Oracle Patent Application US20260099533A1 Topic Maps for Raw Content
Summary
USPTO published patent application US20260099533A1 assigned to Oracle International Corporation on April 9, 2026. The application covers techniques for receiving, storing, and analyzing raw text content using topic maps, including normalizing input text, identifying topics via tags, and generating topic maps referencing content items. Filing date was November 24, 2025; application number 19398208.
What changed
Oracle International Corporation filed patent application US20260099533A1 for raw content storage and analysis using topic maps. The system receives raw text with tags, normalizes the input by removing formatting attributes, stores normalized content in target datasets, and parses tags to identify topics and computing system associations. The patent generates topic maps referencing content items within datasets.
Technology companies and AI developers should monitor Oracle's IP portfolio for topic mapping and content analysis technologies. While patent publications do not create immediate compliance obligations, they signal competitive positioning in AI-driven natural language processing and data organization. Entities developing similar systems should conduct freedom-to-operate analyses.
Archived snapshot
Apr 18, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Raw Content Storage and Analysis Using Topic Maps
Application US20260099533A1 Kind: A1 Apr 09, 2026
Assignee
Oracle International Corporation
Inventors
Jean-Francois Verrier
Abstract
Techniques for receiving, storing, analyzing, and utilizing raw content are disclosed. The system receives raw text from a user, including a first tag and second tags. The system identifies and removes formatting attributes in the raw text, including whitespace characters, to generate a normalized input. The system stores the normalized input in target dataset(s) and parses the normalized input for the first tag and the second tags. In this case, the first tag corresponds to one or more topics, and the second tags represent a computing system associated with corresponding portions of the normalized input. The system analyses the first tag and the second tags to identify the topics. The system generates one or more topic maps for the target dataset(s) based on the first tag and the one or more second tags. The topic map(s) include one or more references to content items within the target dataset(s).
CPC Classifications
G06F 16/358 G06F 16/3329 G06F 16/3334 G06F 40/103 G06N 3/0475
Filing Date
2025-11-24
Application No.
19398208
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