to realize MRC (Maximum Ratio Combining) and SMI (Sample Matrix Inversion) adaptive beam-forming algorithms. Experimental results show that the proposed system drastically improves the quality of reception. Moreover, the proposed system can achieve excellent performance under the conditions of strong interferences.
International Journal of Computational Vision and Robotics
Sentiment analysis has been emerging recently as one of the major natural language processing (NL... more Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.
Ieice Transactions, 2006
In this paper, an adaptive array antenna is implemented to enhance the performance of digital TV ... more In this paper, an adaptive array antenna is implemented to enhance the performance of digital TV ISDB-T reception. Issues of realizing the proposed array antenna and its implementation by a joint hardware-software solution are also presented in this paper. Instead of using known reference signals, the proposed method utilizes the GI (Guard Interval) and a periodic property of OFDM signal as a constraint to realize MRC (Maximum Ratio Combining) and SMI (Sample Matrix Inversion) adaptive beam-forming algorithms. Experimental results show that the proposed system drastically improves the quality of reception. Moreover, the proposed system can achieve excellent performance under the conditions of strong interferences.