Importance of Knowledge Graphs and Their Issues
Understand the importance of knowledge graphs.
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Use cases
The main importance of knowledge graphs comes when handling several real-world use cases. Here are some of the few different use cases:
Semantic search: Google Search and Google's Knowledge Graph are great examples of this use case. The graphs are used to enhance the search capabilities of the website.
Recommendation system: We model the relationships between products, users, and other entities to provide personalized recommendations. Netflix's recommendation system models the relationship between users, movies, and TV shows.
Question answering: A chatbot or a language model is a good example for this use case. OpenAI's GPT-3, Google Assistant, and Apple's Siri are some examples that use a knowledge graph to generate human-like text responses.
Data integration: Since knowledge graphs are multi-relational, we can integrate and link data from multiple sources to make them more useful.
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