AUTOMATIC RULE GENERATION FOR NEXT-ACTION RECOMMENDATION ENGINE
A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior patte...
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Main Authors | , , , |
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Format | Patent |
Language | English |
Published |
28.01.2021
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Abstract | A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data. |
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AbstractList | A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data. |
Author | Grissen, Darrell Zhang, Yuxi Xie, Kexin Mallick, Shrestha Basu |
Author_xml | – fullname: Zhang, Yuxi – fullname: Mallick, Shrestha Basu – fullname: Xie, Kexin – fullname: Grissen, Darrell |
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Snippet | A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior... |
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SubjectTerms | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
Title | AUTOMATIC RULE GENERATION FOR NEXT-ACTION RECOMMENDATION ENGINE |
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