Weighted Section Search Profiles for Patent Document Retrieval
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Solution Overview
Problem
Existing electronic intellectual property document search tools do not efficiently support different classes of searches, such as novelty, product clearance, and invalidity searches, as they require manual section selection by the searcher, increasing the burden with growing databases and lacking in accuracy.
Innovation Solution
A method and system that create search profiles by assigning weights to sections of intellectual property documents, allowing for selective emphasis on specific sections based on search types, with the option for secondary weights and hierarchical structures to refine search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual section selection is used by searchers, then search scope can be limited, but the burden on searchers increases and accuracy decreases
Solution Approach 1:
The system performs preliminary actions by automatically identifying and weighting relevant document sections before the search is executed. Search profiles pre-configure which sections (claims, specification, drawings) should be emphasized, eliminating the need for searchers to manually select sections and ensuring consistent, accurate section weighting across all searches.
Solution Approach 2:
The search system serves itself by automatically analyzing and weighting document sections based on pre-configured search profiles. The system autonomously determines which sections are most relevant to the search query without requiring manual intervention from searchers, thereby reducing searcher burden while maintaining or improving search accuracy.
2Reliability
If all document sections are reviewed, then comprehensive search results are achieved, but search time and resources increase with growing databases
Solution Approach 1:
The system applies local quality by assigning different weights to different sections of patent documents based on their relevance to specific search types. Instead of uniformly reviewing all sections, the system emphasizes locally important sections (e.g., claims for novelty searches, specification for invalidity searches), achieving comprehensive results in less time by focusing computational resources on the most relevant areas.
3Measurement precision
If section weights are assigned based on search type, then search relevance is improved, but system complexity increases
Solution Approach 1:
The system implements dynamics by making section weights adjustable and search-profile-specific rather than fixed. Different search types (novelty, invalidity, clearance) have different pre-configured weightings for various document sections, allowing the system to dynamically adapt to different search requirements while maintaining manageable complexity through automation and pre-configuration.
Data Source
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AI summary
A method, system, and article are provided for efficiently and effectively searching an electronic document collection. Each of the documents in the collection is pre-divided into sub-sections. One or more profiles are created, with each profile including a selection of one or more of the sections of the documents in the collection. In addition, a weight is assigned to each of the selected sections in the profile. Based upon the parameters of a query and selection of a profile, select sub-sections of each document are employed in a comparison of query data to the underlying document collection. A compilation of documents is created based upon all documents with data matching the query data within the sections of the document as identified in the submitted profile.