# How Computers Group Files Based on Meaning and Context > A system that organizes digital files and data into related groups by analyzing their meaning, context, and how they relate to one another. - **Patent:** US 20150206070 - **Original title:** Context based co-operative learning system and method for representing thematic relationships - **Owner:** Individual - **Status:** Active - **Times cited:** 17 - **Field:** software, ai_ml, ecommerce ## What it does The system acts as an intelligent librarian for digital data. It uses an identifier to index files and a context determinator to figure out what those files are actually about by analyzing their semantic and syntactic features. It then builds clusters of related objects and maps user search queries to these clusters to return highly relevant results. A key component is the co-operative learner, which allows different instances of the system to share what they have learned about themes and contexts to improve future search accuracy. ## What it does NOT cover - Does not cover simple keyword-based search engines that lack thematic clustering. - Does not cover hardware storage devices or physical data retrieval methods. - Does not cover systems that rely solely on user-provided tags without automated semantic analysis. - Does not cover real-time streaming data processing that does not involve indexing or clustering. ## The clever bit The system uses a co-operative learner that allows multiple independent systems to share their learned thematic associations, effectively creating a distributed intelligence network for data organization. ## Real-world examples 1. Enterprise document management systems 2. Smart database indexing tools 3. Advanced content recommendation engines ## Why it matters As data volumes grow, finding specific information becomes harder. This patent addresses the challenge of moving beyond basic keyword matching toward understanding the 'theme' of content, which is essential for modern enterprise search and knowledge management systems. ## Frequently asked questions ### What does How Computers Group Files Based on Meaning and Context cover? A system that organizes digital files and data into related groups by analyzing their meaning, context, and how they relate to one another. ### Who owns patent US 20150206070? This patent is owned by Individual. ### What is patent US 20150206070 cited by? This patent has been cited by 17 later patents that build on its ideas. ### What problem does this patent solve? As data volumes grow, finding specific information becomes harder. This patent addresses the challenge of moving beyond basic keyword matching toward understanding the 'theme' of content, which is essential for modern enterprise search and knowledge management systems. ### What does this patent NOT cover? Does not cover simple keyword-based search engines that lack thematic clustering. **Full plain-English explainer:** https://patentbrief.org/patent/us/20150206070/generative-adversarial-networks-gans **Original patent:** https://patents.google.com/patent/US20150206070 --- _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 Computers Find Hidden Connections Between Different Fields of Knowledge](https://patentbrief.org/patent/us/6523026/google-search-query-processing) — A method for finding related ideas in completely different subjects by using math to map how words appear together, even when the subjects use different vocabulary. - [How Computers Automatically Organize and Search Photos Using Contextual Data](https://patentbrief.org/patent/us/8862582/amazon-redshift) — A system for indexing images by attaching descriptive data to objects within them and adjusting search rankings based on how often a user searches for those specific items. - [Teaching Computers to Understand Document Similarity Using AI](https://patentbrief.org/patent/us/10909459/federated-learning) — This patent describes a way to train a computer program (a neural network) to understand how similar documents are to each other, by showing it examples and teaching it to group similar ones together and separate dissimilar ones. - [How Groupon Automatically Categorizes Merchant Services Using Text Analysis](https://patentbrief.org/patent/us/9330167/amazon-rds) — A system that automatically scans merchant websites and uses high-precision search queries to label their services, helping platforms like Groupon organize thousands of business listings. - [How Software Predicts What You Need Based on Your Coworkers](https://patentbrief.org/patent/us/7685160/ntfs-file-system) — A system that uses the browsing history and work habits of your colleagues to automatically build a personalized dashboard of links and content you are likely to need next.