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1.发明公开公开(公告)号：US20230401242A1
公开(公告)日：2023-12-14
申请号：US17806559
申请日：2022-06-13
IPC分类号： G06F16/332 , G06F16/31
CPC分类号： G06F16/332 , G06F16/316
摘要： In an approach for a cooperative build and content annotation system for conversational design of virtual assistants, a processor formulates a build context based on a build activity of a user. A processor formulates one or more content queries based on the build context. A processor builds a content index by augmenting a text-search index with a neural Information Retrieval (IR) index. A processor searches the content index using the one or more content queries to identify content relevant to the build context. A processor determines at least one recommendation for the user based on heuristic rules applied to the build context and the identified content, wherein each recommendation is a build suggestion or a content annotation suggestion.
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公开(公告)号：US20240104307A1
公开(公告)日：2024-03-28
申请号：US17953443
申请日：2022-09-27
发明人： Muhtar Burak Akbulut , Pankaj Dhoolia , Dan O'Connor , Andy James Stoneberg , Venkat Raghavan Ganesh Sekar
摘要： A plurality of constraints associated with conversational steps implemented by a conversation model is extracted from the conversation model. Using the conversational steps and the constraints, a directed graph is constructed, each node in the directed graph representing a conversational step, each directed edge in the directed graph representing a possible execution path from a first conversational step to a second conversational step. An edge in the graph is populated with flow data denoting a probability associated with the edge. By traversing a portion of the graph, an experience preview is generated, the experience preview demonstrating a user experience of a portion of the conversation model.
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公开(公告)号：US11853335B1
公开(公告)日：2023-12-26
申请号：US17806559
申请日：2022-06-13
IPC分类号： G06F16/332 , G06F16/31
CPC分类号： G06F16/332 , G06F16/316
摘要： In an approach for a cooperative build and content annotation system for conversational design of virtual assistants, a processor formulates a build context based on a build activity of a user. A processor formulates one or more content queries based on the build context. A processor builds a content index by augmenting a text-search index with a neural Information Retrieval (IR) index. A processor searches the content index using the one or more content queries to identify content relevant to the build context. A processor determines at least one recommendation for the user based on heuristic rules applied to the build context and the identified content, wherein each recommendation is a build suggestion or a content annotation suggestion.
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