Electronic Document Generation from Disparate Data Sources
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Solution Overview
Problem
Enterprises face challenges in gathering and analyzing data from disparate sources, including structured and unstructured data scattered across multiple databases and file servers, which makes providing meaningful correlations and summarizations complex and resource-intensive.
Innovation Solution
A system and method for retrieving and analyzing data from internal and external sources to identify segments and topics, using a lexical database to determine contextual words and scores for relevance, generating electronic documents that summarize data efficiently and effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is gathered from multiple disparate sources (databases, file servers, user devices), then the completeness and coverage of information is improved, but the complexity of creating, searching, retrieving, and maintaining data increases
Solution Approach 1:
The patent merges data from multiple disparate sources (databases, file servers, user devices) into a unified data structure with standardized schemas. This consolidation allows comprehensive information gathering while simplifying management through a single integrated system rather than handling multiple separate sources independently.
Solution Approach 2:
The patent creates a universal data structure and schema framework that can accommodate various types of data sources and formats. This multi-functional approach allows the same system to handle structured data from databases, unstructured data from file servers, and semi-structured data from user devices, reducing the need for source-specific management procedures.
2Loss of information
If data is retrieved and analyzed from multiple sources to provide meaningful correlations and summarizations, then the quality of insights is improved, but the resource consumption (processors, memory, network bandwidth) increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and structuring data as it is ingested from various sources, organizing it into standardized schemas and relationships. This upfront preparation reduces the computational burden during analysis and retrieval operations, as data is already organized and indexed for efficient access rather than requiring intensive processing at query time.
Solution Approach 2:
The patent segments data into structured components with defined schemas and relationships, organizing information into manageable units that can be independently processed and analyzed. This segmentation allows selective retrieval and analysis of specific data portions rather than processing entire datasets, reducing overall resource consumption while maintaining insight quality.
3Measurement precision
If electronic documents are generated by processing data from multiple data sources with contextual analysis, then the relevance and accuracy of information is improved, but the processing time and computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-computing contextual relationships and scoring mechanisms during data ingestion and indexing. Contextual words, their frequencies, and relevance scores are calculated in advance rather than during document generation. This allows rapid assembly of relevant information when documents are created, maintaining high relevance and accuracy while significantly reducing processing time.
Data Source
AI summary
Implementations are directed to providing an electronic document, and include receiving text content including a plurality of segments, the text content being received from data sources, determining a set of topics to be included in the electronic document, for each topic in the set of topics, providing a set of contextual words associated with a respective topic, contextual words being determined from a lexical database, each contextual word having a respective frequency, determining a score for each segment and topic pair, the score indicating a relevance of a respective topic to a respective segment, each score being determined based on respective contextual words of the respective topic and frequencies of the respective contextual words, for each topic, providing, by the one or more processors, a summary including at least one segment based on respective score, and providing, to a user device, the electronic document including one or more summaries.