최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
DataON 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Edison 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Kafe 바로가기국가/구분 | United States(US) Patent 등록 |
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국제특허분류(IPC7판) |
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출원번호 | US-0725550 (2012-12-21) |
등록번호 | US-8942986 (2015-01-27) |
발명자 / 주소 |
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출원인 / 주소 |
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대리인 / 주소 |
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인용정보 | 피인용 횟수 : 44 인용 특허 : 1624 |
Methods, systems, and computer readable storage medium related to operating an intelligent digital assistant are disclosed. A plurality of predefined domains each representing a respective area of service offered by an intelligent automated assistant are stored. A text string derived from a user req
Methods, systems, and computer readable storage medium related to operating an intelligent digital assistant are disclosed. A plurality of predefined domains each representing a respective area of service offered by an intelligent automated assistant are stored. A text string derived from a user request is obtained, the text string including at least one or more words derived from a speech input received from a user. From the plurality of predefined domains, a relevant domain for the user request is identified based at least on respective degrees of match between the text string derived from the user request and a respective plurality of words associated with each predefined domain. A task is executed in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request.
1. A method for operating an intelligent automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: storing a plurality of predefined domains each representing a respective area of service offered by the intelligent
1. A method for operating an intelligent automated assistant, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: storing a plurality of predefined domains each representing a respective area of service offered by the intelligent automated assistant, wherein each of the predefined domains comprises a respective plurality of concepts and one or more relations relating the respective plurality of concepts, wherein each predefined domain is associated with at least one task flow specifying steps for performing a respective task in the predefined domain, and wherein each of the predefined domains is associated with a respective plurality of words relevant to the predefined domain;obtaining a text string derived from a user request, the text string including at least one or more words derived from a speech input received from a user;from the plurality of predefined domains, identifying a relevant domain for the user request based at least on respective degrees of match between the text string derived from the user request and the respective plurality of words associated with each predefined domain; andexecuting a task in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request. 2. The method of claim 1, wherein the respective plurality of words associated with each predefined domain comprises at least two respective words that each represent a concept related to the predefined domain or an entity related to the predefined domain. 3. The method of claim 1, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service on behalf of the user, the application or web-based service operable to provide the one or more functions directly to the user through a user interface of the application or web-based service. 4. The method of claim 1, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service that provides no user interface for direct user access to the one or more functions. 5. The method of claim 1, wherein the degrees of match includes degrees of semantic match and degrees of phonetic match between the text string derived from the user request and the respective plurality of words associated with each predefined domain. 6. The method of claim 1, wherein identifying the relevant domain from the plurality of predefined domains further comprises: generating two or more semantic parses from the text string, each semantic parse associating the text string with two or more concepts of a respective one of the plurality of predefined domains;from among the two or more semantic parses, selecting a candidate semantic parse that associates the text string with two or more concepts of a first predefined domain, wherein the selecting is based at least on a strength of connections existing between the two or more concepts in the first predefined domain; andidentifying the relevant domain based on the candidate semantic parse. 7. The method of claim 1, wherein at least one of the plurality of predefined domains is associated with a dialog flow, the dialog flow specifying steps for the intelligent automated assistant to request information regarding one or more task parameters for a respective task associated with the at least one predefined domain. 8. The method of claim 1, wherein the user request further includes context information associated with the speech input received from the user, and one or more of the task parameters are derived based on the context information. 9. A system, comprising: one or more processors; andmemory having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: storing a plurality of predefined domains each representing a respective area of service offered by an intelligent automated assistant, wherein each of the predefined domains comprises a respective plurality of concepts and one or more relations relating the respective plurality of concepts, wherein each predefined domain is associated with at least one task flow specifying steps for performing a respective task in the predefined domain, and wherein each of the predefined domains is associated with a respective plurality of words relevant to the predefined domain;obtaining a text string derived from a user request, the text string including at least one or more words derived from a speech input received from a user;from the plurality of predefined domains, identifying a relevant domain for the user request based at least on respective degrees of match between the text string derived from the user request and the respective plurality of words associated with each predefined domain; andexecuting a task in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request. 