# How to Combine Information from Multiple Knowledge Graphs > This patent describes a method for merging information from two or more existing knowledge graphs into a single, unified knowledge graph, using special rules called "graph operators." - **Patent:** US 20240144032 - **Original title:** Knowledge graph data fusion - **Owner:** Alipay Hangzhou Information Technology Co - **Status:** Active - **Times cited:** 4 - **Field:** software, telecommunications, ecommerce, ai_ml, finance ## What it does The patent outlines a method for combining information from different knowledge graphs. First, it obtains a "target entity field" (like "person" or "product") and a "target relationship description" (like "works for" or "buys") from the "ontology definition data" of two or more existing knowledge graphs (Claim 1). Then, it determines "graph operators" which are specific rules for combining these fields and relationships (Claim 1). It gathers "data instances" (actual data, like "John Doe" or "iPhone") corresponding to these fields and relationships from the original graphs (Claim 1). Finally, it uses the graph operators to process these data instances and create a "fused knowledge graph" (Claim 1). For example, if one graph has "customer" and another has "user," a graph operator could fuse them into a single "customer/user" entity, standardizing how their attributes are expressed (Claim 5). ## What it does NOT cover - Does not cover fusing data that is not structured as a knowledge graph with defined entities and relationships. - Does not cover data fusion methods that do not use specific "graph operators" to process data instances. - Does not cover combining knowledge graphs without first selecting target entity fields and relationship descriptions from their ontology definitions. - Does not cover simple data aggregation without creating a new, fused knowledge graph structure. - Does not cover fusion where the operators are not determined either by user input or automatic generation (Claim 3). ## The clever bit The novelty lies in systematically using "graph operators" to not just combine raw data, but to specifically fuse the *ontology definition data* (the blueprints) and then process the *data instances* (the actual facts) from multiple knowledge graphs, ensuring a coherent and structured merged result. ## Real-world examples 1. Combining customer data from an e-commerce platform and a payment system. 2. Merging product catalogs from different suppliers in a supply chain. 3. Integrating medical research data from various hospital systems. 4. Creating a unified view of financial transactions from multiple banking services. ## Why it matters In today's world, information is often scattered across many different databases and systems. This patent provides a structured way to bring together knowledge from various sources, like different departments in a company or various online platforms. This allows for a more complete understanding of complex topics, making it easier to find connections and draw conclusions that wouldn't be possible with isolated data. ## Frequently asked questions ### What does How to Combine Information from Multiple Knowledge Graphs cover? This patent describes a method for merging information from two or more existing knowledge graphs into a single, unified knowledge graph, using special rules called "graph operators." ### Who owns patent US 20240144032? This patent is owned by Alipay Hangzhou Information Technology Co. ### When does this patent expire? This patent is expected to expire on December 20, 2043, when the invention enters the public domain. ### What is patent US 20240144032 cited by? This patent has been cited by 4 later patents that build on its ideas. ### What problem does this patent solve? In today's world, information is often scattered across many different databases and systems. This patent provides a structured way to bring together knowledge from various sources, like different departments in a company or various online platforms. This allows for a more complete understanding of complex topics, making it easier to find connections and draw conclusions that wouldn't be possible with isolated data. ### What does this patent NOT cover? Does not cover fusing data that is not structured as a knowledge graph with defined entities and relationships. **Full plain-English explainer:** https://patentbrief.org/patent/us/20240144032/knowledge-graph-data-fusion **Original patent:** https://patents.google.com/patent/US20240144032 --- _Source: PatentBrief — https://patentbrief.org. Patent facts are from public records; the plain-English explanation is PatentBrief's._ ## Related patents Semantically similar inventions in the PatentBrief corpus: - [How AI Connects Different Databases Using Knowledge Graphs](https://patentbrief.org/patent/us/11507851/system-and-method-of-integrating-databases-based-on-knowledge-graph) — This patent describes a server-based method that uses artificial intelligence and two learning models to automatically find and integrate connections between data fields and data values across multiple databases that have different structures. - [Improving AI Language Understanding with Aligned Knowledge Graphs](https://patentbrief.org/patent/us/11798529/generation-of-optimized-knowledge-based-language-model-through-knowledge-graph-m) — This patent describes a method for making AI language models smarter by combining them with knowledge modules, which learn from two different, but related, knowledge graphs. - [How Assistant Systems Combine Information About One Thing from Many Places](https://patentbrief.org/patent/us/11704899/resolving-entities-from-multiple-data-sources-for-assistant-systems) — This patent describes a system that gathers all known information about a single person, place, or thing from various sources and combines it into one complete profile for an assistant system. - [How Computers Match and Join Messy Data from Different Sources](https://patentbrief.org/patent/us/9607103/amazon-athena) — A method for merging datasets by identifying related but non-identical items using flexible matching rules rather than strict equality. - [Industrial Equipment Data Organized into Smart Knowledge Graphs](https://patentbrief.org/patent/us/20230195095/industrial-knowledge-graph-and-contextualization) — Honeywell's patent describes a system that collects data from industrial equipment, makes sense of it using rules, and organizes it into a smart graph for better control and actions.