Visual Rule Builder for Contextual Search in Electronic Records
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional techniques for retrieving information from electronic records, such as medical, financial, and legal records, fail to provide contextual understanding and statistical support for decision-making, and are not intuitive for users to construct complex logical rules.
Innovation Solution
A system that includes a searching unit with direct and contextual search capabilities, along with a visual interface for displaying results and a statistical analyzer, and a visual rule builder for constructing logical rules, allowing users to search and extract data based on context and statistical analysis, using a web-based platform with a server and client architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional techniques are used to retrieve information from electronic records, then basic search functionality is provided, but contextual understanding and statistical support are not provided
Solution Approach 1:
The search system is segmented into multiple functional units: a searching unit with direct and contextual search capabilities, a visual interface unit for displaying results, and a statistical analyzer unit for providing statistical support. This segmentation allows each unit to specialize in specific tasks, enabling comprehensive contextual information retrieval while maintaining manageable system complexity through modular design.
Solution Approach 2:
The search system is designed as a multi-functional platform that simultaneously performs direct searching, contextual searching, visual display, and statistical analysis. The searching unit can operate in multiple modes (direct search for exact matches, contextual search for surrounding text), and the system provides both retrieval and analytical functions, reducing the need for separate specialized tools.
2Reliability
If conventional techniques are used for information retrieval, then document retrieval is possible, but statistical support for decision-making is not provided
Solution Approach 1:
The statistical analyzer unit performs preliminary statistical analysis on retrieved documents, pre-calculating frequencies, distributions, and contextual patterns before the user makes decisions. This preliminary processing provides ready-to-use statistical support that enhances decision-making reliability without requiring additional manual analysis time, thereby maintaining productivity.
Solution Approach 2:
The system provides feedback through statistical analysis results that inform and improve decision-making processes. The statistical analyzer delivers information about document frequencies, contextual patterns, and distribution data that feed back into the user's decision-making, allowing for more informed and reliable choices while the automated nature of this feedback maintains processing efficiency.
3Ease of operation
If logical rules are constructed manually using conventional methods, then data extraction is possible, but the process is not intuitive and is difficult to visualize
Solution Approach 1:
The visual interface unit transforms the abstract, one-dimensional concept of logical rules into a two-dimensional visual representation. Rules are displayed as graphical elements with visible connections and structures, allowing users to see the relationships between different search criteria and logical operators. This dimensional transformation makes rule construction more intuitive and easier to understand while managing complexity through visual organization.
Solution Approach 2:
The system uses visual metaphors and graphical representations that copy familiar visual patterns from real-world concepts. Logical rules are represented using visual elements that resemble flowcharts or decision trees, making them intuitive to understand. This visual copying approach allows users to grasp complex rule structures through familiar visual patterns without requiring deep technical knowledge.
Data Source
AI summary
A web-based system for visual construction of logical rules includes a server, a network, and client operatively connected to the server via the network. The server includes a database and a search engine. The client includes a web-based visual rule building application including selectable windows for displaying and visually editing terms, logical operators, logical rules for storage in the database. The logical rules are generated by visually selecting at least one of the terms and logical operators from the windows. The server may further include a search engine configured to perform at least one of a direct search or a contextual search for an entered query string in records stored in the database and the client may include a visual interface for displaying results of the searches. The search results generated by the search engine may be stored as terms in the database for subsequent rule generation.