Cognitive Computing for Natural Language Understanding
Table Of Contents
1. Introduction
1.1 Background and Motivation
1.2 Objectives and Scope
2. Literature Review
2.1 Cognitive Computing and Natural Language Understanding
2.2 State-of-the-Art Techniques and Applications
3. Methodology
3.1 Data Collection and Preprocessing
3.2 Cognitive Computing Models and Algorithms
4. Natural Language Understanding System Design
4.1 Semantic Analysis and Context Awareness
4.2 Sentiment Recognition and Emotional Analysis
5. Implementation and Experimentation
5.1 System Development and Integration
5.2 Performance Evaluation and Testing
Thesis Abstract
Cognitive computing has emerged as a powerful paradigm for developing intelligent systems that can understand and process natural language. This project aims to explore the application of cognitive computing techniques, including machine learning and natural language processing, to enhance the understanding of human language by computers. The project will focus on developing a cognitive computing system capable of advanced natural language understanding, including semantic analysis, context awareness, and sentiment recognition. The system's potential applications range from conversational agents to advanced text analytics and information retrieval.
Thesis Overview
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