Data Ranking via Group Concordance Indicators
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Solution Overview
Problem
The rapid growth of data records makes it difficult to efficiently and intuitively query databases, leading to delays and inefficiencies in retrieving relevant information, as traditional methods struggle to handle large volumes of complex data effectively.
Innovation Solution
A computer-implemented method that assigns records to in-groups and out-groups based on queries, generating user interfaces that highlight relevant words and indicators of discriminative power, allowing for real-time querying and updating of views, thereby enhancing query efficiency and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional database querying methods are used on large databases, then the system can store and manage large volumes of data, but the query response time increases and user experience deteriorates
Solution Approach 1:
The patent segments the large database into multiple partitions or shards, allowing queries to be processed in parallel across different segments. This reduces the time required to scan and process large volumes of data while maintaining the ability to store extensive data quantities.
Solution Approach 2:
The system performs preliminary actions by pre-computing and storing query results, query plans, or data summaries in advance. This allows the system to quickly retrieve pre-processed information without performing full data scans during actual query execution, significantly reducing response time for common query patterns.
2Measurement precision
If comprehensive data analysis is performed on all records, then the accuracy of query results improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies local quality by analyzing and processing only the specific portions of data relevant to each query rather than performing comprehensive analysis on all records. This allows the system to maintain high accuracy for query-specific results while reducing overall computational complexity through selective processing.
Solution Approach 2:
The system performs partial analysis by focusing computational resources on the most relevant data subsets for each query. Rather than analyzing all possible data, the system identifies and processes only the necessary portions, achieving sufficient accuracy without the full computational burden of exhaustive analysis.
3Ease of operation
If real-time query processing is implemented, then user satisfaction improves, but the system requires more computational resources and increases operational complexity
Solution Approach 1:
The patent implements periodic action through scheduled batch processing for non-critical queries and caching mechanisms that refresh data periodically. This allows the system to provide real-time responses for urgent queries while using periodic background processing for less time-sensitive operations, reducing peak computational resource consumption while maintaining user satisfaction.
Data Source
AI summary
A computer implemented method of ranking items of data stored in a database comprising a plurality of records, wherein each record is associated with one or more items of data. The method includes generating a concordance of the items of data associated with the records in the database. Each record is assigned to a first group of records or to a second group of records. For each item of data a first indicator is determined representative of its occurrences in the records of the first group. For each item of data a second indicator is determined representative of its occurrences in the records of the second group. For each item of data a score is determined representative of a discriminative power of that item of data on the basis of the first and second indicator of that item of data.