Patent Literature Search Engine Using Citation Analysis
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Solution Overview
Problem
The increasing volume of patent-related information makes it difficult for professionals to efficiently search for relevant literature, assess patentability, marketability, and valuation of ideas, and determine the value of intellectual property assets, as existing electronic search tools rely on rudimentary keyword matching and require trial-and-error strategies.
Innovation Solution
A Patent Related Publication Search Engine (PRPSE) is developed to iteratively find relevant patent publications using input text, determining predominant keywords through algorithms, and employing citation analysis to locate correlated publications, while providing an interface for users to refine searches and suggest related keywords and categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic search tools use rudimentary keyword matching, then the search system is simple to implement, but the search efficiency and accuracy deteriorate due to the need for trial-and-error strategies and inability to handle large patent corpora effectively
Solution Approach 1:
The patent introduces an intermediary system that bridges the gap between simple keyword matching and complex professional search strategies. The system automatically generates and refines search queries by analyzing patent documents, extracting relevant terms, and constructing optimized search strings that professionals would otherwise need to develop through extensive experience and trial-and-error
Solution Approach 2:
The search system performs self-service by automatically analyzing patent corpora, extracting key terminology, and generating optimized search queries without requiring professional intervention. The system learns from the patent documents themselves to improve its search capabilities, eliminating the need for external expertise to formulate effective search strategies
2Quantity of substance
If the corpus of patent information grows dramatically, then more comprehensive coverage is achieved, but the difficulty of searching and navigating the information increases
Solution Approach 1:
The system extracts essential search terms and concepts from within the large patent corpus, pulling out only the most relevant keywords and phrases needed for effective searching. This extraction process creates a condensed representation of the vast patent information that can be used to navigate and search the corpora efficiently without being overwhelmed by its size
Solution Approach 2:
The search system is designed to handle multiple functions simultaneously: it can search across different patent corpora, analyze various document types, and adapt to different search scenarios. This multi-functionality allows the system to maintain ease of operation while managing increasingly large and diverse patent information collections
3Measurement precision
If professionals manually formulate search strategies through experience and trial-and-error, then search accuracy can be improved, but the time and expertise requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-analyzing patent documents to extract and store relevant terminology, concepts, and relationships before searches are conducted. This preliminary processing creates a structured knowledge base that enables accurate searches to be executed quickly without requiring professionals to spend time on trial-and-error strategy formulation for each search
Data Source
AI summary
Methods, systems, and techniques for using of keywords, categories, patent related publications, and other literature to profile users are provided. Some examples provide a profiling tool which enables users to self-describe using, for example, keywords, patent related publications, and articles. In other examples, the tool assigns search-based profiling information. The profiling tool using citation based patent related search techniques to suggest additional keywords and/or patent publications for augmenting the user's search-based profile information. In some examples, the IP Invention Management System (IPIMS) uses these profiles to distribute workload, for example, to route patent assets to be reviewed or be improved upon as ripe for invention. In addition, other applications may use these profiles to offer other types of matching services, such as social mapping.