Ad-Hoc Data Analysis via Metadata Lookup Structure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for data analysis either lack speed and simplicity (search approach) or require time-consuming text mining steps (analytical approach), failing to provide true ad-hoc analysis that combines both speed and deep insights.
Innovation Solution
A system and method that generates a metadata lookup structure based on a text index, including metadata items such as date, link, author, and sentiment information, allowing for rapid searching and aggregation of data without separate text mining steps, using a computer server and user device to compile and report aggregate information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the search approach is used with a full-text index, then speed and simplicity are improved, but deep insights such as link analysis and sentiment information are lost
Solution Approach 1:
The patent applies preliminary action by generating a metadata lookup structure in advance during the indexing phase. This structure pre-computes and stores metadata information (such as link data, sentiment scores, language detection results) alongside the full-text index, so that when a search is performed, both the textual results and the enriched metadata are immediately available without requiring additional processing time.
2Loss of information
If the analytical approach with text mining algorithms is used, then deep insights and metadata information are improved, but speed and simplicity are worsened due to time-consuming processing
Solution Approach 1:
The patent applies preliminary action by generating a metadata lookup structure in advance during the indexing phase. This structure pre-computes and stores metadata information (such as link data, sentiment scores, language detection results) alongside the full-text index, so that when a search is performed, both the textual results and the enriched metadata are immediately available without requiring additional processing time.
Solution Approach 2:
The patent merges the full-text indexing process with metadata extraction by integrating multiple functions into a single indexing operation. Instead of separately running text mining algorithms after search, the system combines full-text indexing with metadata generation (link analysis, sentiment detection, language identification) into one unified process, creating a consolidated index structure that provides both search capability and analytical insights simultaneously.
3Loss of information
If separate text mining steps are performed for analysis, then deep insights are improved, but device complexity and operational complexity increase
Solution Approach 1:
The patent merges the full-text indexing process with metadata extraction by integrating multiple functions into a single indexing operation. Instead of separately running text mining algorithms after search, the system combines full-text indexing with metadata generation (link analysis, sentiment detection, language identification) into one unified process, creating a consolidated index structure that provides both search capability and analytical insights simultaneously.
Solution Approach 2:
The patent applies universality by designing an indexing system that performs multiple functions simultaneously: full-text indexing, metadata extraction, link analysis, sentiment detection, and language identification. This multi-functional index structure eliminates the need for separate analytical tools and processes, providing a universal solution that handles both search and analysis requirements within a single system framework.
Data Source
AI summary
It is a first aspect of the present invention to provide a computer implemented method of performing ad-hoc analysis including the steps of: generating a text index of the textual information items, generating a metadata lookup structure based, at least in part, on the text index, searching the text index using a search query, compiling results of the text index search into aggregate information related to characteristics of the search results from the metadata items associated with the textual information items in the search results from the metadata lookup structure, and reporting the aggregate information.