Document Metadata Query Suggestion Generation
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Solution Overview
Problem
Information retrieval systems, such as search engines, face challenges in providing accurate query suggestions as they often rely on past user queries, failing to capture new information not previously requested, which limits the coverage of accessible information.
Innovation Solution
A method that involves obtaining metadata from documents, assigning tags based on grammatical relationships, determining grammatical correctness, and storing sequences of terms as query suggestions, along with calculating suggestion scores to provide relevant and meaningful query suggestions to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If query suggestions are taken from past user queries, then the system can provide suggestions based on actual user behavior, but it fails to capture new information that has not been previously requested
Solution Approach 1:
The system performs preliminary processing of document metadata to generate query suggestions in advance, rather than waiting for user queries to accumulate. By extracting and validating potential queries from document titles and metadata before they are needed, the system proactively builds a repository of meaningful query suggestions that represent uncovered information, resolving the contradiction between information coverage and system complexity
Solution Approach 2:
The system introduces an intermediary processing layer that uses part-of-speech tagging and grammatical validation to bridge between raw document metadata and usable query suggestions. This intermediary grammar checking mechanism filters and structures metadata to generate syntactically valid queries, enabling the system to expand information coverage while maintaining controlled complexity through a dedicated validation component
2Reliability
If the system processes metadata with grammatical validation, then it can generate meaningful query suggestions, but it increases processing time and computational resources
Solution Approach 1:
The system segments the metadata processing task into distinct stages: extracting individual terms from document titles, assigning part-of-speech tags to each term, and then combining tagged terms into grammatically valid queries. This segmentation allows each stage to be optimized independently and enables parallel processing of multiple documents, improving both quality and processing efficiency simultaneously
Solution Approach 2:
The system changes the parameter of grammatical validation from comprehensive sentence-level analysis to simpler part-of-speech tag-based validation. By using part-of-speech tags to determine grammatical correctness rather than full syntactic parsing, the system maintains sufficient quality for generating meaningful queries while dramatically reducing computational complexity and processing time
Data Source
AI summary
Methods, systems and apparatus are described herein that include obtaining metadata within a document, where the metadata comprises a sequence of terms. Tags are assigned to terms in the sequence of terms based at least in part on grammatical relationships between the terms, thereby forming a corresponding sequence of tags. A determination is made that the sequence of terms is grammatically correct based at least in part on tags within the corresponding sequence of tags. In response to the determination, the sequence of terms is stored as a query suggestion.