PATENT CLAIM ANALYSIS

Application Number: 15941851
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-10
Patent Classification: ["715", "200000"]

Abstract:
This invention relates to a novel and innovative means and method to accurately and consistently classify professional services and expenses into textual, numerical, and Uniform Task Based Management System (UTBMS) or similar categories which can then be reliably used by attorneys, consultants, accountants, architects, and other professionals who bill by the hour for their services to track, analyze, and evaluate their costs, the performance of specific individuals and vendors, and other metrics. More particularly, this invention relates to a novel and innovative means and method of: (1) automating and standardizing the coding of professional activity and expenses in an accurate, consistent, and therefore useful manner; (2) automatically evaluating and standardizing billing entries through the use of lexical, statistical, and multivariate analysis, pattern matching, contextual grouping, and supervised and unsupervised machine learning of American English legal and other phrases; and (3) evaluating the reasonableness of amounts charged for specific professional activities and expenses, whether by entry or in the aggregate.

Claim (Index 1):
A method for the use of computer software for the automatic evaluation and assignment of appropriate amounts of time billed, amounts charged for expenses, and Uniform Task Based Management System (UTBMS) or similar codes for new billing entries for work performed by attorneys, consultants, accountants, architects, and other professionals who bill by the hour for their services, comprising:\n Obtaining, a database of vetted and approved data sets (individually or in bulk) for text descriptions, amounts of time billed, amounts charged for expenses, and/or UTBMS or similar codes; Evaluating, the database of vetted and approved data employing lexical analysis, pattern matching and contextual grouping of American English phrases to generate discrete tokens and lexemes; Obtaining, additional inputs of unapproved entries of text descriptions, amounts of time billed, amounts charged for expenses, and UTBMS or similar codes for new billing entries entered by the user; Generating an output to the user suggesting previously approved and vetted entries for selection by the user during the user's input process of new entries concurrently during the process of obtaining additional inputs of unapproved entries from users; Utilizing a multivariate lexical and statistical analysis to evaluate unapproved entries against the database of vetted and approved data sets to determine the affinity of the new entry to the approved database and to determine the acceptability of the new entry within the allowable range; Generating, an output displayed to the user indicating whether or not the new data entry meets within acceptable ranges of the approved and vetted entries; Using unsupervised and supervised machine learning to curate and maintain the database of vetted and approved data sets.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 1.75229
- Patent Class: 715.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['11694734', '10838000', '11847258', '12614387', '13180265']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2944203971760248
- 35 USC 102 Novelty (BERT): 0.4596556812300837
- Combined Prediction Score: 0.3109439255814308
- Mean Citation Score: 133.11788
- Max Citation Score: 139.77293
- Similarity Product: 102.44976429968597

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

Dataset: test