Adaptive Data Mining Query Expansion for Real-Time Analysis
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Solution Overview
Problem
Current data mining technologies are limited in analyzing real-time data across multiple sources, particularly due to the inability of typical search engines to index and query non-structured data sources, leading to incomplete and unsatisfactory results for real-time data analysis.
Innovation Solution
A method and apparatus for generating and expanding queries based on topics of interest, executing them across various data sources, including both open-source and proprietary data, and monitoring selected sources for matches, utilizing processors and memory units to perform data extraction and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If typical search engines are used to query data sources, then the search process is simple and fast, but the ability to analyze multiple data points in real time and access non-indexed data is limited
Solution Approach 1:
The system performs multiple functions within a single data mining platform: it executes structured queries like traditional search engines, continuously monitors non-indexed data sources for pattern changes, expands search terms using thesauruses, and analyzes unstructured data. This multi-functional approach resolves the contradiction by making the system both simple to use (query-based) and highly versatile (accessing multiple data types and sources).
Solution Approach 2:
The system dynamically adapts its data collection and analysis processes based on query results and identified patterns. It continuously monitors data sources and adjusts its monitoring scope and search term expansion based on real-time findings, enabling it to handle both structured and unstructured data effectively while maintaining real-time analysis capability.
2Loss of information
If search engines are limited to indexed web sites, then the search process is efficient, but the information obtained is incomplete as nearly seventy percent of web pages are not indexed
Solution Approach 1:
The system introduces intermediary components including a thesaurus database for term expansion and pattern identification, and automated monitoring agents that access non-indexed data sources. These intermediaries bridge the gap between structured query capabilities and unstructured data sources, enabling comprehensive information retrieval without requiring direct complex access to all data sources.
Solution Approach 2:
The system performs preliminary actions by continuously monitoring data sources and identifying patterns before queries are executed. It pre-processes and stores pattern information from non-indexed sources, so when a query is run, the system can quickly retrieve and analyze relevant pre-identified patterns, reducing the complexity of real-time analysis of unstructured data.
3Productivity
If traditional data mining approaches are used, then the system is simple to operate, but it cannot provide real-time analysis or expand search terms dynamically
Solution Approach 1:
The system performs self-service through automated query expansion using thesauruses and pattern recognition. When a user submits a query, the system automatically expands search terms, identifies related patterns from monitored data sources, and executes comprehensive analysis without requiring user intervention. This maintains ease of operation while dramatically increasing analysis speed and completeness.
Solution Approach 2:
The system implements feedback loops where query results are analyzed to identify patterns, which then inform subsequent query expansions and data source monitoring. The system continuously refines its search strategy based on feedback from data analysis, enabling real-time adaptation while keeping the user interface simple and easy to operate.
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.