Abstract: The present disclosure provides method and apparatus for providing a response to a user in a session. At least one message associated with a first object may be received in the session, the session being between the user and an electronic conversational agent. An image representation of the first object may be obtained. Emotion information of the first object may be determined based at least on the image representation. A response may be generated based at least on the at least one message and the emotion information. The response may be provided to the user.

Abstract: Aspects of the present disclosure provide systems and methods for detecting memorable events of a user, storing those memorable events in a user profile, and leveraging those events to the user. In so doing, memorable events with positive emotional weight may be recalled to encourage delightful experiences. Alternatively or additionally, memorable events with negative emotional weight may be recalled to increase user engagement for conversational systems.

Abstract: The present application discloses a data processing method and apparatus, a device, and a storage medium. The specific implementation solution is: acquiring attribute information of a detection object, where the attribute information includes a type of the detection object and at least one of the following: a level coefficient of the detection object and a validity of the detection object; a processing module, configured to test a tested object by the detection object according to the type of the detection object to obtain a test result, where the test result includes first abnormal information detected in the tested object; the processing module is further configured to update the attribute information of the detection object according to the test result. In the above solution, the attribute information of the detection object needs no manual intervention and can be updated in time, thereby reducing quality risks.

Abstract: Systems and methods for automated mathematical chatting. The systems and methods convert any identified non-numerical inputs into vectors and then perform the mathematical equation utilizing the vectors instead of the nonnumeric inputs along with any other identified numeric inputs to obtain a numerical vector result. The systems and methods decode the numerical vector result into a result feature and then search one or more databases for output based on the result feature. The systems and methods provide the selected output from the one or more databases in response to the mathematical query.

Abstract: The present disclosure provides method and apparatus for providing a response to a user in a session. At least one message associated with a first object may be received in the session, the session being between the user and an electronic conversational agent. An image representation of the first object may be obtained. Emotion information of the first object may be determined based at least on the image representation. A response may be generated based at least on the at least one message and the emotion information. The response may be provided to the user.

Abstract: Systems and methods are disclosed for response retrieval using communication session vectors. In one implementation, a first communication session is received. The first communication session includes a first communication. The first communication session is encoded as a first vector. A second vector is identified within a defined proximity of the first vector. The second vector represents a second communication session that includes a second communication. The second communication is provided within the first communication session in response to the first communication.

Abstract: Representative embodiments disclose mechanisms for discovering, synthesizing, presenting and interacting with multiple chat bots. A broker system can interact with a user and receive a query which is passed to a search engine. The search results are evaluated for bots provided by domains. The query can be submitted to the discovered bots. For domains that do not provide a bot, a bot can be synthesized if desired and the query submitted to the synthesized bots. Answers from the bots are retrieved. Answer are directly presented for bots that are directly surfaced to the user in the search results page. Answers can be fused for bots that are not directly surfaced to the user and presented via a broker bot. Answers from the one bot can be fed to other bots so that the bots can participate in a group chat between bots and the user.

Abstract: Examples of the present disclosure describe systems and methods relating to conversational system user experience. In an example, a conversational system may use one or more sensors of a user device to affect the topic or direction of a conversation or to identify a new conversation topic. The conversational system may also receive input from a user, wherein a GUI may enable the user to specify or alter semantic information used during the conversation. The GUI may comprise one or more skeuomorphic elements designed to provide a familiar or intuitive way for the user to interact with the conversational system. The GUI may also be used to disambiguate messages or convey emotion or sentiment to the user. In another example, haptic or audio feedback may be provided alongside a message to convey emotion to the user during the conversation.

Abstract: Systems and methods are disclosed for response retrieval using communication session vectors. In one implementation, a first communication session is received. The first communication session includes a first communication. The first communication session is encoded as a first vector. A second vector is identified within a defined proximity of the first vector. The second vector represents a second communication session that includes a second communication. The second communication is provided within the first communication session in response to the first communication.

Abstract: Systems and methods are disclosed for response retrieval using communication session vectors. In one implementation, a first communication session is received. The first communication session includes a first communication. The first communication session is encoded as a first vector. A second vector is identified within a defined proximity of the first vector. The second vector represents a second communication session that includes a second communication. The second communication is provided within the first communication session in response to the first communication.

Abstract: Systems and methods for personality consistent automated chatting are provided. The systems and methods track the emotional state of the chat bot, track entity related dispositions of the chat bot and/or track the closeness of the relationship between the chat bot and a user. Accordingly, the systems and methods are able to provide consistent personality and/or points of view by generating replies based on the tracked chat bot emotional state, chat bot entity dispositions, and/or the relationship closeness between the chat bot and the user.

