Natural Language Search Indexing via Object Graph Path Analysis
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Solution Overview
Problem
Natural language searches for variables face challenges in achieving high accuracy and speed of response, which are crucial for enhancing user experience in electronic information systems.
Innovation Solution
An apparatus and method utilizing a processor to search an index containing information about variables, employing key words and context from user queries, mapping documents as nodes in an object graph, identifying paths, filtering based on user criteria, and ranking results for timely and accurate information display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If natural language search uses comprehensive indexing and processing of multiple documents, then search accuracy improves, but response time increases
Solution Approach 1:
The patent segments the search process into multiple phases: initial broad search using keywords, followed by contextual filtering and ranking. The object graph is divided into nodes representing different document types and relationships, allowing selective traversal based on user criteria. This segmentation enables the system to process only relevant portions of the index, improving accuracy while controlling response time.
Solution Approach 2:
The system performs preliminary actions by pre-processing and indexing documents into an object graph structure before actual search queries are received. Metadata about documents, their relationships, and contextual information is organized in advance, allowing rapid retrieval and filtering during actual search operations. This preliminary organization enables fast response times while maintaining comprehensive search capabilities.
2Loss of information
If the system processes more documents and relationships to ensure accurate answers, then information completeness improves, but processing complexity increases
Solution Approach 1:
The patent introduces a hierarchical dimension to document organization through the object graph structure. Documents are arranged in layers based on their relationships and importance, with root nodes representing top-level concepts and child nodes representing detailed information. This dimensional organization allows the system to traverse only relevant layers based on user criteria, maintaining information completeness while reducing processing complexity by ignoring irrelevant lower-level details.
Solution Approach 2:
The search processing is made dynamic by adjusting the depth and scope of document traversal based on user-specific criteria and preferences. The system dynamically determines which nodes and relationships to explore based on the query context and user profile, rather than processing all documents uniformly. This dynamic approach ensures complete information retrieval when needed while simplifying processing when user criteria allow for more limited search scopes.
3Reliability
If the system filters and ranks paths based on user criteria, then answer relevance improves, but processing time increases
Solution Approach 1:
The system applies partial filtering and ranking actions by evaluating only the most relevant paths and nodes based on user criteria. Rather than processing every possible path through the complete object graph, the system identifies and processes a representative sample of high-relevance paths, achieving sufficient answer relevance without the time cost of exhaustive processing. This partial action approach balances reliability with processing time efficiently.
Data Source
AI summary
A method for natural language search for variables is provided. The method may include searching an index using key words from a user's natural language question and the context of the user's question. The index may reference variables and/or web service calls in a domain model. The method may also include saving documents obtained in response to the search. The method may also include mapping each of the documents as a node into an object graph. Each node may be associated with a parent node, except when the node is a root node. The method may also include identifying the root node of each document. The method may also include identifying the path of each node from the node to the node's root node. The method may also include identifying matching paths. Each matching path may provide an answer to the user's question.