公开(公告)号：US20250053905A1

公开(公告)日：2025-02-13

申请号：US18232397

申请日：2023-08-10

Applicant: NICE LTD.

Inventor： Eran ROSEBERG ,  Oz GRANIT ,  Yuval SHACHAF

IPC: G06Q10/0631 ,  G06F9/451 ,  G06F40/30

Abstract: A computer-implemented method for unsupervised task segmentation. The computer-implemented method includes receiving a stream of data of desktop-actions. Each desktop-action relates to UI data-handling operations of applications, and labeled with an action-related integer id, operating an unsupervised task segmentation module on the stream of data of desktop-actions to identify sequences of desktop-actions. The unsupervised task segmentation module includes creating an integer sequence from the action related integer id, such that desktop-actions are consecutively concatenated, creating word embeddings of the UI data-handling operations of applications for each desktop-action based on the integer id thereof, to yield a vector of embeddings, and implementing unsupervised topic-segmentation NLP module on the created vector of embeddings to determine cutting-points in the integer sequence to yield segments such that semantic-similarity-level of embeddings in each yielded segment is maximized, and a number of non-complete business processes is reduced. Each cutting-point indicates an end of a segment.

公开(公告)号：US20240176673A1

公开(公告)日：2024-05-30

申请号：US18072349

申请日：2022-11-30

Applicant: Nice Ltd.

Inventor： Eran ROSEBERG ,  Yuval SHACHAF ,  Oz GRANIT

IPC: G06F9/50

CPC classification number: G06F9/5061

Abstract: A computerized system and method may generate computer automation opportunities based on segmenting action sequences from action data and/or information items. A computerized system including a processor or a plurality of processors, and a memory including a data store of a plurality of data items describing actions input to a computer may be used to receive an input query or a plurality of actions input to a computer; segment action sequences from the stored data items based on the query; and produce automation candidates based on the segmented sequences. Embodiments of the invention may include generating, by a machine learning model, vector embeddings for action sequences, calculating similarity scores for sequences based on the embeddings, and mining a plurality of action subsequences based on, a group or set of similar sequences, as well as additional and/or auxiliary procedures and operations.

公开(公告)号：US20230359659A1

公开(公告)日：2023-11-09

申请号：US17737495

申请日：2022-05-05

Applicant: NICE LTD

Inventor： Oz GRANIT ,  Yuval SHACHAF ,  Eran ROSEBERG

IPC: G06F16/35

CPC classification number: G06F16/355

Abstract: A system and method may identify computer-based processes involving the use of text templates which may be candidates for automation. Using one or more computers, embodiments of the invention may sort low-level user action information for a given process which may be received as input; search for a plurality of strings pasted multiple times in the sorted information; discard one or more of the strings found from the search which correspond to a set of criteria (e.g., found to be shorter, or pasted, or edited fewer times than a predetermined threshold); group the strings according to an identifier of the target app where each string was pasted; iteratively calculate a similarity score for strings or groups of strings, and cluster strings or groups for which the similarity score is below a predetermined threshold, to form final clusters; and suggest the final clusters as automation opportunities to, e.g., a business analyst.