Abstract: Systems and methods are disclosed for response retrieval using communication session vectors. In one implementation, a first communication session is received. The first communication session includes a first communication. The first communication session is encoded as a first vector. A second vector is identified within a defined proximity of the first vector. The second vector represents a second communication session that includes a second communication. The second communication is provided within the first communication session in response to the first communication.

Abstract: Aspects of the present disclosure provide systems and methods for detecting memorable events of a user, storing those memorable events in a user profile, and leveraging those events to the user. In so doing, memorable events with positive emotional weight may be recalled to encourage delightful experiences. Alternatively or additionally, memorable events with negative emotional weight may be recalled to increase user engagement for conversational systems.

Abstract: Examples of the present disclosure describe systems and methods relating to conversational system user experience. In an example, a conversational system may use one or more sensors of a user device to affect the topic or direction of a conversation or to identify a new conversation topic. The conversational system may also receive input from a user, wherein a GUI may enable the user to specify or alter semantic information used during the conversation. The GUI may comprise one or more skeuomorphic elements designed to provide a familiar or intuitive way for the user to interact with the conversational system. The GUI may also be used to disambiguate messages or convey emotion or sentiment to the user. In another example, haptic or audio feedback may be provided alongside a message to convey emotion to the user during the conversation.

Abstract: Systems and methods for personality consistent automated chatting are provided. The systems and methods track the emotional state of the chat bot, track entity related dispositions of the chat bot and/or track the closeness of the relationship between the chat bot and a user. Accordingly, the systems and methods are able to provide consistent personality and/or points of view by generating replies based on the tracked chat bot emotional state, chat bot entity dispositions, and/or the relationship closeness between the chat bot and the user.

Abstract: Representative embodiments disclose mechanisms for discovering, synthesizing, presenting and interacting with multiple chat bots. A broker system can interact with a user and receive a query which is passed to a search engine. The search results are evaluated for bots provided by domains. The query can be submitted to the discovered bots. For domains that do not provide a bot, a bot can be synthesized if desired and the query submitted to the synthesized bots. Answers from the bots are retrieved. Answer are directly presented for bots that are directly surfaced to the user in the search results page. Answers can be fused for bots that are not directly surfaced to the user and presented via a broker bot. Answers from the one bot can be fed to other bots so that the bots can participate in a group chat between bots and the user.

Abstract: Systems and methods for automated mathematical chatting. The systems and methods convert any identified non-numerical inputs into vectors and then perform the mathematical equation utilizing the vectors instead of the nonnumeric inputs along with any other identified numeric inputs to obtain a numerical vector result. The systems and methods decode the numerical vector result into a result feature and then search one or more databases for output based on the result feature. The systems and methods provide the selected output from the one or more databases in response to the mathematical query.

Abstract: Identifying a location of a mobile device is disclosed (e.g., presuming user consent to the same). One or more received signal strengths (RSSs), comprising a first RSS, may be received by a first access point (AP) from the mobile device. The RSSs may be used to identify a grid area, comprising a first grid space. A signal distance between the first grid space and the first AP may be identified using the first RSS, and combined with a first grid space distance, comprising a known distance between the first grid space and the first AP, to determine a first grid space likelihood score for the first grid space. A second grid space likelihood score may be determined for a second grid space (e.g., and a third, etc.), and the grid space comprising a desired grid space likelihood score (e.g., highest) may be selected as the mobile device location.

Abstract: Identifying a location of a mobile device is disclosed (e.g., presuming user consent to the same). One or more received signal strengths (RSSs), comprising a first RSS, may be received by a first access point (AP) from the mobile device. The RSSs may be used to identify a grid area, comprising a first grid space. A signal distance between the first grid space and the first AP may be identified using the first RSS, and combined with a first grid space distance, comprising a known distance between the first grid space and the first AP, to determine a first grid space likelihood score for the first grid space. A second grid space likelihood score may be determined for a second grid space (e.g., and a third, etc.), and the grid space comprising a desired grid space likelihood score (e.g., highest) may be selected as the mobile device location.

Abstract: Identifying a location of a mobile device is disclosed (e.g., presuming user consent to the same). One or more received signal strengths (RSSs), comprising a first RSS, may be received by a first access point (AP) from the mobile device. The RSSs may be used to identify a grid area, comprising a first grid space. A signal distance between the first grid space and the first AP may be identified using the first RSS, and combined with a first grid space distance, comprising a known distance between the first grid space and the first AP, to determine a first grid space likelihood score for the first grid space. A second grid space likelihood score may be determined for a second grid space (e.g., and a third, etc.), and the grid space comprising a desired grid space likelihood score (e.g., highest) may be selected as the mobile device location.