Master Data Management Search Engine Selection
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Solution Overview
Problem
Current master data management systems face challenges in efficiently accessing and retrieving data records due to limitations in search engine performance and relevance, often requiring users to retry or reformulate search queries to obtain accurate results.
Innovation Solution
The integration of multiple search engines with different capabilities, such as full text and structured probabilistic search engines, within the master data management system, which selects the best combination of engines based on the input data and query type, and dynamically updates the selection rule based on user interactions to improve search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single search engine is used in the master data management system, then the system structure is simple, but the search performance and relevance are insufficient
Solution Approach 1:
The patent combines multiple search engines (full-text search engine and structured probabilistic search engine) into a single master data management system. The system selects and executes appropriate search engines based on the type of data and query, merging their capabilities to achieve superior search performance while managing complexity through intelligent selection rules.
Solution Approach 2:
The master data management system is designed to handle multiple types of data (structured and unstructured) using different search engines. The system universally applies search functionality across various data formats by selecting the appropriate engine based on data type, making the system multi-functional and adaptable to different search scenarios.
2Measurement precision
If multiple search engines are integrated into the master data management system, then the search results relevance is improved, but the system complexity increases
Solution Approach 1:
The system dynamically selects which search engines to execute based on the query type and data characteristics. Rather than always using all search engines, the system adapts its behavior in real-time, selecting only the relevant engines for each specific search task, thereby improving relevance while managing complexity through dynamic decision-making.
Solution Approach 2:
The system pre-establishes selection rules that determine which search engines should be used for specific data types and query patterns. These preliminary rules are set up in advance to guide the search engine selection process, reducing the need for complex real-time decisions and simplifying system operation while maintaining high search relevance.
3Adaptability or versatility
If the system uses fixed search engine selection rules, then the system operation is simple, but the search results may not adapt to changing user needs
Solution Approach 1:
The system incorporates feedback mechanisms that monitor search results and user interactions. Based on this feedback, the system can refine its selection rules and adapt to changing user needs over time. The feedback loop allows the system to learn from previous searches and improve future results without requiring manual reconfiguration, maintaining ease of operation while enhancing adaptability.
Data Source
AI summary
An approach for accessing multi-attribute data records of a master data management system. The method comprises: enhancing the master data management system with one or more search engines for enabling data record access. A request of data may be received at the master data management system. A set of one or more of the multiple attributes, referenced in the received request, may be identified. A combination of one or more of the search engines of the master data management system, whose performances for searching values of at least part of the set of attributes fulfil a current selection rule may be selected. And, the request may be processed using the combination of search engines. At least part of the results of the processing may be provided, and the selection rule may be updated based on user operations on the provided results, the updated selection rule becoming the current selection rule.