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公开(公告)号：US20240386315A1
公开(公告)日：2024-11-21
申请号：US18318524
申请日：2023-05-16
Applicant: ADOBE INC.
Inventor： Thomas BOUCHER , Tanay ANAND , Stephane LECERCLE , Saurabh GARG , Pranjal PRASOON , Nikaash PURI , Mukul LAMBA , Milan AGGARWAL , Jayakumar SUBRAMANIAN , Francoise CORVAISIER , David MENDEZ ACUNA , Camel AISSANI , Balaji KRISHNAMURTHY
Abstract: Methods and systems are provided for a transformer model for journey simulation and prediction. In embodiments described herein, training data is obtained from stored journeys. The training data for each journey indicates customer interactions with each event in the sequence of events of the journey. A machine learning model is trained using the training data to simulate customer interaction with an input journey. The trained machine learning model then generates a simulation of customer interaction with an input journey and the results of the simulation are displayed.
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公开(公告)号：US20250124620A1
公开(公告)日：2025-04-17
申请号：US18380059
申请日：2023-10-13
Applicant: Adobe Inc.
Inventor： Tarun 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
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.
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公开(公告)号：US20250086448A1
公开(公告)日：2025-03-13
申请号：US18367020
申请日：2023-09-12
Applicant: Adobe Inc.
Inventor： Tanay ANAND , Siddarth RAMESH , Shripad Vilasrao DESHMUKH , Jayakumar SUBRAMANIAN
IPC: G06N3/08 , G06N3/0475
Abstract: Systems and methods provide a generative recommendation model that leverages verbalizations generated from sequential data. In accordance with some aspects, sequential data for a trajectory comprising a plurality of steps is accessed, in which the sequential data comprises a tuple for each step of the trajectory. Verbalized sequential data is generated from the sequential data, in which the verbalized sequential data for each step of the trajectory comprises one or more natural language sentences generated from the tuple for the step. A generative model is trained on the verbalized sequential data to provide a trained generative model that generates a recommended action given a prompt specifying a current state.
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公开(公告)号：US20210406935A1
公开(公告)日：2021-12-30
申请号：US16910357
申请日：2020-06-24
Applicant: ADOBE INC.
Inventor： Pankhri SINGHAI , Piyush GUPTA , Balaji KRISHNAMURTHY , Jayakumar SUBRAMANIAN , Nikaash PURI
Abstract: Methods and systems are provided for generating and providing insights associated with a journey. In embodiments described herein, journey data associated with a journey is obtained. A journey can include journey paths indicating workflows through which audience members can traverse. The journey data can include audience member attributes (e.g., demographics) and labels indicating journey paths traversed by audience members. A set of audience segments are determined that describe a set of audience members traversing a particular journey path. The set of audience segments can be determined using the journey data to train a segmentation model and, thereafter, analyzing the segmentation model to identify patterns that indicate audience segments associated with the particular journey path. An indication of the set of audience segments that describe the set of audience members traversing the particular journey path can be provided for display.
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