Entity Descriptor Standardization for Query Performance
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Solution Overview
Problem
Data processing systems face inefficiencies when dealing with large amounts of textual data containing inconsistent and non-standardized entity descriptors, leading to increased computing resources and processing time for queries and analytical operations.
Innovation Solution
A text transformation system that standardizes entity descriptors by applying a series of transformation operations, including preprocessing, tokenization, and lookup table-based standardization, to generate indexed datasets that allow for faster querying and reduced resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If entity descriptors are standardized using transformation operations, then query performance and data processing efficiency are improved, but device complexity and processing time for transformation are increased
Solution Approach 1:
The patent applies preliminary action by pre-processing entity descriptors through tokenization, normalization, and standardization operations before they are stored in the dataset. This transforms raw descriptors into standardized forms in advance, so that subsequent queries can operate on already-processed data, improving query performance without requiring complex processing during actual queries.
Solution Approach 2:
The patent introduces intermediary components including a transformation module that mediates between raw entity descriptors and the standardized dataset, and an index structure that mediates between standardized descriptors and stored records. These intermediaries organize and standardize data systematically, improving overall system efficiency while managing complexity through modular design.
2Loss of energy
If entity descriptors are standardized using transformation operations, then computing resources required for processing are reduced, but processing time for transformation is increased
Solution Approach 1:
The transformation operations (tokenization, normalization, standardization) are performed in advance during data ingestion or batch processing, converting entity descriptors into standardized forms before they need to be queried. This shifts the processing time burden to the transformation phase, while subsequent queries operate on pre-processed data, reducing computing resources during actual query operations.
3Speed
If indexed datasets with standardized entity descriptors are used, then search speeds are improved, but data processing system complexity is increased
Solution Approach 1:
The patent segments the entity descriptor processing into distinct components: tokenization (breaking descriptors into tokens), normalization (standardizing token forms), and standardization (mapping to standardized entity types). Each component handles a specific aspect of transformation, improving search speed through systematic processing while managing complexity through clear separation of concerns.
Solution Approach 2:
The patent adds an indexing dimension to the data structure, creating an index that maps standardized entity descriptors to record locations. This additional dimensional organization enables fast retrieval by standardized descriptor without requiring linear search through all records, significantly improving search speed while the index structure manages the complexity of mapping relationships.
Data Source
AI summary
In some aspects, a computing system can receive, from a client device, a request to perform an analytical operation that involves a query regarding a common entity type. The computing system can extract a query parameter having a particular standardized entity descriptor for the common entity type and parse a transformed dataset that is indexed in accordance with standardized entity descriptors. The computing system can match the particular standardized entity descriptor from the query to records from the transformed dataset having index values with the particular standardized entity descriptor. The computing system can retrieve the subset of the transformed dataset having the index values with the particular standardized entity descriptor. In some aspects, the computing system can generate the transformed dataset by performing conversion operations that transform records in a data structure by converting a set of different entity descriptors into a standardized entity descriptor for the common entity type.