Data System High-Level Low-Level Indexing Disparate Sources
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Solution Overview
Problem
The challenge lies in discovering connections within vast amounts of publicly available structured and unstructured data sets stored in numerous independent systems and varying formats, making it impractical to acquire, search, and provide meaningful results due to their dispersed nature and format variations.
Innovation Solution
A data system and method that acquires, processes, and indexes structured and unstructured data sets using high-level and low-level indexing techniques, enabling efficient querying by creating a bridge network between relevant data sets through natural language processing and machine learning, allowing for efficient data retrieval and connection identification across disparate sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data are stored in numerous independent systems and locations with varying formats, then data availability and accessibility are improved, but data discovery and connection identification become impractical
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between disparate data sources and users. This system includes data acquisition components that collect data from multiple independent systems, processing components that standardize and index the data, and search components that enable unified querying. The intermediary translates between different data formats and structures, allowing users to access diverse data without directly interacting with each source system's complexity.
2Loss of information
If vast amounts of structured and unstructured data are acquired into a unified system, then data discovery capability is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and indexing data as it is acquired into the unified system. Data acquisition components collect data and immediately pass it to processing components that create indexes and metadata structures in advance. This preliminary indexing allows subsequent search operations to quickly locate and retrieve relevant data without performing full scans of the entire dataset, significantly reducing query processing time.
Solution Approach 2:
The patent segments the data processing system into distinct functional components: data acquisition modules that collect from specific sources, processing modules that index and standardize data, and search modules that query indexed data. This segmentation allows parallel processing of different data streams and enables the system to handle large volumes of data efficiently by distributing processing tasks across multiple specialized components.
3Productivity
If high-level and low-level indexing techniques are applied to all data sets, then search efficiency is improved, but device complexity and processing overhead increase
Solution Approach 1:
The patent applies local quality by implementing different levels of indexing strategies tailored to specific data types and search requirements. High-level indexes provide broad categorization and metadata for quick filtering, while low-level indexes provide detailed field-level indexing for precise searches. The system selectively applies appropriate indexing techniques based on the data characteristics and query patterns, rather than uniformly applying the most complex indexing to all data.
Data Source
AI summary
A system and method for content sharing includes acquiring, by a processing device, a plurality of data objects from data sources, storing the plurality of data objects in a data warehouse, generating a high-level index that is shared by the plurality of data objects, generating a plurality of low-level indices that each provides a respective low-level index for a respective one of the plurality of data objects, and providing the plurality of data objects on the content sharing platform for query or search using the high-level index and the plurality of low-level indices.