Strategic Patent Search Automation

Method for searching for relevant patent documents using machine learning and AI techniques to improve the effectiveness and efficiency of patent searching. The method involves parsing claim elements, selecting keywords, identifying synonyms, forming search strings, ranking documents, determining citations, and mapping elements. This allows targeted searching of databases using user-defined elements instead of keywords, improving recall and reducing false positives compared to keyword-based searching.

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Patent search method and platform that improves efficiency and expands the range of retrieved patents by leveraging product and effect trees. When searching for patents using brief effects, the platform extracts hyponym words from the product and effect trees to find related patents beyond just matching the exact words. This provides a hierarchy of related concepts that expands the search beyond just the exact input words. The platform also suggests higher level concepts to broaden searches when exact words aren't found.

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A hybrid AI system for patent claims analysis that combines machine learning and user input to accurately search and analyze patent documents. The system allows users to initiate searches based on reference documents, narrow the search focus, and select sections. It uses ML to transform the document and claims into embeddings representing their meaning. Element-by-element searches find matches based on these embeddings. Confidence scores rank the results. The system provides feedback to improve future searches.

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A decentralized blockchain system for granting smart contracts as an alternative to centralized patent examination systems. This system leverages a distributed network of validators to review and approve smart contracts that confer patent-like rights. Validators are incentivized through token rewards for successfully validating contracts, promoting participation, and maintaining the integrity of the system.

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More accurate patent searching and analysis using AI, specifically natural language understanding (NLU) and machine learning (ML) techniques, to improve search results and avoid missing relevant patents. The method involves analyzing patent claims and relevant text from a reference document using AI systems to determine the meaning of claim elements and search for matches to rank patents based on how well their claims match the reference document.

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A method to assist users in patent searching by enabling them to select and search within patent documents based on key criteria like classification codes and related tags. The system retrieves patent documents matching the initial search criteria. Users can then select one or more patents of interest and extract additional criteria like classification codes from them. The system generates a refined search using the extracted criteria to find more relevant patents. This iterative process allows users to navigate and refine patent searches using criteria specific to patents, enhancing search accuracy and relevance.

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Improved efficiency and insight in a patent review that facilitates effective and appropriate handling of review-sharing capabilities. The system maintains a registered user database to determine whether to generate a share link that is publicly accessible or only accessible by the intended recipient. It also generates an interactive publication review history interface using interconnected records to gather previously stored work products associated with a particular publication.

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A patent data publishing method and system to reduce errors when publishing patent data for sale on a transaction platform. The method involves acquiring at least one piece of bibliographic data of the patent, verifying the data with a third-party source, and then publishing the verified bibliographic data, legal status, and transaction price. This avoids manual entry errors.

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Patent document search using diffusion models to improve accuracy and efficiency of patent retrieval. The method involves using diffusion models to generate keyword-oriented abstracts, claims, and sentences from a patent document. These expanded versions are then searched separately to find similar patents. The results are integrated and weighted to identify the most relevant patents. This expansion and integration process allows more comprehensive and accurate retrieval compared to just matching keywords.

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Intelligent system for fast and accurate patent search using natural language queries. The system takes user input of patent-related information like product names, self-made words, and company names. It then filters and displays relevant patents based on this input. The system leverages databases to find matching products, companies, and keywords. This improves the accuracy and efficiency of patent searching compared to querying raw patent databases.

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Automatically extracting patent document templates from a patent corpus by identifying sets of similar patent documents and extracting the common text shared between them. This allows finding and generating standardized document templates from a collection of similar documents like patents.

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A method for searching for similar patents based on natural language expressing most of the contents of a patent. The method involves extracting patent elements like components and functional elements from a query patent, extracting search words from the elements, matching and sorting elements of the query patent and elements of similar patents, calculating a matching rate, identifying missing elements, and optionally prompting a user to input a paraphrase for those missing elements. The paraphrase is then used to search for additional similar patents. This allows more accurate matching of components and handling of paraphrases and neologisms in patent descriptions.

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Automatically generate concise summaries of patent documents by extracting key information from the technical problem, solution, and beneficial effects sections of the patent. The method involves using pre-trained models to extract problem, solution, and effect sentences from the patent document. These sentences are then combined to create a summary of the invention.

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A method for creating a patent document summary that involves leveraging natural language processing and machine learning techniques to analyze the text of a patent document and generate a concise summary that captures key information from the document. The method involves identifying repetitive word sequences in the document, replacing subsequent occurrences of those sequences with shorter substitutes, and generating the summary based on the modified text.

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Automated prior patent search solution to quickly and easily generate patent search reports by leveraging text mining techniques. The solution involves extracting keywords from a search query, expanding them with synonyms, creating a search expression, searching patents, analyzing results, and generating a report. The text mining involves stopping unnecessary words, extracting primary keywords, expanding with synonyms, and storing unmatched keywords.

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Automated patent analysis and document generation system that can analyze patent claims and generate reports and search results based on the claims. The system uses natural language processing techniques to analyze patent claims and extract key elements. It generates search strings from these elements and sends them to external search engines to find related documents. The system also generates profiles for claims and documents based on linguistic analysis, syntactic categories, and metrics like stemming and word count. These profiles can be displayed to users for analysis.

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A platform for conducting patent searches and analyzing patent value using a combination of AI, machine learning, and blockchain technology. The platform leverages natural language processing to improve patent search relevance by analyzing similarities between claim limitations and prior art specifications. It also uses AI algorithms to rank prior art based on relevance to specific claim elements. The platform further provides tools for highlighting, weighting, and customizing search parameters.

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Patent information processing system using word frequency analysis to provide efficient patent searching and licensing recommendations. The system extracts key words from patents, calculates word frequencies, and uses similarity metrics to identify related patents. It also leverages linear programming to estimate patent licensing value based on factors like enterprise capabilities and patent descriptions. The system provides intelligent patent retrieval and suggests high correlation patents. It can also evaluate patent licensing potential through linear programming.

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Automatically classifying patents via machine learning to save time and resources. The method involves learning from a patent database to establish a basic classification model. When a user searches for patents, it uses their classification input to predict their personalized classification standard. This combines with the basic model to classify the remaining unclassified patents. It leverages transfer learning to customize the basic model using the user's classification pattern.

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Method and system for retrieving key technologies in patents and documents that improves upon existing patent retrieval methods by finding comprehensive and accurate key technologies in a field. The method involves extracting topics from patent and document databases, judging patent and document topic strengths, and identifying key techniques based on those scores. This analyzes documents and patents simultaneously to determine field-specific key technologies more comprehensively and accurately compared to just patent retrieval.

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