Mastering Prior Art Searching: Best Practices and Strategies

Semi-automatic patent claims analysis that improves the speed and accuracy of a computer or server when performing a patent search, particularly for infringement analysis. The analysis involves using preconditioning rules to determine relevant portions of a reference document, a query is submitted to find a set of patents that are similar to the reference document, a set of matching patents from the query are received and claim construction rules are used to determine how a meaning of claim elements of the patents will be ascertained in further analysis, Patent infringement rules and an artificial intelligence (AI) system are used to search the relevant portions of the reference document with the claim constructed claim elements of the patents returned from the search, the set of patents are ranked based on assigned confidence scores indicating a degree to which respective claim elements match the relevant portions of the reference document, and the results are presented to a client device.

A method for assisting users in searching patents. The method involves enabling users 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.

Generating search strings from seed documents or collection of seed documents. The search strings are generated based on the content of the seed documents, the number of claims analyzed, the number of associated documents, and the number of search strings generated from the search strings.

A system to automatically create patent application templates based on prior art references to reduce the time and expertise needed to draft patent applications. The system parses prior art documents to identify sections related to the invention. It then generates a template patent application by removing claims and sections from the prior art that are not relevant to the invention. The template can be edited by the drafter to insert the novel features of the invention.

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.

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.

Data-driven method to efficiently screen a large number of patent documents for relevancy to a target subject matter using a triage approach. The method involves mapping key concepts from claims of the identified patent pool to quickly screen and rule out irrelevant patents. The concepts marked as "definitely not in target subject matter" are used to eliminate patents without manually reviewing each one.

Computer systems and methods for searching, filtering, and analyzing large numbers of patent-related documents to find documents of interest to a user. The system utilizes a comprehensive patent-based parts index derived from the US patent corpus to identify and interrelate part expressions (i.e., part names) in patents. This allows users to search for drawings containing specific parts, search for patents with similar drawings to a selected drawing, and determine non-literal support for claim terms in patent specifications using conceptually related variants.

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 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.

Patent evaluation and determination method for improving the accuracy of determining patentability with a high level of accuracy. The method includes receiving input from an invention sentence relating to an invention, a keyword extraction step of performing a syntactic analysis on the input invention sentence in units of words, and then extracting any search keyword in the invention sentence; a patent sentence group extraction step of extracting a patent sentence group in which the search keyword is contained from a database using the extracted search keyword; and a determination step of comparing the invention sentence and a sentence included in the patent sentence group and determining the patentability of the invention sentence, wherein the determination step includes determining the patentability of the invention sentence based on a result obtained by multiplying a reciprocal number of an edit distance of the sentence included in the patent sentence group by a length index of the invention sentence and a content rate of the search keyword.

A method and apparatus for searching for patents similar to an input query patent that leverages element alignment, paraphrasing, and neologism handling. The technique involves extracting semantic elements from the query patent and searching for similar patents based on those elements. It then aligns the elements of the matched patents with the query elements to calculate a similarity score. If any elements don't match, it prompts the user to provide a paraphrase to improve the search. The paraphrase is added to a dictionary for future use.

Determining the validity or infringement of a patent using natural language processing and information retrieval techniques. The method involves indexing the patent and references to create search documents, building a search index, generating queries from patent claims, and searching the index to find matches. This allows efficiently locating where in references a patent claim is described.

Automated computerized reference harvesting and ranking for patent-related references. The harvesting process includes using a number of seed sets of references as the source of references and pruning research threads in order to create a relatively smaller set of relevant references based on automatically harvested and pruned research threads, together with a computerized reference ranking engine that ranks the set of harvested references for relevance with respect to the entirety of a claim set for a patent or patent application.

A patent searching system that suggests keywords based on the structural attributes of patent claims. The system takes a searching keyword, performs a patent search, extracts definitions related to specific attributes (like subject matter or interrelationship), calculates frequency of those definitions, and suggests keywords from the high frequency ones. This provides more precise search results by focusing on informational relationships within claims instead of just whole-claim keywords.

Automated search, analysis, and display of patent content using a cladistics-based methodology. The system allows users to search patents, view results in a tree diagram, and expand/collapse claims hierarchically. It parses claims, generates diagrams, and allows selecting sub-elements to find matching tech. It analyzes tech content in real-time to find matches and displays thumbnails beside the claims tree. This provides a comprehensive and interactive view of patent claims and related tech.

A patent document searching and retrieval system that improves the relevance and ranking of patent documents in response to user queries, particularly queries based on patent claims. The system involves re-ranking the initial search results using features specific to patent documents like classification codes, citation structure, and similarity to the query claims. This re-ranking is learned through automated training using features computed from search results.

A patent portfolio and annuity management system that provides tools to quickly analyze prior art and make informed decisions about patent prosecution and maintenance. The system uses keyword analysis to identify unique elements in a patent claim set compared to prior art. It ranks documents based on degree of differentiation and presents a visual timeline to show how elements evolved over time. This helps assess patent strength, relevance, and infringement potential.