Search Engine for Cross-Domain Case Recombination
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Solution Overview
Problem
Traditional case study methods limit learners to applying existing solutions within the same field, lacking the ability to devise new solutions and gain practical experience in combining diverse case studies for innovative problem-solving.
Innovation Solution
A search engine that presents a list of topics related to a first object with a goal, determines second objects sharing a common attribute, and searches for cases teaching solutions to achieve the goal, allowing users to combine parts from different cases for innovative solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If learners study only one case at a time within the same field, then they can deeply understand existing solutions, but they cannot devise new solutions or gain experience in combining diverse cases
Solution Approach 1:
The system segments cases into distinct components including problem statements, solutions, and key attributes. This allows learners to analyze individual case elements separately and then recombine them in novel ways, fostering innovative solution development while maintaining manageable complexity through structured organization
Solution Approach 2:
The search engine performs multiple functions: it searches for cases based on various criteria, identifies similar cases across different fields, extracts relevant attributes, and presents combined results. This multi-functional approach enables diverse case exploration without proportionally increasing complexity, as the system integrates these functions into a unified platform
2Adaptability or versatility
If learners are exposed to diverse case studies from different fields, then they can develop innovative solutions, but the complexity of searching and analyzing multiple cases increases
Solution Approach 1:
The system pre-organizes cases by attributes, industries, and problem types before user queries. Cases are tagged with metadata and structured in advance, allowing the search engine to quickly retrieve relevant diverse cases without requiring learners to manually search through extensive collections, thereby reducing time loss while maintaining exposure to diverse perspectives
Solution Approach 2:
The search engine acts as an intermediary between learners and the vast repository of case studies. It automatically filters, retrieves, and presents relevant cases based on user goals, eliminating the need for learners to manually search and sort through numerous cases across different fields, thus reducing time investment while enabling access to diverse innovative examples
3Ease of operation
If traditional search engines are used to find cases, then simple keyword searches are possible, but additional functionality to view and combine parts of different cases is lacking
Solution Approach 1:
The system merges multiple case studies into unified views, allowing learners to see connections and combine elements from different cases. It integrates problem statements, solutions, and key attributes from multiple sources into comprehensive presentations that facilitate innovative solution development while maintaining ease of operation through a unified interface
Solution Approach 2:
The system implements nested viewing capabilities where individual case elements (problems, solutions, attributes) are contained within case studies, which are in turn contained within broader case collections. This nested structure allows learners to drill down from overview to detailed analysis and easily extract and combine specific elements without overwhelming complexity
Data Source
AI summary
In a method of searching for cases, a list of topics is presented by a computer for selection of one of the topics by a user. The one selected topic relates to a first object and is associated with a goal. At least one second object is determined by the computer. The at least one second object differs from the first object but includes a same attribute as the first object. The computer searches for cases that teach solutions for achieving the goal for the at least one second object. Cases that resulted from the searching are presented by the computer to the user.