Intelligent Forecasting with Benchmarks
    1.
    发明公开

    公开(公告)号:US20240232778A1

    公开(公告)日:2024-07-11

    申请号:US18095244

    申请日:2023-01-10

    IPC分类号: G06Q10/0639 G06Q10/0637

    CPC分类号: G06Q10/06393 G06Q10/06375

    摘要: A method for providing benchmark-plans to a customer based on benchmark information, comprising receiving a customer-defined service goal and a demand forecast for the customer; generating, with a planner, a plan for achieving the customer-defined service goal based on the demand forecast; determining a benchmark category from a plurality of benchmark categories that the customer belongs to based on at least an industry of the customer, wherein the benchmark category defines a plurality of other customer-defined service goals for other customers participating in at least the industry as the customer; determining benchmark service goals based on the determined benchmark category; executing the planner for each of the benchmark service goals thereby generating benchmark-plans for the demand forecast for the customer; and outputting, to the customer, the plan and the benchmark-plans, wherein the benchmark-plans are different from the plan.

    Machine based expansion of contractions in text in digital media

    公开(公告)号:US11907656B2

    公开(公告)日:2024-02-20

    申请号:US17705898

    申请日:2022-03-28

    发明人: Ian Beaver

    IPC分类号: G06F40/253

    CPC分类号: G06F40/253

    摘要: As described herein, a system for expanding contractions in electronically stored text includes expanding contractions having only on expanded form. For remaining contractions, a grammar check is performed for all possible expanded forms to determine if an expanded form can be selected based on context and grammar rules. If an expanded form is not evident from the first two steps, all possible expanded forms of the remaining contractions are converted to a vector representation along with the original text. A Word Movers Distance (WMD) for each possible expansion is calculated using the vectors for each possible expansion and the original text. An expanded form is chosen without human intervention based on the grammar score alone or the WMD and the grammar score.

    GENERATING CONVERSATIONAL AI RESPONSE SUGGESTIONS

    公开(公告)号:US20240037344A1

    公开(公告)日:2024-02-01

    申请号:US17815042

    申请日:2022-07-26

    发明人: Timothy Hewitt

    IPC分类号: G06F40/40

    CPC分类号: G06F40/40

    摘要: The present disclosure describes methods and systems for suggesting responses generated from an entity's own published information with links to the source of that generated response should provide a quality starting point that is already accurate and brand compliant or, if not, quickly editable to become so. The published information is ingested by the system, and a question/answer transformation process is applied against the ingested data using training language data that is tagged and categorized by intent to generate suggested responses. The suggested response may be presented in a user interface with a link to the URL which was used to construct the response. The suggested responses may be edited if needed.

    Task Gathering for Asynchronous Task-Oriented Virtual Assistants

    公开(公告)号:US20240037334A1

    公开(公告)日:2024-02-01

    申请号:US17875790

    申请日:2022-07-28

    摘要: 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 destination entity 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 another computer. Before the IVA contacts the destination entity, a specific user profile is injected into an IVA dialog state. The IVA contacts the destination entity and answers customer service agent (CSA) questions by using the specific user profile inserted. 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.

    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

    IPC分类号: G06F9/451 G06Q30/00 G06F40/40

    摘要: 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

    IPC分类号: G06N5/02

    CPC分类号: G06N5/022

    摘要: 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.