AI White Paper Downloads — LargitData Technical White Papers
LargitData regularly publishes AI technology white papers, sharing our in-depth research findings across areas including sentiment analysis, RAG technology, and enterprise AI deployment. Combining academic research with real-world industry experience, these white papers help enterprise decision-makers and technical teams gain a deeper understanding of AI technology trends and best practices.
The Complete Enterprise Media Monitoring Guide: From Data Collection to Decision Support
This white paper provides an in-depth exploration of how enterprises can apply AI-powered sentiment analysis to extract valuable business insights from vast news, social media, and online forum data. Topics covered include data collection strategies, the technical principles of NLP sentiment analysis, sentiment metric design, and how to translate sentiment data into actionable business decisions.
- Media Monitoring Technical Architecture and Data Source Strategy
- Technical Challenges and Solutions for Chinese NLP Sentiment Analysis
- Enterprise Media Monitoring Metric Design and KPI Tracking
- Real-World Case Analysis and ROI Calculation
Pages: 32 | Format: PDF | Language: Traditional Chinese
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RAG Technology White Paper: Enterprise Applications of Retrieval-Augmented Generation
A comprehensive analysis of RAG (Retrieval-Augmented Generation) technology — covering its underlying principles, architectural design, and enterprise application scenarios. This white paper details how to build an enterprise knowledge base using RAG, enabling employees to interact with internal knowledge through natural language, and compares RAG against traditional knowledge management systems.
- RAG Technical Principles: Embeddings, Vector Databases, and Generative Models
- Complete Process and Architecture Design for Building an Enterprise Knowledge Base
- RAG vs. Fine-Tuning: Choosing the Right Approach for Your Needs
- Document Chunking, Index Optimization, and Strategies for Improving Answer Quality
Pages: 28 | Format: PDF | Language: Traditional Chinese
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Enterprise AI Deployment Strategy: Choosing Between Cloud and On-Premise
A comprehensive analysis of the critical decisions involved in enterprise AI deployment. This white paper compares the advantages and disadvantages, cost structures, security considerations, and applicable scenarios of cloud-based versus on-premise AI deployment — helping enterprise IT decision-makers select the most suitable deployment strategy.
- Architectural Differences and Technical Comparison of Cloud AI vs. On-Premise AI
- TCO (Total Cost of Ownership) Analysis: Short-Term Costs vs. Long-Term Benefits
- Data Security and Regulatory Compliance Considerations
- Hybrid Deployment Strategy and Best Practice Recommendations
Pages: 24 | Format: PDF | Language: Traditional Chinese
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Large Language Model Enterprise Application Guide: From POC to Production
This white paper provides a complete roadmap for enterprise LLM (Large Language Model) adoption, covering every step from proof of concept (POC) to full production deployment. Topics include model selection, data preparation, performance evaluation, security safeguards, and best practices for continuous optimization.
- LLM Selection Guide: Evaluation Framework for Open-Source vs. Commercial Models
- Implementation Roadmap from POC to Production Environment
- Prompt Engineering and AI Safety Measures
- Performance Monitoring and Continuous Optimization Strategy
Pages: 36 | Format: PDF | Language: Traditional Chinese
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