PATENT CLAIM ANALYSIS

Application Number: 16181971
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["705", "004000"]

Abstract:
A computer-implemented method and a computer-based system for detecting, profiling and benchmarking Intellectual Property (IP) law professional liability risks and professional liability insurance risks and value associated with IP prosecution and maintenance processes for IP business entities, including IP law firms and independent IP professionals. The invention allows further an insurance firm to accurately quantify professional liability risk of a new or existing IP business client and to mitigate such risks. The present method involves accessing and collecting transaction data indicative of risk-reducing and risk-increasing behavior of an IP business entity from a National IP Office in a chosen jurisdiction and sending the transaction data to a back-end computer system for processing and analysis. In the preferred embodiment of the invention, the transaction data is collected from the USPTO PAIR system5

Claim (Index 12):
A non-transitory computer-readable medium having computer executable statements and instructions stored thereon, said executable statements and instructions adapted to be executed by one or more processors of a computer-based system for detecting, profiling and benchmarking liability trigger events indicative of performance quality and subject matter conflict of interest of intellectual property (IP) professional practices and susceptible to affect liability risk profile and liability insurance risk profile of a target entity engaged in said IP professional practices, including IP professionals employed or representing said target entity, said executable statements and instructions comprising:\n a. first set of computer-executable statements and instructions for communicating electronically with a National/Regional Intellectual Property Office (IPO) computer system in at least one IP jurisdiction, identifying and extracting Asset Data from said IPO computer system, processing and clustering said extracted Asset Data, generating an IP jurisdiction identifier to associate each document of said Asset Data with the jurisdiction of the corresponding IP document, and storing said IP jurisdiction identifier with said each document of said Asset Data therewith to a data storage device; b. second set of computer-executable statements and instructions for indexing and consolidating said Asset Data and selective internal results of calculations and comparisons performed on said Asset Data, and storing the indexed and/or consolidated Asset Data and said selective internal results of calculations and comparisons performed on said Asset Data to said data storage device; c. third set of computer-executable statements and instructions for filtering and profiling the processed Asset Data by checking for codes associated with one or more of said liability trigger events indicative of said performance quality and said subject matter conflict of interest of IP professional practices and susceptible to affect said liability risk profile and said liability insurance risk profile of said target entity, including IP professionals employed or representing said target entity, to produce Liability Alert Data, and storing said Liability Alert Data to said data storage device; d. fourth set of computer-executable statements and instructions for applying one or more predetermined factors associated with said one or more liability trigger events to said Liability Alert Data to produce Weighted Liability Alert Data, and storing said Weighted Liability Alert Data to said data storage device; e. fifth set of computer-executable statements and instructions to determine, based on receiving said processed Asset Data from said storage device, one or more factors associated with said target entity, including at least the number of professional employees, the number of IP transaction conducted, and the dollar amount of filing fees paid in a pre-determined period of time, and to output the resulting information to said data storage device, and/or to a user interface, and/or to a display device; f. sixth set of computer-executable statements and instructions to determine said liability risk profile and said liability insurance risk profile of said target entity, including IP professionals employed or representing said target entity, by applying one or more predictive models trained on said Asset Data to said Weighted Liability Alert Data, and outputting said liability risk profile and said liability insurance risk profile to said data storage device, and/or to said user interface, and/or to said display device; g. seventh set of computer executable statements and instructions to determine said subject matter conflict of interest of IP professional practices of said target entity by filtering and profiling said processed Asset Data to find all documents associated with the same target entity, filtering and profiling further the results to find documents having identical set of classification classes and subclasses, filtering and profiling further the results to find documents having different entries in the Applicant field or in the Assignee field respectively, and outputting the resulting documents to said data storage device, and/or to said user interface, and/or to said display device; h. eighth set of computer-executable statements and instructions to receive an input from at least one user via user interface and to automatically retrieve corresponding information from said computer-based system in response to said at least one user input, and to output said corresponding information to said user interface.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 1.6747
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['12589113', '10309705', '12028620', '11180503', '12890514']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.105117903084433
- 35 USC 102 Novelty (BERT): 0.4886052906129225
- Combined Prediction Score: 0.1434666418372819
- Mean Citation Score: 172.07454199999995
- Max Citation Score: 188.14514
- Similarity Product: 124.8797428952396

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test