USER PERSONA INJECTION FOR TASK-ORIENTED VIRTUAL ASSISTANTS

    公开(公告)号:US20240036893A1

    公开(公告)日:2024-02-01

    申请号:US17815685

    申请日:2022-07-28

    CPC classification number: G06F9/453 G06Q30/016 G06F40/40

    Abstract: An intelligent virtual assistant (IVA) is deployed to place a call/chat to customer service on behalf of the customer, thus saving them time and frustration. The IVA contacts a specific company over one or more channels, for example, chat, phone call, Application Programming Interface (API), or email, in order to complete open-ended task(s) requested by its user. Before the IVA contacts the company, a specific user profile is injected into an IVA dialog state. The IVA contacts the company or agency and answers customer service agent (CSA) questions by using the specific user profile provided for the call. The IVA then stores the task outcome for the user to review. If something prevents the task from succeeding, the IVA alerts the user that either it needs more information or the user may need to perform some action before the task can be completed, such as filling out or emailing a form.

    SELECTING FORECASTING ALGORITHMS USING MOTIFS

    公开(公告)号:US20240020545A1

    公开(公告)日:2024-01-18

    申请号:US17812312

    申请日:2022-07-13

    CPC classification number: G06N5/022

    Abstract: The present disclosure describes methods and systems for selecting the forecasting algorithm to use for a prediction based on motifs. A motif is a pattern of interval values that is found to repeat in time series data. Time series data that includes historical demand data (e.g., average communication volume) for an entity at various time intervals in the past is received. The time series data is processed to identify motifs. For each identified motif, the forecasting algorithm that best predicts the historical demand data for time intervals associated with the motif is determined. Later, when the entity desires to receive a forecast for a future time interval, the motif associated with the future time interval is determined. The forecasting algorithm determined to best predict demand for the determined motif is then used to predict the demand for the future time interval.

    Systems and methods for generating labeled short text sequences

    公开(公告)号:US11797594B2

    公开(公告)日:2023-10-24

    申请号:US17093722

    申请日:2020-11-10

    CPC classification number: G06F16/355 G06F16/367 G06F40/289

    Abstract: A set of documents related to a particular topic, industry, or entity are received. Sentences are extract from each document. The sentences are grouped into tuples of one, two, or three consecutive sentences (i.e., short text sequences). The sentence tuples are clustered based on vector representations of the sentences. For each cluster, a set of tuples that best represents or best fits the cluster is selected. These sentence tuples are fed to an ontology to determine ontological entities associated with each tuple. These determined ontological entities are associated with the clusters corresponding to each tuple. The sentence tuples associated with each cluster are labeled based on the ontological entities associated with the cluster. The labeled sentence tuples may then be used for a variety of purposes such as training a model to determine the topic of short text sequences.

    USER INTERFACE FOR FRAUD ALERT MANAGEMENT
    18.
    发明公开

    公开(公告)号:US20230224403A1

    公开(公告)日:2023-07-13

    申请号:US17986245

    申请日:2022-11-14

    CPC classification number: H04M3/436 H04M2203/6027

    Abstract: A system for a graphical user interface for fraud detection for a call center system includes a processor and a visual display in communication with the processor. The processor causes the visual display to present an identifier corresponding to a communication received; a graphical representation of a threat risk associated with the identifier; a numeric score associated with the threat risk, wherein the numeric score is a weighted score based on a plurality of predetermined factors updated substantially continuously.

    Systems and methods for automatic scheduling of a workforce

    公开(公告)号:US11699112B2

    公开(公告)日:2023-07-11

    申请号:US17840304

    申请日:2022-06-14

    CPC classification number: G06Q10/06311 G06Q10/063116 G06Q10/063 G06Q10/0631

    Abstract: Systems and methods are disclosed for scheduling a workforce. In one embodiment, the method comprises receiving a shift activity template; receiving an association between the shift activity template and at least one worker; and scheduling a plurality of schedulable objects. The scheduling is performed in accordance with a workload forecast and schedule constraints. Each of the schedulable objects is based on the shift activity template. The shift activity template describes a worker activity performed during a shift. The template has range of start times and a variable length for the activity. The activity is associated with a queue.

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