公开(公告)号：US20250148348A1

公开(公告)日：2025-05-08

申请号：US18388020

申请日：2023-11-08

Applicant: SAP SE

Inventor： Barbora BLASKOVA ,  Nitin Chavan ,  Gaurav Vanawat ,  Sudhir Verma ,  Rohan Koul ,  Rajeev Kansal ,  Shubham Gupta

IPC: G06N20/00

Abstract: A machine-learning model is trained to cluster support requests based on the contents of the support requests. A user of the recommendation system may select a set of support requests to be clustered. Based on the selected set of support requests, the trained machine-learning model may be tuned and used to cluster the selected set of support requests. Using the characteristics of the support requests in one or more generated insights, one or more tools suitable for providing automated support for the cluster of support requests may be identified. Using a knapsack-based approach, one or more of the identified tools is selected for recommendation to the user.

公开(公告)号：US20240320274A1

公开(公告)日：2024-09-26

申请号：US18124190

申请日：2023-03-21

Applicant: SAP SE

Inventor： Kiran Venkatarama ,  Sudhir Verma ,  Anupama Rakesh Singh ,  Ankit Lohiya ,  Raghuraj Shetty ,  Ishita Kriti ,  Rohan Koul ,  Anirudh Saraiya ,  Akhileswara Kumar Chatala ,  Suketu Nitin Dave ,  Rohit Kumar

IPC: G06F16/93 ,  G06F40/166 ,  G06F40/20 ,  G06N5/02

CPC classification number: G06F16/93 ,  G06F40/166 ,  G06F40/20 ,  G06N5/02

Abstract: Techniques for conserving system resources using smart document retention are disclosed. A computer system may identify a first portion of a plurality of documents as being decision-making documents based on each document in the first portion being scheduled for deletion within a specified period of time, identify a second portion of the plurality of documents as being non-decision-making documents based on each document in the second portion either being scheduled for deletion outside of the specified period of time or having been converted into and stored as a knowledge base document, and determine a corresponding level of similarity between each decision-making document and each non-decision-making document. The computer system may then cause identifications of a subset of the decision-making documents to be displayed on a computing device based on the corresponding level of similarity between each decision-making document in the subset and at least one of the non-decision-making documents.

公开(公告)号：US11803402B1

公开(公告)日：2023-10-31

申请号：US18079522

申请日：2022-12-12

Applicant: SAP SE

Inventor： Sidharth Gupta ,  Nitin Chavan ,  Rohan Koul ,  Sudhir Verma

IPC: G06F11/07 ,  G06F9/451 ,  G06N20/00 ,  G06F3/0484

CPC classification number: G06F9/453 ,  G06F3/0484 ,  G06F11/0793 ,  G06N20/00

Abstract: A computer system may obtain reference ticket data for reference tickets of an online system, with the reference ticket data indicating a reference issue for a reference component and a reference solution, and also obtain learning content items from a learning management system. The computer system may then create a mapping between the reference issues indicated by the reference ticket data for the reference tickets and the learning content items using an unsupervised machine learning algorithm. The computer system may detect target ticket data that has been provided by a user to the online system via a computing device, with the target ticket data indicating a target issue for a target component, identify a target solution for the target issue based on the target ticket data using the mapping, and cause a recommendation of the target solution to be displayed on the computing device.