US 12,592,904 B2 · Intelligent transaction scoring

Abstract

Systems and methods provide a flexible environment for intelligently scoring transactions from data sources. An example method includes providing a user interface configured to generate a rubric by receiving selection of one or more one or more conditions, each condition identifying a tag generated by a classifier in the library of classifiers and for each identified tag, receiving selection of a value for the tag that satisfies the condition and receiving selection of an outcome attribute for the condition. The outcome attribute may be a weight for the tag or an alert condition. The method includes storing the rubric in a data store and applying the stored rubric to scoring units of a transaction. The method also includes aggregating scores for transactions occurring during a trend period and displaying the trend score. In some implementations, at least one classifier in the library is a rule-based classifier defined by a user.

Claims20

Dependent claims

A method comprising:

generate tags for each transaction in a plurality of transactions by applying classifiers in a library of classifiers to the plurality of transactions, each transaction representing a conversation organized into scoring units;
calculating a respective transaction score for each transaction of the plurality of transactions based on the tags and on scoring criteria that apply to the transaction;
identifying a set of transactions of the plurality of transactions that meet an alert condition based on the respective transaction scores or the tags;
and
generating a user interface configured to:
display a respective identifier for each transaction in the set of transactions,
display a respective snippet for each transaction in the set of transactions, and
display, for each transaction in the set of transactions, tags generated for the transaction.

5 more elements

A method comprising:

generating tags having tag values for each transaction in a plurality of transactions by applying classifiers in a library of classifiers to the plurality of transactions, each transaction representing a conversation organized into scoring units;
determining a set of transactions from the plurality of transactions that are associated with an attribute value for a transaction attribute and that have a date that falls within a trend period;
calculating category summaries for the attribute value, each category summary of the category summaries being based on an aggregation of tag values of a tag of the tags for the transactions in the set of transactions;
and
providing a user interface for the attribute value, the user interface configured to display the category summaries for the attribute value.

2 more elements

A system comprising:

at least one processor;
and
memory storing instructions that, when executed by the at least one processor, cause the system to perform operations including:
generating tags having tag values for each transaction in a plurality of transactions by applying classifiers in a library of classifiers to the plurality of transactions, each transaction representing a conversation organized into scoring units;
determining a set of transactions from the plurality of transactions that are associated with an attribute value for a transaction attribute and that have a date that falls within a trend period;
calculating category summaries for the attribute value, each category summary of the category summaries being based on an aggregation of tag values of a tag of the tags for the transactions in the set of transactions;
and
providing a user interface for the attribute value, the user interface configured to display the category summaries for the attribute value.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application

18/621,816Filed 29 Mar 2024 · continuation

Priority

29 Apr 2020

Published

US 2025/0023841 A116 Jan 2025

Granted

31 Mar 2026

Term ends

Not estimatedThe source records don’t support an estimate.

Classification13 codes

G06F 40/253
Natural language analysis: grammatical analysis; Style critique
H04L 51/52
User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail: for…
G06F 40/289
Recognition of textual entities: phrasal analysis, e.g. finite state techniques or chunking
G06F 40/30
Handling natural language data: semantic analysis

Family

Application63/017,434Us provisional application · filed 29 Apr 2020

Application16/928,397Parent of this division · filed 14 Jul 2020

Application18/060,845Parent of this continuation · filed 1 Dec 2022

US 11,546,285 B2Parent of this division · filed 3 Jan 2023

US 2025/0023841 A1Pre-grant publication · published 16 Jan 2025

US 11,949,645 B2Parent of this continuation

Application18/060,845Parent of this division

US 2021/0344636 A1Published application

US 2023/0101221 A1Published application

US 12,592,904 B2This patent

From the US filing history. Foreign family members aren’t listed.

Intelligent transaction scoring

Life of this patent

Intelligent transaction scoring

Life of this patent

Abstract

Claims20