Our other publications
Building a Custom BPM Worklist, Oracle InSync 2011 User Group presentation
Performance Tuning for Oracle Business Process Management Suite 10g, Oracle Whitepaper, July 2011
Performance Tuning for Oracle Business Process Management Suite 11g, Oracle Whitepaper, February 2013
Oracle BPM Suite 11g: Advanced BPMN Topics, Packt Publishing, September 2012
Fusion Middleware 12.1.2: Developing Applications with Continuous Integration
Fusion Middleware 12.1.3: Developing Applications with Continuous Integration
Tag Archives: graph
From GraphRAG Demo to Enterprise AI System with Oracle AI Database 26ai
Key Takeaways A useful AI answer needs more than similar text A support engineer asks what sounds like a straightforward question: Which maintenance policy applies to ACME’s pump 17 after the seal failure? A vector search workflow may get close. … Continue reading
From GraphRAG Demo to AI System: Build a Minimum Viable Knowledge Graph with Oracle AI Database 26ai
Key Takeaways In the first article, we built the mechanics of GraphRAG with Oracle AI Database 26ai. We parsed documents, created chunks, extracted entities and relationships, stored embeddings in VECTOR columns, defined a SQL property graph, and compared … Continue reading
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Tagged graph, graphrag, hybrid-query, ontology, oracle, taxonomy
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Four kinds of agent memory in Java with LangChain4j and Oracle AI Database
Key Takeaways In the first article, we gave a Java agent durable semantic memory: selected facts stored in Oracle AI Database and retrieved by meaning through LangChain4j. That is a useful starting point, but most agents need more … Continue reading
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Tagged agent, ai, episodic, graph, langchain4j, oracle, procedural, semantic
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Implementing GraphRAG with Oracle AI Database 26ai: SQL Property Graphs, Vector Search, and Automated Graph Extraction
Key Takeaways Standard vector Retrieval-Augmented Generation, or RAG, retrieves chunks that are semantically similar to a question. That works well when the answer appears in a compact passage whose wording is close to the question. It becomes harder to inspect … Continue reading
From Graph Patterns To Analytics And Visualization
GRAPH_TABLE is the right first tool because it demonstrates the core idea: match a graph pattern and return rows. But graph work often goes one step further. You may want to rank important accounts, find connected groups, trace weighted paths, … Continue reading
Detect Fraud Patterns With Graphs
We have tables. We have a SQL property graph named BANK_GRAPH. Now we can ask graph-shaped questions. The key tool is GRAPH_TABLE. GRAPH_TABLE is a SQL table expression. You give it a graph and a pattern to match, and it … Continue reading
Build Your First SQL Property Graph In Oracle AI Database 26ai
The first article introduced the graph idea: vertices are things, edges are relationships, and properties describe both. Now we will build one. The easiest way to learn SQL property graphs in Oracle AI Database 26ai is to start with ordinary … Continue reading
What Is a Graph in Oracle AI Database 26ai?
If you have ever asked, “How is this thing connected to that thing?”, you have already asked a graph question. A customer sends money to an account. That account sends money to two other accounts. One of those accounts sends … Continue reading
Exploring Oracle’s new AI Agent Memory Python Library with OpenAI
Hi everyone! In this post, I want to show you a small but useful demo application that uses Oracle AI Agent Memory from Python. The complete code for this example is in the agent-memory repository. You can learn more about … Continue reading
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