US 12,675,925 B2Granted

Computer network activity summarizer and chat interface

AssigneeAdobe Inc.

InventorsTarun Arora, Tanay Anand, Siddarth Ramesh, Shripad Deshmukh, Pranjal Prasoon, Piyush Dewnani, Md Anis Alam, Jayakumar Subramanian, Gaurav Satija, Diwakar Reddy Yerragunta, Deepthi Amirthagadeswaran, Balaji Krishnamurthy, Avinash Katiyar

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Abstract

Various disclosed embodiments are directed to deriving, via a language model, a summary of data by converting or encoding table data into one or more natural language sentences, which are then used as input to the language model for generating the summary. One or more embodiments are additionally or alternatively directed to deriving, via a language model, a response to a user question or command via a chat interface by providing the language model with the generated summary as input. In this way, for example, the language model can use the summary as a prompt or other target context for providing a response.

Claims19

Dependent claims

A system comprising:

at least one computer processor;
and
one or more computer storage media storing computer-useable instructions that, when used by the at least one computer processor, cause the at least one computer processor to perform operations comprising:
accessing, from the one or more computer storage media, user activity data in one or more database tables, the user activity data including statistics indicating a quantity of different types of computer user input, each database table, of the one or more database tables, having one or more columns and one or more rows, a column, of the one or more columns, having a column name indicated in natural language, a row, of the one or more rows, having one or more values that are a part of the statistics indicating the quantity of different types of computer user input;
generating, via computer natural language processing, a machine-readable tag, the machine-readable tag providing additional contextual text that supplements the column name to indicate an entity type of the column;
for the row, generating a natural language sentence by combining the column name and the machine-readable tag of the column with the one or more values that are the part of the statistics indicating the quantity of different types of computer user input;
and
at least partially responsive to the generating of the natural language sentence, encoding the natural-language sentence into a numerical tensor representation and providing the numerical tensor representation as input to a transformer-based language model comprising an attention mechanism, wherein an output layer of the language model generates an embedding vector corresponding to a semantic summary associated with the row based on the attention mechanism.

5 more elements

A computer-implemented method comprising:

accessing, from one or more computer storage media, data from one or more tables, the data includes at least one of lead data of a lead and account data of an account, each table, of the one or more tables having one or more columns and one or more rows, each column, of the one or more columns, having a column name, each row, of the one or more rows, having one or more values corresponding to statistics of computer user input of the lead or the account;
generating, for each column name and via computer natural language processing, a machine-readable tag that indicates a semantic meaning of a respective column name of the one or more tables;
generating one or more natural language sentences by combining at least the computer-readable tag with the one or more values corresponding to the statistics of computer user input of the lead or account for each row of the one or more tables;
and
encoding the one or more natural language sentences into a numerical tensor representation and providing the numerical tensor representation as input into a language model comprising an attention mechanism, wherein an output layer of the language model generates an embedding vector representing at least one summary associated with each row based on the attention mechanism.

2 more elements

A computer system comprising:

a user activity extractor means for accessing, from the one or more computer storage media, data from one or more tables, the data includes at least one of lead data of a lead and account data of an account, each table, of the one or more tables having one or more columns and one or more rows, each column, of the one or more columns, having a column name, each row, of the one or more rows, having one or more values corresponding to statistics of computer user input of the lead or the account;
a verbalization component means for generating, for each column name and via computer natural language processing, a machine-readable tag that indicates a semantic meaning of a respective column name of the one or more tables;
wherein the verbalization component means further for generating one or more natural language sentences by combining at least the computer-readable tag with the one or more values corresponding to the statistics of computer user input of the lead or account for each row of the one or more tables;
and
a summarization component means for encoding the one or more natural language sentences into a numerical tensor representation and providing the numerical tensor representation as input into a language model comprising an attention mechanism, wherein an output layer of the language model generates an embedding vector representing at least one summary associated with each row based on the attention mechanism.

2 more elements

Dependencies are inferred from the claim text.