Скачать или смотреть The Power of Semantic Index in AI Copilot

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To sum up, keyword indexing depends on specific terms and exact matches, whereas semantic indexing endeavors to grasp the conceptual meaning of content, offering increased flexibility and depth in retrieving information.

Semantic indexing proves especially beneficial in applications that require a thorough understanding of context and user intent.

Example:
Query "Running Shoes"
Keyword indexing: Only documents containing the exact phrase "running shoes" will be retrieved.
Semantic indexing: The finding results may include "jogging sneakers," "athletic footwear," or similar concepts.

Searching for "Artificial Intelligence"
Keyword indexing: Looking at the exact phrase "artificial intelligence" will be retrieved.
Semantic indexing: Results may include documents discussing "machine learning advancements," "smart systems," or similar topics.

Asking "Healthy Recipes"
Keyword indexing: Documents explicitly mentioning the phrase "healthy recipes" are indexed.
Semantic indexing: Documents related to the concept of nutritious cooking, even if they use different wording, are indexed.

Topic: "Global Warming"
Keyword indexing: Search for the exact phrase "global warming" will be retrieved.
Semantic indexing: Documents related to "climate crisis," "environmental changes," or related concepts.