Entity Index Refinement Tree for Search Precision
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Solution Overview
Problem
Existing information retrieval systems face challenges in efficiently searching for named entities and proper nouns in large document collections, often resulting in voluminous and irrelevant search results, especially when users specify queries in natural language or by attributes, and lack collaboration features for team-based searches.
Innovation Solution
A system and method that generate an entity index with entity structures characterized by terms, allowing for cluster formation and refinement, enabling users to navigate a refinement tree for precise searches and leveraging prior user feedback for improved results, while facilitating collaborative searches by team members.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users search for named entities in large document collections using natural language queries, then the search capability is improved, but the search results become voluminous and irrelevant
Solution Approach 1:
The patent segments the search process into multiple stages: initial entity identification, cluster formation, and hierarchical refinement. Entity structures are divided into multiple terms (name, type, attributes) that can be independently processed and refined, allowing users to navigate from broad categories to specific entities through the refinement tree, thereby reducing irrelevant results while maintaining comprehensive search capability
Solution Approach 2:
The patent introduces a hierarchical dimension to traditional flat search results by organizing entities into clusters and refinement trees. This multi-level structure adds depth to the search results, allowing users to navigate through hierarchical levels (from general entity types to specific instances) and filter results dynamically, transforming voluminous flat results into structured, navigable hierarchies that improve relevance
2Ease of operation
If entity-based searching is performed without structured refinement, then search simplicity is maintained, but search precision deteriorates
Solution Approach 1:
The patent performs preliminary actions by automatically generating entity structures with multiple terms (name, type, attributes) and organizing them into clusters and refinement trees before the user conducts the search. This pre-processed hierarchical structure is ready for user navigation, eliminating the need for users to manually construct complex queries while maintaining precision through the structured refinement path
Solution Approach 2:
The refinement tree acts as an intermediary between simple keyword search and complex structured query construction. It provides a visual, navigable interface that mediates between user intent and precise entity retrieval, allowing users to refine searches by selecting nodes in the hierarchy without needing to understand complex query syntax or data structures
3Adaptability or versatility
If individual users conduct searches independently, then user autonomy is maintained, but collaborative knowledge sharing is lost
Solution Approach 1:
The patent implements feedback mechanisms where user search interactions (selections, refinements, navigation patterns) are captured and used to improve the search system. Collective user feedback refines entity clusterings and refinement trees over time, allowing individual users to benefit from aggregated group knowledge while maintaining their own autonomous search decisions and preferences
Data Source
AI summary
A system and method are provided for refining a user's query. An entity index, generated from a corpus of text documents, is provided. The entity index includes a set of entity structures, each including a plurality of terms. Each of the terms of an entity structure is a feature of the same entity. Entity structures can be retrieved from the entity index which match at least a portion of the user's query. Clusters of the retrieved entity structures are identified which have at least one of their terms in common. A cluster hierarchy is generated from the identified clusters in which nodes of the hierarchy are defined by one or more of the terms of the retrieved entity structures. At least a portion of the cluster hierarchy is presented to the user for facilitating refinement of the user's query through user selection of a node which, when formulated as a search, retrieves one or more responsive documents from the corpus of documents.