Weighted Identity Retrieval for Schema-Free Query Reliability
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Solution Overview
Problem
The challenge of querying unstructured or semi-structured data in databases is exacerbated by the lack of a formal model for storing and retrieving such data, particularly in NoSQL databases, where there are no guarantees regarding content type or data quality, leading to difficulties in processing data without a schema.
Innovation Solution
A weighted identity retrieval process that uses a domain model to apply variable weights to identifying properties during ingestion and search operations, leveraging vector-search capability and index-type-specific similarity-assessment to enable high-recall and high-precision querying of unstructured data, utilizing phonemic, temporal, and verbatim indexes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If unstructured or semi-structured data is stored without enforcing a schema, then data flow is maximized and data acceptance is improved, but querying reliability and data quality guarantees deteriorate
Solution Approach 1:
The patent segments the data retrieval process into multiple independent indexing stages (phonemic index, temporal index, verbatim index), each handling specific aspects of data representation. This allows the system to process unstructured data flexibly while maintaining reliable retrieval through multiple validation dimensions, resolving the contradiction between data acceptance and querying reliability.
Solution Approach 2:
The patent introduces variable weight parameters that can be adjusted during query processing to prioritize different indexing strategies. By changing the weight parameters based on data characteristics and query requirements, the system maintains high data acceptance while achieving reliable querying results through optimized parameter configuration.
2Adaptability or versatility
If no formal schema is imposed on incoming data, then data flow and flexibility are improved, but data quality and content type guarantees deteriorate
Solution Approach 1:
The patent replaces traditional mechanical schema validation with a vector-search based retrieval mechanism. Instead of rejecting data that doesn't conform to a predefined schema, the system uses phonemic, temporal, and verbatim indexes to enable flexible data acceptance while maintaining quality through intelligent retrieval algorithms that can handle varied data formats.
Solution Approach 2:
The patent introduces an intermediary indexing layer between data ingestion and query processing. The indexing system acts as a mediator that transforms unstructured data into multiple representational formats (phonemic, temporal, verbatim), enabling the system to accept diverse data while maintaining quality through standardized retrieval mechanisms.
3Measurement precision
If variable weights are applied to search terms, then search precision is improved, but the complexity of the retrieval model increases
Solution Approach 1:
The patent segments the retrieval model into independent indexing components (phonemic index, temporal index, verbatim index), each with its own weight parameters. This segmentation allows the system to achieve high search precision through weighted combinations of simple, well-defined retrieval operations, avoiding the complexity of a single complex model while maintaining precision.
Data Source
AI summary
A method, computer program product, and computing system for processing a query for obtaining data from an unstructured database. A parsed representation of a query field of the query is generated by parsing the query field from the query. A fuzzified representation of the query field is generated by fuzzifying the parsed representation of the query field. A vectorized representation of the query field is generated by vectorizing the fuzzified representation of the field. A matching input field is identified from the unstructured database by processing the vectorized representation of the query field. The matching input field is scored based upon, at least in part, weighting from a domain model. A weighted result is provided to the query using the scoring of the matching input field.