Text Sample Entry Group Formulation for Rapid Search
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Solution Overview
Problem
Current methods for searching and filtering large volumes of information are inefficient, as they often require multiple scans and complex processes to identify relevant text components and sequences within text samples.
Innovation Solution
Assigning unique identifiers to text samples and components, creating text component entries, and organizing them into groups for efficient scanning, allowing for rapid searches through bitwise logical operations on bitmaps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional search methods are used to search through large volumes of information, then search functionality is provided, but multiple scans and complex processes are required, reducing search efficiency
Solution Approach 1:
The patent applies preliminary action by pre-processing text samples during ingestion to create optimized data structures (text component entries with identifiers, bitmaps, and sequential organization). This advance preparation enables rapid single-scan searches later, eliminating the need for multiple scans and complex processing during actual search operations.
Solution Approach 2:
The patent segments text samples into discrete text components with unique identifiers, organizing them into structured entries that can be independently processed and efficiently queried. This segmentation allows the search system to work with individual components rather than processing entire text samples, dramatically improving search speed.
2Productivity
If text samples are stored in original format, then storage simplicity is maintained, but searching requires multiple scans and complex processes
Solution Approach 1:
The system performs preliminary transformation of text samples into optimized data structures during the ingestion phase. Text samples are parsed, segmented into components, assigned identifiers, and organized into entries with associated bitmaps before storage. This advance processing creates the complexity upfront but enables simple, fast single-scan searches later.
Solution Approach 2:
The patent creates a copied and transformed representation of the original text samples in an optimized format (text component entries with identifiers and bitmaps). This copy enables efficient searching operations without requiring access to or processing of the original text format during search operations.
Data Source
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AI summary
Storing text samples in a manner that the text samples may be quickly searched. The text samples are assigned a text sample identifier and are each parsed to thereby extract text components from the text samples. Text components that have the same content are assigned the same text component identifier. For each parsed text component, a text component entry is created that includes the assigned text component identifier as well as the text sample identifier for the text sample from which the text component was parsed. A text sample entry group is created for each text sample that contains the text component entries in sequence for the text components found within the text sample. The text sample entry groups are stored so as to be scannable during a future search.