公开(公告)号：US20230297907A1

公开(公告)日：2023-09-21

申请号：US17694784

申请日：2022-03-15

Applicant: NICE LTD.

Inventor： Noam KAPLAN ,  Gennaldi LEMBERSKY

IPC: G06Q10/06

CPC classification number: G06Q10/063112 ,  G06Q10/06316

Abstract: A method for allocating resources for a plurality of time intervals, including: receiving a forecasted workload and at least one required service metric value; applying a search algorithm to identify an initial allocation assignment; inputting the assignment to a machine learning algorithm, the machine learning algorithm trained on historic data of past intervals; predicting an expected service metric value provided by the initial allocation assignment; adjusting the initial allocation assignment based on a difference between the expected service metric value and the corresponding required service metric value; iteratively repeating the applying, inputting, predicting, and adjusting operations until one of: the expected service metric value predicted for an adjusted allocation assignment is within a predetermined distance of the corresponding at least one required service metric value for the interval; or a predetermined time has elapsed.

公开(公告)号：US20240386357A1

公开(公告)日：2024-11-21

申请号：US18319337

申请日：2023-05-17

Applicant: NICE LTD.

Inventor： LeAnn HOPKINS ,  Matan KERET ,  Noam KAPLAN ,  Rahul VYAS ,  Salil DHAWAN

IPC: G06Q10/0639 ,  G06N3/044 ,  G06Q10/0631

Abstract: Classification and resolution systems and methods, and non-transitory computer readable media, including receiving a repeat interaction from a customer after a first interaction with a first agent; determining a history of the customer with the contact center, historical statistics of the first agent, skill statistics of the first agent, and contact center information on the first interaction; providing the history of the customer with the contact center, the historical statistics of the first agent, the skill statistics of the first agent, and the contact center information on the first interaction to a source classification model; automatically determining a source of the repeat interaction; automatically ranking based on the determined source of the repeat interaction, one or more reasons for the repeat interaction; and performing an action during the repeat interaction that corresponds to the one or more reasons for the repeat interaction to improve customer satisfaction.

公开(公告)号：US20230325736A1

公开(公告)日：2023-10-12

申请号：US18325347

申请日：2023-05-30

Applicant: Nice Ltd.

Inventor： Eyal SEGAL ,  Noam KAPLAN ,  Gennadi LEMBERSKY

IPC: G06Q10/0631 ,  G06Q10/0639

CPC classification number: G06Q10/06312 ,  G06Q10/063112 ,  G06Q10/06395

Abstract: A computerized system and method for allocating multi-functional or multi-feature resources (which may handle multiple functions or tasks, e.g., simultaneously) for a plurality of time intervals, including: transforming an initial allocation matrix (which may associate each resource with a single function, task, or feature - and may not address simultaneous handling of tasks or task types by the resources) into an updated allocation matrix, where the updated allocation matrix includes a plurality of feature matrices describing different multi-feature resources to be allocated; predicting, using a machine learning (ML) model, expected service metrics for the updated allocation matrix; and providing a final allocation matrix based on the expected service metrics. Embodiments may perform iterative calculations and/or transformations of data to improve allocation matrices and provide a final allocation matrix for which predicted service metrics correspond to required or optimal service metrics.

公开(公告)号：US20230297909A1

公开(公告)日：2023-09-21

申请号：US18096732

申请日：2023-01-13

Applicant: Nice Ltd.

Inventor： Noam KAPLAN ,  Ying ZHANG ,  Gennadi LEMBERSKY ,  Nick MARTIN ,  Eyal SEGAL

IPC: G06Q10/0631

CPC classification number: G06Q10/063112 ,  G06Q10/06316

Abstract: Methods and systems for, upon receipt of a second computer data stream, predicting a change in processing a first computer data stream, include: receiving, at a computing device, the first computer data stream; generating a first data sequence comprising a time of receipt of the first computer data stream; receiving the second computer data stream; generating a second data sequence comprising a time of receipt of the second computer data stream; sending the first and second data sequences to a prediction model; predicting, by the prediction model, at least one change in at least one metric associated with processing the first computer data stream, the predicted change based at least in part on the first and second data sequences; and sending, by the prediction model, to the computing device, the at least one change in the at least one metric associated with processing the first computer data stream.