Categoría: Search
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Semantic Search vs. Keyword Search: What’s the Difference?
When you search for something online, you expect the search engine to understand what you mean, not just what you type. You want it to grasp the context, the nuance, and the intent behind…
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Building Smarter Agents: How Vector Search Drives Semantic Intelligence
The way we search and interact with information has shifted dramatically over the past decade. Traditional keyword-based search engines once served us well in finding documents or answers, but today’s business challenges demand much…
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Introducing Couchbase as a Vector Store in Agno
We’re excited to announce that Couchbase is now supported as a vector store in Agno. This integration brings together the best of Agno’s agent orchestration capabilities and Couchbase’s high-performance, scalable vector store. It allows…
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Semantic Similarity with Focused Selectivity
Why does semantic search need selectivity? Up until now, we’ve viewed a vector embedding as a complete, stand-alone entity – focused entirely on the meaning it encodes. While this enables semantic search, often with…
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Cracking the Code on Quality Control with Vector Search
There is a good chance you encounter vector search regularly, even if you are not building applications with it. Discovering content recommendations based on previous liked content is a common use case of vector…
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Transformando Experiências no Varejo com Couchbase Mobile e Google GenAI
Imagine entrar em uma loja de varejo onde a experiência parece feita sob medida para você. Enquanto percorre os corredores, displays digitais exibem promoções e recomendações personalizadas com base em suas preferências. O pagamento…
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Transforming Retail Experiences with Couchbase Mobile and Google GenAI
Imagine, you walk into a retail store and the experience feels tailored just for you. Browsing through the aisles, digital displays showcase personalized promotions and recommendations based on your preferences. Checking out is seamless,…
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Enhancing Performance Using XATTRs for Vector Storage and Search
With the introduction of vector search, users can now store large vector arrays—often made up of seemingly arbitrary numbers—within their documents. Since this data isn’t required for most standard queries, users can now leverage…
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Get Started With Couchbase Vector Search In 5 Minutes
What is a Vector A Vector is an object that represents a real-world item as an array of floating numbers. Each item in the real world is represented in Vector format(as an array) and…
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Querying Vectors And Things That Can Go Wrong With Them
Couchbase 7.6 introduces Vector Search into the Couchbase architecture, expanding its search capabilities by leaps and bounds. This article showcases how this affects search queries, how we have to adapt in certain situations and…
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Hybrid Search: An Overview
What Is Hybrid Search? Hybrid search typically refers to a search approach that combines multiple search methodologies or technologies to provide more comprehensive and accurate results. In the context of information retrieval, hybrid search…
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Twitter Thread tl;dr With AI? Part 2
In part 1 we saw how to scrape Twitter, turn tweets in JSON documents, get an embedding representation of that tweet, store everything in Couchbase and how to run a vector search. These are…