IP Document Search with Weighted Keyword and Related-Term Ranking
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Solution Overview
Problem
Existing document search systems struggle with achieving highly accurate searches, particularly for intellectual property documents, due to the difficulty in selecting appropriate keywords and related terms, leading to inconsistent search results based on user skill and potential oversights.
Innovation Solution
A document search system that includes a processing portion capable of extracting keywords and related terms, assigning weights based on inverse document frequency and similarity degrees, scoring, and ranking data for accurate output, utilizing artificial intelligence and neural networks for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated keyword extraction and weighting is implemented, then search accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the search process into distinct functional modules: keyword extraction module, related term extraction module, weighting module, scoring module, and ranking module. Each module performs a specific task, making the overall complex system manageable and maintainable while achieving high search accuracy through coordinated operation of these segmented components.
Solution Approach 2:
The system introduces intermediate data structures and processing layers between user input and final results. Keywords and related terms serve as intermediaries that bridge the gap between simple search queries and complex document analysis, enabling accurate matching while abstracting the complexity from the user interface.
2Reliability
If multiple processing functions are integrated, then search quality is improved, but ease of operation deteriorates
Solution Approach 1:
The system merges multiple search functions (keyword extraction, related term extraction, weighting, scoring, and ranking) into a single integrated processing portion. This consolidation allows the system to perform complex multi-step analysis automatically without requiring users to manually execute each function, thereby maintaining high search quality while preserving ease of operation through automation.
Solution Approach 2:
The system performs self-service by automatically extracting keywords, identifying related terms, assigning weights, calculating scores, and ranking results without user intervention. The processing portion autonomously executes the entire search pipeline, eliminating the need for users to manually configure multiple parameters or functions while delivering high-quality search results.
Data Source
AI summary
A highly accurate document search, particularly a search for a document relating to intellectual property, is achieved with an easy input method. A document search system includes a processing portion. The processing portion has a function of extracting a keyword included in text data, a function of extracting a related term of the keyword from words included in a plurality of pieces of first reference text analysis data, a function of giving a weight to each of the keyword and the related term, a function of giving a score to each of a plurality of pieces of second reference text analysis data on the basis of the weight, a function of ranking the plurality of pieces of second reference text analysis data on the basis of the score to generate ranking data, and a function of outputting the ranking data.