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#semanticsearch — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #semanticsearch, aggregated by home.social.

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  1. Exciting to see LA Referencia do semantic search:

    "Search in your language. Discover research across languages."

    (with a friendly reminder that semantic search leverages AI techniques including NLP, ML, and embeddings...)

    la-referencia-ioi.github.io/la

    #OpenAccess #SemanticSearch

  2. Exciting to see LA Referencia do semantic search:

    "Search in your language. Discover research across languages."

    (with a friendly reminder that semantic search leverages AI techniques including NLP, ML, and embeddings...)

    la-referencia-ioi.github.io/la

    #OpenAccess #SemanticSearch

  3. Exciting to see LA Referencia do semantic search:

    "Search in your language. Discover research across languages."

    (with a friendly reminder that semantic search leverages AI techniques including NLP, ML, and embeddings...)

    la-referencia-ioi.github.io/la

    #OpenAccess #SemanticSearch

  4. Exciting to see LA Referencia do semantic search:

    "Search in your language. Discover research across languages."

    (with a friendly reminder that semantic search leverages AI techniques including NLP, ML, and embeddings...)

    la-referencia-ioi.github.io/la

    #OpenAccess #SemanticSearch

  5. Exciting to see LA Referencia do semantic search:

    "Search in your language. Discover research across languages."

    (with a friendly reminder that semantic search leverages AI techniques including NLP, ML, and embeddings...)

    la-referencia-ioi.github.io/la

    #OpenAccess #SemanticSearch

  6. I spent some time trying to make search behavior visible in one small Quarkus app.

    Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

    This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

    the-main-thread.com/p/full-tex

    #Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

  7. I spent some time trying to make search behavior visible in one small Quarkus app.

    Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

    This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

    the-main-thread.com/p/full-tex

    #Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

  8. I spent some time trying to make search behavior visible in one small Quarkus app.

    Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

    This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

    the-main-thread.com/p/full-tex

    #Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

  9. I spent some time trying to make search behavior visible in one small Quarkus app.

    Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

    This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

    the-main-thread.com/p/full-tex

    #Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

  10. I spent some time trying to make search behavior visible in one small Quarkus app.

    Full-text is good at exact terms. Vector search helps when user language and catalog language drift apart. Hybrid is usually the one I’d trust first in a real product search.

    This article walks through all three with Quarkus, PostgreSQL, Elasticsearch, Hibernate Search, and local embeddings.

    the-main-thread.com/p/full-tex

    #Java #Quarkus #PostgreSQL #Elasticsearch #SemanticSearch #HibernateSearch #VectorSearch

  11. pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

    ✨ Give the project a try on GitHub (and don't forget to star the project while you're there): github.com/pgEdge/pg_semantic_

    ➡️ Read more: pgedge.com/blog/pg_semantic_ca

    #postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

  12. pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

    ✨ Give the project a try on GitHub (and don't forget to star the project while you're there): github.com/pgEdge/pg_semantic_

    ➡️ Read more: pgedge.com/blog/pg_semantic_ca

    #postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

  13. pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

    ✨ Give the project a try on GitHub (and don't forget to star the project while you're there): github.com/pgEdge/pg_semantic_

    ➡️ Read more: pgedge.com/blog/pg_semantic_ca

    #postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

  14. pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

    ✨ Give the project a try on GitHub (and don't forget to star the project while you're there): github.com/pgEdge/pg_semantic_

    ➡️ Read more: pgedge.com/blog/pg_semantic_ca

    #postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

  15. pg_semantic_cache: an open-source extension that enables semantic query result caching in #PostgreSQL. Traditional caching requires exact query matches; this extension uses vector embeddings to find and retrieve cached results for semantically similar queries.

    ✨ Give the project a try on GitHub (and don't forget to star the project while you're there): github.com/pgEdge/pg_semantic_

    ➡️ Read more: pgedge.com/blog/pg_semantic_ca

    #postgres #data #llm #semanticsearch #ai #aiengineering #opensourceai #opensource

  16. Did you know? Our pgedge-vectorizer tool (on GitHub: github.com/pgEdge/pgedge-vecto) automatically chunks text content and generates vector embeddings with the help of background workers.

    OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (There’s even built-in views and functions for monitoring queue status.)

    #github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

  17. Did you know? Our pgedge-vectorizer tool (on GitHub: github.com/pgEdge/pgedge-vecto) automatically chunks text content and generates vector embeddings with the help of background workers.

    OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (There’s even built-in views and functions for monitoring queue status.)

    #github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

  18. Did you know? Our pgedge-vectorizer tool (on GitHub: github.com/pgEdge/pgedge-vecto) automatically chunks text content and generates vector embeddings with the help of background workers.

    OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (There’s even built-in views and functions for monitoring queue status.)

    #github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

  19. I'll be speaking at PHP Tek in May — two talks I've been building toward for a while.

    **Kubernetes for PHP Developers**: The translation guide from Docker Compose to production K8s. No 40-hour course required.

    **Semantic Search in Laravel**: Building search that understands meaning using pgvector and embeddings. Based on what I built for DailyMedToday.

    Both talks from production experience, not theory.

    Full details: eric.mann.blog/speaking-at-php

    #PHP #Kubernetes #Laravel #PHPTek #SemanticSearch