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Sentiment Analysis Based on Bi-LSTM Using Tone

2019 15th International Conference on Semantics, Knowledge and Grids (SKG), 2019
In view of most of sentiment analysis texts are too short to get enough textual features, a method of bidirectional Long Short-Term Memory using tone (Word, Character and Tone model based on Bidirectional Long Short-Term Memory, WCT-Bi-LSTM) was proposed.
Huakang Li   +3 more
openaire   +1 more source

Research on Question Classification Based on Bi-LSTM

2018
Question classification plays an important role in question answering (QA) system, and its results directly affect the quality of QA. Traditional methods of question classification include rule-based methods and statistical machine learning methods. They need to manually summarize rules or extract the features of questions.
Qian Zhang   +4 more
openaire   +1 more source

Mining Aspects in Online Comments with Attention and Bi-LSTM

2019 5th International Conference on Big Data Computing and Communications (BIGCOM), 2019
With the rapid development of e-commerce platforms, a large number of commodity comments have emerged on the Internet. Comments not only provide consumers with the experience of others, but also make it easier for companies to get feedback from users.
Lan Yao   +3 more
openaire   +1 more source

Image Retrieval Using Multilayer Bi-LSTM

2021
The growth of the internet and the social media has led to rapid growth of the digital images available online as digital databases. The problem of searching such databases for items that are similar to a query image or a query descriptor is termed as image retrieval, and such systems are called image retrieval systems.
Shaily Malik   +4 more
openaire   +1 more source

Myanmar Dialogue Act Recognition Using Bi-LSTM RNN

2020 23rd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA), 2020
Spoken language understanding (SLU) is an essential element of any dialogue system to understand the language where dialogue act (DA) recognition is also critical aspects of pre-processing step for speech understanding and dialogue system. This paper proposes a deep learning-based DA model which use a deep recurrent neural network (RNN) with bi ...
Sann Su Su Yee, Khin Mar Soe
openaire   +1 more source

CP Decomposition for Fast training of Bi-LSTM

2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech), 2021
Ruixin Ma, Chuang Wang, Xin Li
openaire   +1 more source

Construction of Word Segmentation Model Based on HMM + BI-LSTM

2020
Chinese word segmentation plays an important role in search engine, artificial intelligence, machine translation and so on. There are currently three main word segmentation algorithms: dictionary-based word segmentation algorithms, statistics-based word segmentation algorithms, and understanding-based word segmentation algorithms.
Hang Zhang, Bin Wen
openaire   +1 more source

VIT and Bi-LSTM for Micro-Expressions Recognition

2022 IEEE 5th International Conference on Information Systems and Computer Aided Education (ICISCAE), 2022
Huilong Chen   +3 more
openaire   +1 more source

Text multi-label sentiment analysis based on Bi-LSTM

2019 IEEE 6th International Conference on Cloud Computing and Intelligence Systems (CCIS), 2019
The sentiment classification is still one of the most popular research directions in the past decade. Furthermore, the information contained in the Chinese text is definitely not limited to the positive or negative emotions. In view of the complexity of emotional texts, this paper combines various tags to increase the accuracy of sentiment analysis ...
Junlin Hu 0002   +3 more
openaire   +1 more source

Abstractive Summarizer using Bi-LSTM

2022 International Conference on Edge Computing and Applications (ICECAA), 2022
Preethi. S   +4 more
openaire   +1 more source

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