Multi-Level Entity Search for Accurate Subsidiary Identification
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Solution Overview
Problem
Business entities often have complex structures that are difficult for outsiders to navigate, making it challenging to identify the appropriate subsidiary for engagement.
Innovation Solution
A multi-level search algorithm is applied by an entity identification computer program to identify target entities based on transaction information, entity search terms, requestor information, and entity preferences, providing contact information and suggesting suitable individuals for transactions while managing conflicts of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-level search algorithm is applied to identify target entities, then the precision of entity identification is improved, but the complexity of the system increases
Solution Approach 1:
The search algorithm is divided into multiple levels (first level, second level, third level) where each level performs a specific search operation with increasing precision. The first level searches for exact name matches, the second level searches for partial name matches, and the third level searches for related entities, allowing the system to progressively refine results without overwhelming complexity at each stage
Solution Approach 2:
The system performs preliminary searches at broader levels before narrowing down to more specific searches. By first searching for exact matches and then progressively expanding to partial matches and related entities, the system prepares the search space in advance and filters results incrementally, improving precision while managing computational complexity
2Measurement precision
If multiple search levels are used to refine entity identification, then the accuracy of contact information retrieval is improved, but the time required for the search process increases
Solution Approach 1:
The search process is structured as a series of periodic search levels that execute sequentially. Each level completes its search operation and returns results before the next level begins, allowing the system to periodically refine the search criteria and results rather than performing a single exhaustive search, thereby balancing accuracy with time efficiency
Data Source
AI summary
A method may include: (1) receiving, by an entity identification computer program executed by a backend and from a requestor via a requestor electronic device, transaction information and an entity search term for a desired entity; (2) receiving, by the entity identification computer program, requestor information for the requestor; (3) receiving, by the entity identification computer program, entity preferences for an organization or for the requestor; (4) applying, by the entity identification computer program, a multi-level search algorithm to identify a target entity using the transaction information, the entity search term, the requestor information, and the entity preferences; (5) receiving, by the entity identification computer program, an indication that the target entity is the desired target entity; (6) retrieving, by the entity identification computer program, contact information for the target entity; and (7) returning, by the entity identification computer program, the contact information to the requestor.