Semantic Search Parsing for Structured Database Queries
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Solution Overview
Problem
Current search methods for structured databases, such as social networking and job searching platforms, are inefficient as they require users to choose between advanced search forms and keyword searching, leading to either excessive time consumption or irrelevant results due to misspelling and omission of synonyms.
Innovation Solution
A method that allows users to enter a search query in a single box, which is automatically parsed and expanded to include similar terms, and then searched across structured database fields, ensuring relevant results by classifying search query components and including synonyms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users employ advanced search forms with multiple fields, then search precision is improved, but device complexity and ease of operation deteriorate due to the need to navigate multiple forms and understand field mappings
Solution Approach 1:
The system segments the unstructured search query into multiple structured attributes automatically, dividing the search task into organized components without requiring user intervention. The parser module breaks down the query string into distinct attributes like job title, location, and skills, mapping them to appropriate database fields automatically.
Solution Approach 2:
The patent introduces a parser module and search term attribute dictionary as intermediary components between the user's simple query and the complex database structure. This intermediary automatically translates natural language queries into structured search attributes, bridging the gap between user convenience and database precision.
2Ease of operation
If users employ keyword searching, then ease of operation is improved, but measurement precision deteriorates due to misspelling and omission of synonyms
Solution Approach 1:
The system performs preliminary actions by pre-processing the search query to expand terms with synonyms and related concepts before executing the search. The expansion module adds alternative terms and synonyms to the search attributes, ensuring that variations and misspellings are accounted for in advance of the actual database search.
Solution Approach 2:
The patent changes the parameters of the search by dynamically expanding search attributes with multiple synonymous terms and related concepts. Instead of searching for a single term, the system transforms the search parameters to include multiple equivalent expressions, thereby maintaining precision while preserving the simplicity of keyword-based input.
3Measurement precision
If the system expands search attributes with synonyms, then search precision is improved, but loss of time increases due to processing additional terms
Solution Approach 1:
The system applies partial expansion by selectively adding synonyms and related terms based on the specific search attributes and context, rather than expanding all possible terms universally. This targeted approach ensures sufficient search coverage without the overhead of exhaustive term expansion, balancing precision with processing efficiency.
Data Source
AI summary
Disclosed in one example is a method for searching. In some examples, the method includes receiving an unstructured search query, parsing the unstructured search query into a plurality of structured search attributes using a search term attribute dictionary, performing a search of a structured database based upon the plurality of structured search attributes to identify a plurality of search results, populating a plurality of form fields of a search form with the plurality of structured search attributes, and displaying the search form in association with the search results.