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Distributed Online Pre-Processing Framework for Big Data Sentiment Analytics [PDF]
Journal of Artificial Intelligence and Data Mining, 2022 Performing sentiment analysis on social networks big data can be helpful for various research and business projects to take useful insights from text-oriented content.
M. Molaei, D. Mohamadpur
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DESIGNING EFFECTIVE CHATBOT SYSTEM USING GRU WITH BEAM SEARCH
ICTACT Journal on Soft Computing, 2022 Artificial Intelligence (AI) based Chatbot is a moderately new technology in the world. AI and Natural Language Processing (NLP) empowers a Chatbot to converse like a human being.
Sandeep A. Thorat +2 more
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Successive Image Generation from a Single Sentence [PDF]
ITM Web of Conferences, 2021 Through various examples in history such as the early man’s carving on caves, dependence on diagrammatic representations, the immense popularity of comic books we have seen that vision has a higher reach in communication than written words. In this paper,
Parab Amogh +4 more
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Click-through rate prediction model based on a deep neural network
工程科学学报, 2022 The click-through rate (CTR) prediction task is to estimate the probability that a user will click an item according to the features of user, item, and contexts.
Hong-li LIU +4 more
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Gated Recurrent Unit Based On Feature Attention Mechanism For Physical Behavior Recognition Analysis
Journal of Applied Science and Engineering, 2022 In order to overcome the problem that traditional machine learning methods rely heavily on artificial feature selection and have low recognition accuracy in the field of human behavior recognition, a deep learning model based on multi-layer recurrent ...
Wen Ying
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Review on recent Computer Vision Methods for Human Action Recognition
Advances in Distributed Computing and Artificial Intelligence Journal, 2022 The subject of human activity recognition is considered an important goal in the domain of computer vision from the beginning of its development and has reached new levels. It is also thought of as a simple procedure.
Azhee Wria Muhamada, Aree A. Mohammed
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Learning and Generalization in RNNs
CoRR, 2021 Simple recurrent neural networks (RNNs) and their more advanced cousins LSTMs etc. have been very successful in sequence modeling. Their theoretical understanding, however, is lacking and has not kept pace with the progress for feedforward networks, where a reasonably complete understanding in the special case of highly overparametrized one-hidden ...
Abhishek Panigrahi, Navin Goyal
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Excitation Backprop for RNNs [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 CVPR 2018 Camera Ready ...
Sarah Adel Bargal +5 more
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SENTIMENT ANALYSIS WITH LONG-SHORT TERM MEMORY (LSTM) AND GATED RECURRENT UNIT (GRU) ALGORITHMS
Barekeng, 2023 Sentiment analysis is a form of machine learning that functions to obtain emotional polarity values or data tendencies from data in the form of text. Sentiment analysis is needed to analyze opinions, sentiments, reviews, and criticisms from someone for a
Muhammad Nazhif Abda Putera Khano +3 more
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CoRR, 2014 Sequence prediction and classification are ubiquitous and challenging problems in machine learning that can require identifying complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory, to cope with these temporal dependencies by virtue of the short-term memory implemented by their recurrent ...
Jan Koutník +3 more
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