ICSADL 2020
Scopus-Indexed Springer International Conference on Sentimental Analysis and Deep Learning 2020
Important Dates
About ICSADL 2020
International Conference on Sentimental Analysis and Deep Learning (ICSADL 2020) is a prominent event organized with the motivation for providing an international forum for all researchers, academicians and students for sharing their research findings on the different facets of Deep Learning and Sentimental Analysis techniques. ICSADL 2020 aims to exchange and share new ideas and research results about all aspects of Sentimental analysis and deep learning which includes Artificial Intelligence, Innovations in robotics, Big Data and also converse the practical challenges encountered and the solutions adopted. ICSADL 2020 Conference proceedings publication with Springer Communications in Computer and Information Science series
Topics
Artificial intelligence, computer software and applications, Architecture, artificial intelligence, computer software and applications, computing, data mining, design, energy, engineering,Call for Papers
We invite submissions of papers addressing theoretical aspects of Sentimental Analysis, Deep Learning and related topics. We strongly support a broad definition of learning theory, including, but not limited to: Sentiment Analysis
- Cognitive Computing
- Deep Learning
- Semantics & Syntactic Analysis
- Natural Language Processing
- Emotion-Driven Systems
- Data Mining for ontology matching, instance matching and search
- Recommender systems Applications in Social Networks
- AI Driven Sentiment Analysis
- Information Retrieval and Document Analysis
- Intelligent Decision Making
- Fog Computing
- Data Analytics and Computing
- Reinforcement learning
- Image Processing
- Cognitive Networks
- Evolutionary Computing
- Genetic Algorithms
- Statistical learning methods
- Fuzzy models
- Security and Privacy Methods in Deep Learning
- Foundational theoretical or computational models for big data
- Big data quality evaluation and assurance technologies
- Artificial Intelligence for big data
- Visualization analytics for big data
- Real-time Big Data Services and Applications
- Big data services and applications for healthcare
- Web Intelligence
- Cryptographic Algorithms and Protocols
- Web mining and Graph Mining
- Machine learning in cloud computing
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