Effective Strategies for Expert Patent Searches

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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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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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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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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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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Searching, filtering, and analyzing large numbers of patent-related documents to find documents of interest to a user. It provides user interface tools for filtering and analyzing patent-related documents to find documents of interest. It also allows searching for specific patent drawings.

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A patent strategy chart that visually represents the relationship between patent claims and embodiments in a way that is intuitive and quickly understandable. The chart uses two main graphical elements: 1) a first display representing embodiments using characters or figures, and 2) a second display representing the scope of patent claims using an approximate fan shape. These displays are grouped together and arranged on a two-dimensional plane with arbitrary coordinates. The chart can be generated manually or using a digital system. This allows representing the inclusion/association of embodiments within patent claims and helps quickly grasp patent landscapes and competitive situation.

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Optimizing patent literature searches by taking a user's search formula and expanding it to a higher-quality search by adding relevant search terms and operators. The system receives a user's search formula, classifies it into groups based on operators, adds additional relevant search terms to each group, combines the groups with operators to create a final optimized search formula, and provides that to the user. This expands and improves the user's initial search.

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A research and development (R&D) auxiliary system that leverages patent databases to provide suggestions and insights to R&D teams. The system uses association rules created by analyzing patent classification numbers or technical element messages from patent documents. These association rules, along with their strength values, are used to generate suggestions like patentable R&D ideas or patent invalidation inferences that can assist R&D efforts. By analyzing patents in this way, the system provides practical guidance based on the patent database that addresses the specific needs of R&D personnel.

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Automating the harvesting and ranking of patent references to improve patent examination and analysis. Automated reference searching and analysis system that provides a tool to collect prior art references based on automatically harvested and pruned research threads. The system also ranks the harvested references for relevance to a claim set and presents the ranking visually.

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An apparatus and method for forecasting patent disputes. It extracts keywords from the claims and background of two patent documents and calculates similarity between them using those keywords. The claim and background similarities are combined to give a cooperative similarity score, which represents the probability that the documents are infringing on each other.

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