Unstructured Content Indexing via Vector Splitting

The patent introduces an intermediary indexing layer that sits between the conventional database and unstructured content. This intermediary structure uses features extracted from unstructured content (such as image features, text features, audio features) to create indexed representations that can be efficiently queried, while the original unstructured content remains stored in the conventional database without modification.

The patent transforms unstructured content into structured feature representations by extracting relevant parameters and characteristics. For example, images are converted to feature vectors, text is converted to term frequencies or embeddings, and audio is converted to spectral features. This parameter transformation enables the application of conventional indexing techniques to previously unindexable content.

The patent implements self-service indexing by automatically extracting features from unstructured content using computational algorithms. Instead of requiring manual tagging, the system autonomously analyzes content characteristics, extracts relevant features, and creates indexed representations. For example, automated image recognition algorithms extract visual features, natural language processing extracts text features, and audio analysis extracts sound features, eliminating the need for human intervention.

The patent replaces the mechanical process of manual feature tagging with automated computational systems. Machine learning models, pattern recognition algorithms, and data processing systems substitute human operators, transforming the tagging process from a manual, time-consuming activity to an automated, scalable process that can handle large volumes of unstructured content efficiently.

The patent performs preliminary feature extraction and indexing when content is initially ingested into the system. By pre-processing and extracting features at the time of content addition, the system prepares the data for future queries without requiring re-processing. This preliminary action ensures that when new query requirements arise, the pre-extracted features can be utilized or incrementally updated rather than requiring a complete re-scan of the entire collection.

The patent implements a dynamic indexing system that can adapt and update features incrementally based on query patterns and content changes. Rather than static, comprehensive re-tagging, the system dynamically adjusts by updating only the necessary portions of the index. This dynamic approach allows the system to maintain feature coverage while minimizing processing time through selective, incremental updates rather than complete re-processing.