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1. 发明申请

US20220284171A1 HIERARCHICAL STRUCTURE LEARNING WITH CONTEXT ATTENTION FROM MULTI-TURN NATURAL LANGUAGE CONVERSATIONS 有权
公开(公告)号：US20220284171A1
公开(公告)日：2022-09-08
申请号：US17693414
申请日：2022-03-14
申请人： SRIVATSAN LAXMAN , SUPRIYA RAO , SRIKHAR PADMANABHAN
发明人： SRIVATSAN LAXMAN , SUPRIYA RAO , SRIKHAR PADMANABHAN
IPC分类号： G06F40/117 , G06F40/242 , G06F40/268 , G06F40/205 , G06F40/35 , G06F40/284 , G06N3/04
摘要： A computerized method for implementing a neural architecture for hierarchical sequence labelling comprising: providing a neural architecture comprising a set of labelling layers, wherein the neural architecture uses a multi-pass approach on the set of labelling layers, receiving an input sentence; parsing the input sentence; embedding the input sentence into a corresponding character vector and a corresponding word vector to generate a feature vector; passing the feature vector through the neural architecture; and performing a multi-layer labelling procedure on the feature vector with the neural architecture comprising: augmenting a set of corresponding bits of the feature vector, wherein the feature vector is passed through the set of labelling layers of neural architecture.

2. 发明申请

US20160086116A1 METHOD AND SYSTEM OF AN AUTOMATICALLY MANAGED CALENDAR AND CONTEXTUAL TASK LIST 审中-公开
标题翻译：自动管理的日历和上下文任务列表的方法和系统
公开(公告)号：US20160086116A1
公开(公告)日：2016-03-24
申请号：US14810477
申请日：2015-07-27
申请人： SUPRIYA RAO , SRIVATSAN LAXMAN , SUSHIL MITTAL
发明人： SUPRIYA RAO , SRIVATSAN LAXMAN , SUSHIL MITTAL
IPC分类号： G06Q10/06 , G06F3/0484
CPC分类号： G06Q10/06311 , G06F3/0481
摘要： In one aspect, a computer system includes an application implemented with a computer processor that automatically discovers a list items from a set of user data sources, wherein the list items correspond to automatic recommendations for a set of calendar events and tasks, and wherein the list items are discovered programmatically in a set of email conversations and a set of calendar updates. The application extracts the list of items and metadata about the list items from the set of user data sources. The application identifies a type of each list item, wherein a set of types comprises a mandatory-action type and an informative type. The application receives a user created list of items. The application creates an electronic agenda view of the auto-recommended list of items and the user created list of items, and organizes these lists by date. The application populates the electronic agenda view with each item in the user created list of items
摘要翻译：一方面，计算机系统包括用计算机处理器实现的应用程序，其自动从一组用户数据源中发现列表项，其中所述列表项对应于一组日历事件和任务的自动建议，并且其中所述列表项目以编程方式在一组电子邮件对话和一组日历更新中被发现。应用程序从用户数据源集中提取关于列表项的项目和元数据的列表。应用程序识别每个列表项的类型，其中一组类型包括强制动作类型和信息类型。应用程序接收用户创建的项目列表。应用程序创建自动推荐的项目列表和用户创建的项目列表的电子议程视图，并按日期组织这些列表。应用程序使用用户创建的项目列表中的每个项目填充电子议程视图

3. 发明申请

US20200134018A1 MIXED-INITIATIVE DIALOG AUTOMATION WITH GOAL ORIENTATION 审中-公开
公开(公告)号：US20200134018A1
公开(公告)日：2020-04-30
申请号：US16170034
申请日：2018-10-25
申请人： SRIVATSAN LAXMAN , DEVANG SAVITA RAM MOHAN , SUPRIYA RAO
发明人： SRIVATSAN LAXMAN , DEVANG SAVITA RAM MOHAN , SUPRIYA RAO
IPC分类号： G06F17/27 , G06N3/08
摘要： In one aspect, method useful for goal-oriented dialog automation comprising incudes the step of receiving an input message. The method includes the step of implementing an entity tagging operation on the input message. The method includes the step of tagging the message context of the input message to generate a tagged message context. The method includes the step of implementing semantic frame extraction from the tagged message context. The method includes the step of implementing an entity interpretation on the extracted frame. The method includes the step of accessing a database to determine a business schedule and a client profile. The business schedule and the client profile are related to the input message. The method includes the step of implementing a retrieval engine. The retrieval engine obtains one or more response templates. The method includes the step of generating a ranked list of candidate templates from the output of the retrieval engine. Based on the output of the entity interpretation, the business schedule and the client profile, and the ranked list of candidate templates, implementing a candidate eliminator. Based on the output of the candidate eliminator, providing a set of recommended responses. Each recommend response is associated with a confidence score.

4. 发明申请

US20210142291A1 VIRTUAL BUSINESS ASSISTANT AI ENGINE FOR MULTIPOINT COMMUNICATION 有权
公开(公告)号：US20210142291A1
公开(公告)日：2021-05-13
申请号：US17080037
申请日：2020-10-26
申请人： srivatsan LAXMAN , SUPRIYA RAO
发明人： srivatsan LAXMAN , SUPRIYA RAO
IPC分类号： G06Q10/10 , G06F16/22 , G06F16/28 , G06N5/02
摘要： A computerized method includes receiving a dialog session. The dialog session comprises a set of new inbound messages. The method feeds the dialog session into tokenizer. The method, with the tokenizer, generates a set of tokens by breaking the new inbound messages into a sequence of tokens. The method provides the tokens to a DAG frame labeler cascade. With the DAG frame labeler cascade, the method uses a sequence of tokens to generate a set of token labels. The method passes the token labels and tokens to an entity interpreter. With the entity interpreter, the method generates a DAG frame. With the DAG frame, the method outputs a structured information from a multiturn dialogue.

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