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Related Questions
- How does a knowledge graph-based representation help virtual assistants understand user intent?
- What are the key components of a knowledge graph that enable virtual assistants to capture user context?
- Can you provide examples of how knowledge graphs are used in virtual assistants to improve user experience?
- How does knowledge graph-based representation differ from traditional natural language processing (NLP) approaches in capturing user context?
- What are the benefits of using knowledge graph-based representation in virtual assistants compared to other methods?
- How can knowledge graphs be updated and maintained to ensure that virtual assistants remain context-aware over time?
- What are some common challenges in implementing knowledge graph-based representation in virtual assistants and how can they be addressed?
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