Entity-Specific Search Logic for Mixed-List Name Precision
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Solution Overview
Problem
Existing name-searching techniques in mixed-entity lists rely on basic string-similarity and token-alignment methods, which fail to produce intuitive results as they do not differentiate between various types of named entities, leading to suboptimal search outcomes.
Innovation Solution
The method involves categorizing names into entity-specific lists and applying specialized search logic tailored to each type of named entity, allowing for semantic, pragmatic, and syntactic evaluations unique to each category, thereby improving search precision and recall.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If basic string-similarity and token-alignment techniques are used for searching mixed-entity lists, then the search process is simple and fast, but the search results lack precision and do not match intuitive human outcomes
Solution Approach 1:
The patent segments the mixed-entity list into multiple entity-specific lists (e.g., personal names, organization names, product names, place names) based on entity types. Each list is then searched using specialized search logic tailored to that entity type, rather than applying a single generic search algorithm to all entities. This segmentation enables precise matching for each entity category while maintaining manageable complexity through modular search strategies.
Solution Approach 2:
The patent applies different search logic and scoring criteria to different entity types within the mixed list. For example, personal name search may prioritize phonetic similarity and common name patterns, while organization name search may emphasize exact matching and structural patterns. This local quality approach ensures that each entity type receives the most appropriate search treatment, improving overall precision without requiring a single overly complex universal algorithm.
2Adaptability or versatility
If a single common search logic is applied to all entity types in a mixed list, then the search system is simple to implement, but it cannot capture entity-specific properties and patterns leading to suboptimal results
Solution Approach 1:
The search system is segmented into multiple specialized search modules, each designed for a specific entity type. The system first categorizes entities in the mixed list by type, then routes queries to appropriate specialized search logic. This modular segmentation provides adaptability to different entity types while keeping each individual search module relatively simple and maintainable.
Solution Approach 2:
The patent creates a universal search framework that can handle multiple entity types through a common architecture. The framework includes entity type detection, dynamic search logic selection, and unified result aggregation, allowing a single system to adaptively serve multiple entity types with different search requirements without requiring separate independent systems for each entity category.
3Measurement precision
If entity-specific search logic is applied to each entity type, then search precision is improved, but the search system becomes more complex and harder to maintain
Solution Approach 1:
By segmenting the search system into entity-type-specific modules, the patent makes maintenance easier despite handling multiple entity types. Each module can be independently developed, tested, and updated without affecting other entity types. This modular segmentation isolates complexity into manageable units, improving maintainability while preserving high precision through specialized search logic for each entity category.
Data Source
AI summary
According to one embodiment of the present invention, a method for name searching in mixed-entity lists is provided which comprises dividing a mixed list of entities into a plurality of entity-specific lists. A name to be searched is then categorized into a category and a specialized search logic is applied to the name to be searched. The specialized search logic is selected to be adapted to the category and uses a one of the entity-specific lists that corresponds to the category of the name to be searched. A shared search logic may also be employed, which is used for all names to be searched.