Advances in Database Construction and Consolidation for IP Management

A patent management system that helps users quickly find relevant patents, analyze patent portfolios and monitor competitors. The system uses AI techniques like claim mapping, concept organization, and similarity indexing to enable efficient patent searching, analysis, and comparison. It provides tools like portfolio analytics, reference management, prior art analytics, docketing management, claim mapping, claim analytics, portfolio analytics, external database analytics, annuity management, and strategic monitoring.

System and method for concept-based management of categorizations or classifications to organize a commonplace, enhancing the navigability of very large information bases by providing in-depth sub-categorization of terminology bases, providing users with incentives to be creative, protecting crowd-sourced contributions, managing searches for what is known either within, or in some accessible location outside of it, and establishing communities associated especially with the concepts, or its narrow categories, and particularly in Intellectual Property. It provides a user with a searching tool for something known or unknown, capturing the concept of the unknown to be reused as if known. This invention extends to new forms of fuzzy clustering and hierarchical self-organizing maps.

A system for organizing and categorizing knowledge to improve information retrieval and enable innovation. The system uses a crowd-sourced categorization database called the Common Mental Model (CMMDB) that contains categorized concepts. Users can search, visualize, refine, and contribute to the database. The system also provides monetization options like selling licenses to access the categorized knowledge.

A method for constructing a patent knowledge database that efficiently analyzes massive patent resource data to extract effective patent information. The method involves analyzing patent specifications and drawings to obtain explicit information like patentee names and application dates, and implicit information like relationships between technical elements. The explicit and implicit information is fused to filter noise and construct the patent knowledge database.

A patent management system that allows an inventor, business manager, or patent attorney to quickly and easily obtain up-to-date information relating to cited references or technology trends in the art to which a user's or competitor's patent portfolio relates. The system includes a database, which stores data representing each matter in which a patent application is filed, an external database, and an operation database.

Automated system for updating databases with information from documents. The system identifies relevant terms and relationships in documents using techniques like text analysis and tagging. It presents possibly relevant terms to a human analyst who confirms actual relevance. Accepted terms are then provided to the database for updating. The system aims to partially automate the process of identifying and extracting information from documents for the database population.

A patent management system that allows parties involved in the patenting process to make decisions at each stage of a patent's life. The system includes a database, a user database, a mapping database, and an analytics database.

Patent analytics using MapReduce clustering to efficiently analyze large patent databases and identify patent clusters related to specific products. The method involves querying public patent databases using patent cluster keywords and enterprise databases using product cluster keywords. The patents are clustered using MapReduce and then sorted by criteria like cluster size and product conflict. This allows for finding patents covering a product, missing patents, related patent clusters, and areas to pursue. The sorting helps prioritize and focus on relevant clusters.

Copyright database and trading platform to resolve copyright challenges by providing a centralized system to find and mediate copyright holders. The database allows copyright holders to upload their works with information and notices attached. It categorizes and organizes the works for easy search and retrieval. The platform also facilitates trading and licensing of copyrights between holders and users. It aims to prevent copyright disputes, enable commercialization of copyrights, and protect creators' rights.

Electronically mining intellectual property by using data mining techniques to automatically discover potential IP from enterprise documents. The method involves harvesting company documents and industry trends, identifying relevant trends, and analyzing documents using text mining to find correlations that could lead to new IPs. It aims to quickly identify business-critical intellectual property by associating enterprise processes with emerging technology trends.

Enhanced methods, techniques, and systems for searching patent-related literature like issued patents, patent applications, and abstracts. The methods involve using machine learning and natural language processing to improve search accuracy and efficiency for tasks like assessing patentability, valuing assets, and finding prior art. It involves training models to understand patent language, identify key concepts, and match them across documents. The models can learn from user feedback and expertise to personalize search results. It aims to overcome the challenges of searching growing patent corpuses with complex language using AI.

A patent management system that provides tools for analyzing patents and patent portfolios to assist in decision making during the patent lifecycle. The tools include prosecution analytics, patent analysis, reference management, prior art analytics, docketing management, claim mapping, claim analytics, portfolio analytics, external database analytics, annuity management, and strategic monitoring. The system retrieves patent claims and compares published and issued versions to identify unique keywords. It then performs keyword analysis on prior art using the unique keywords to potentially determine novelty points.

Creating easily readable comprehensive patent data summaries that are customizable, interactive, and visualized. The summaries can be generated for entities like companies, law firms, inventors, etc. The summaries can be requested by users and delivered over the internet. The summaries can contain information like top assignees, top inventors, top patents, etc. The summaries can be updated automatically with new patent data. The summaries can also have report caching for frequently accessed entities. The summaries can be provided in interactive formats with filters, sorting, and drilldowns. The summaries can be displayed in graphical formats. The summaries can be generated for entities like companies, law firms, inventors, etc. The summaries can contain information like top assignees, top inventors, top patents, etc. The summaries can be updated automatically with new patent data. The summaries can also