10. The system of claim 9, wherein the respective plurality of words associated with each predefined domain comprises at least two respective words that each represent a concept related to the predefined domain or an entity related to the predefined domain. 11. The system of claim 9, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service on behalf of the user, the application or web-based service operable to provide the one or more functions directly to the user through a user interface of the application or web-based service. 12. The system of claim 9, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service that provides no user interface for direct user access to the one or more functions. 13. The system of claim 9, wherein the degrees of match includes degrees of semantic match and degrees of phonetic match between the text string derived from the user request and the respective plurality of words associated with each predefined domain. 14. The system of claim 9, wherein identifying the relevant domain from the plurality of predefined domains further comprises: generating two or more semantic parses from the text string, each semantic parse associating the text string with two or more concepts of a respective one of the plurality of predefined domains;from among the two or more semantic parses, selecting a candidate semantic parse that associates the text string with two or more concepts of a first predefined domain, wherein the selecting is based at least on a strength of connections existing between the two or more concepts in the first predefined domain; andidentifying the relevant domain based on the candidate semantic parse. 15. The system of claim 9, wherein at least one of the plurality of predefined domains is associated with a dialog flow, the dialog flow specifying steps for the intelligent automated assistant to request information regarding one or more task parameters for a respective task associated with the at least one predefined domain. 16. The system of claim 9, wherein the user request further includes context information associated with the speech input received from the user, and one or more of the task parameters are derived based on the context information. 17. A non-transitory computer readable storage medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: storing a plurality of predefined domains each representing a respective area of service offered by an intelligent automated assistant, wherein each of the predefined domains comprises a respective plurality of concepts and one or more relations relating the respective plurality of concepts, wherein each predefined domain is associated with at least one task flow specifying steps for performing a respective task in the predefined domain, and wherein each of the predefined domains is associated with a respective plurality of words relevant to the predefined domain;obtaining a text string derived from a user request, the text string including at least one or more words derived from a speech input received from a user;from the plurality of predefined domains, identifying a relevant domain for the user request based at least on respective degrees of match between the text string derived from the user request and the respective plurality of words associated with each predefined domain; andexecuting a task in accordance with steps specified in a task flow associated with the relevant domain, and in accordance with one or more task parameters derived from the user request. 18. The computer readable storage medium of claim 17, wherein the respective plurality of words associated with each predefined domain comprises at least two respective words that each represent a concept related to the predefined domain or an entity related to the predefined domain. 19. The computer readable storage medium of claim 17, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service on behalf of the user, the application or web-based service operable to provide the one or more functions directly to the user through a user interface of the application or web-based service. 20. The computer readable storage medium of claim 17, wherein at least one of the plurality of predefined domains is associated with a respective service model specifying an API for accessing one or more functions of an application or web-based service that provides no user interface for direct user access to the one or more functions. 21. The computer readable storage medium of claim 17, wherein the degrees of match includes degrees of semantic match and degrees of phonetic match between the text string derived from the user request and the respective plurality of words associated with each predefined domain. 22. The computer readable storage medium of claim 17, wherein identifying the relevant domain from the plurality of predefined domains further comprises: generating two or more semantic parses from the text string, each semantic parse associating the text string with two or more concepts of a respective one of the plurality of predefined domains;from among the two or more semantic parses, selecting a candidate semantic parse that associates the text string with two or more concepts of a first predefined domain, wherein the selecting is based at least on a strength of connections existing between the two or more concepts in the first predefined domain; andidentifying the relevant domain based on the candidate semantic parse. 23. The computer readable storage medium of claim 17, wherein at least one of the plurality of predefined domains is associated with a dialog flow, the dialog flow specifying steps for the intelligent automated assistant to request information regarding one or more task parameters for a respective task associated with the at least one predefined domain. 24. The computer readable storage medium of claim 17, wherein the user request further includes context information associated with the speech input received from the user, and one or more of the task parameters are derived based on the context information.
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