Real-time Adaptive Data Mining Across Unstructured Sources
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Solution Overview
Problem
Current data mining technologies are limited in analyzing real-time data across multiple sources, particularly failing to extract and analyze unstructured data from non-indexed web pages and proprietary data silos, which are essential for comprehensive and timely insights.
Innovation Solution
A data mining system that generates queries based on topics of interest, expands search terms, and monitors selected data sources for matches, including both open-source and proprietary data, using processors and memory units to execute queries and extract relevant data in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search engines are used to query data, then the system is simple to operate, but it cannot analyze multiple data points in real time and is limited to indexed web sites
Solution Approach 1:
The system segments the data mining process into distinct functional modules: query generation module, query expansion module, execution module, and monitoring module. Each module handles a specific aspect of data analysis, allowing the complex real-time analysis task to be divided into manageable components that can process multiple data points simultaneously across structured and unstructured sources
Solution Approach 2:
The data mining system is designed to handle multiple types of data sources (structured databases, unstructured web pages, proprietary data silos) and multiple query types through a unified platform. The system can simultaneously perform exact term matching, pattern recognition, and real-time monitoring across diverse data formats, making it universally applicable to various analysis scenarios without requiring separate specialized tools
2Loss of information
If search engines query only indexed web sites, then the search process is efficient, but seventy percent of web pages including proprietary data silos remain inaccessible
Solution Approach 1:
The system introduces intermediary components including parsers and data extractors that act as mediators between the query engine and unstructured data sources. These intermediaries translate unstructured content from proprietary data silos and non-indexed web pages into structured formats that can be queried and analyzed, enabling access to previously unreachable data while maintaining processing efficiency through automated extraction protocols
3Measurement precision
If comprehensive data from multiple sources is analyzed, then the insights are more accurate and timely, but the system complexity increases
Solution Approach 1:
The system merges multiple data sources including structured databases, unstructured web pages, and proprietary data silos into a unified analysis framework. By combining these diverse sources through a common query processing architecture, the system achieves comprehensive data coverage and improved analysis accuracy while managing complexity through integrated processing rather than separate systems
Data Source
AI summary
A method of analyzing data is presented. The method includes generating a query based on a topic of interest, expanding search terms of the query, executing the query on one or more data sources, monitoring a specific data source selected from the one or more data sources. The monitoring is performed to monitor for matches to the query.