Abstract: Architecture that enables geofence combinations and compositions where multiple correlated geofences are generated for an entity such as a point of interest. The geofences can have varying radii relative to a specific entity and represent distinct areas or aspects of the entity. The geofences can relate to correspondingly different categories to which the entity can belong. The geofences can be of differing shapes than circular, such as polygons (e.g., rectangles, squares, etc.). Moreover, these differently shaped geofences can be applied to a single entity. Each geofence of a geofence set associated with an entity can be assigned to represent different parts of an entity such as a part a shopping mall. Geofence composition is obtained by combining multiple primitive geofences to compose more complex geofence(s) for an entity and for embedding the relationship of the primitive geofences into such compositions.

Abstract: Examples of the present disclosure describe systems and methods relating to conversational system user behavior identification. A user of the conversational system may be evaluated based on one or more factors. The one or more factors may be compared to an aggregated measure for a larger group of conversational system users, such that “anomalous” behavior (e.g., behavior that deviates from a normal behavior) may be identified. When a user is identified as exhibiting anomalous behavior, the conversational system may adapt its interactions with the user in order to encourage, discourage, or further observe the identified behavior. As a result, the conversational system may be able to verify a user's anomalous behavior, discourage the anomalous behavior, or take other action while interacting with 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: Systems and methods are disclosed for conversationally-relevant content requests. In one implementation, a first communication is processed to identify a first content element within the communication. The first content element is stored within a first content repository. A content request is generated based on the first content repository. The content request is provided to the user. A second communication is received from the user in response to the content request. An action is initiated based on the second communication.

Abstract: A system provides emotionally and intellectually relevant responses to user queries received by a chatbot instantiated by a computing device. The system also receives user data associated with the user query. The user query is communicated to a first supervised machine learning model to obtain a first plurality of ranked responses. The system also communicates the received user data to a second supervised machine learning model to obtain a first plurality of emotions associated with the user data. The system then determines determine a second plurality of emotions for the first plurality of responses and re-ranks the first plurality of responses based on a comparison of the first plurality of emotions and the second plurality of emotions. The system then selects a response to the user query from the re-ranked responses and outputs the selected response using the chatbot instantiated by the computing device.

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: Architecture that enables geofence combinations and compositions where multiple correlated geofences are generated for an entity such as a point of interest. The geofences can have varying radii relative to a specific entity and represent distinct areas or aspects of the entity. The geofences can relate to correspondingly different categories to which the entity can belong. The geofences can be of differing shapes than circular, such as polygons (e.g., rectangles, squares, etc.). Moreover, these differently shaped geofences can be applied to a single entity. Each geofence of a geofence set associated with an entity can be assigned to represent different parts of an entity such as a part a shopping mall. Geofence composition is obtained by combining multiple primitive geofences to compose more complex geofence(s) for an entity and for embedding the relationship of the primitive geofences into such compositions.

Abstract: Examples of the present disclosure describe systems and methods relating to conversational system user behavior identification. A user of the conversational system may be evaluated based on one or more factors. The one or more factors may be compared to an aggregated measure for a larger group of conversational system users, such that “anomalous” behavior (e.g., behavior that deviates from a normal behavior) may be identified. When a user is identified as exhibiting anomalous behavior, the conversational system may adapt its interactions with the user in order to encourage, discourage, or further observe the identified behavior. As a result, the conversational system may be able to verify a user's anomalous behavior, discourage the anomalous behavior, or take other action while interacting with the user.

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: Examples of the present disclosure describe systems and methods relating to conversational system user behavior identification. A user of the conversational system may be evaluated based on one or more factors. The one or more factors may be compared to an aggregated measure for a larger group of conversational system users, such that “anomalous” behavior (e.g., behavior that deviates from a normal behavior) may be identified. When a user is identified as exhibiting anomalous behavior, the conversational system may adapt its interactions with the user in order to encourage, discourage, or further observe the identified behavior. As a result, the conversational system may be able to verify a user's anomalous behavior, discourage the anomalous behavior, or take other action while interacting with 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: Systems and methods for receiving various input data, processing said input data, and utilizing artificial emotional intelligence to analyze said input data to return calculated response stimuli are provided. Various electronic devices may be utilized to acquire input data related to a specific user, a group of users, or environments. This input data, which may comprise tone of voice, facial expressions, social media profiles, and surrounding environmental data, may be compared with past data related to a certain user, group of users, or environment. The systems and methods herein may employ artificial emotional intelligence to evaluate the aggregated data and provide a response stimulus to a user or group of users. The response stimulus may be in the form of uplifting/encouraging music, quotes, pictures, jokes, suggestions, etc. The purpose of providing the response stimuli is to significantly increase the productivity of meetings, conversations, and other interactions across electronic devices.

Abstract: Architecture that enables the capability to more effectively define and resize geofences to provide improved geofence utility based on rich context and crowd-sourced data. The architecture enables the intelligent placement of geofences based on rich context that includes both user context and ambient context such as the (predicted or implicitly/explicitly defined) user's travel path, mode of transport, the type of the entity to be visited by the user and geofenced, and the user incentive for visiting the entity to be geofenced. The ambient context includes non-user specific information such as external conditions that may limit or thwart user mobility such as traffic and weather conditions. The rich context and crowd-sourced data assist in improving the spatiotemporal accuracy of suggested/constructed geofences thereby creating a “shaped” geofence that is sufficiently defined to approximate the shape of the entity being geofenced with some degree of accuracy.

Abstract: A server device configured to execute an electronic data analysis platform program to store a plurality of modular data processing tools, each modular data processing tool configured to perform data processing with predetermined data types and to combine with other modular data processing tools in a data analysis pipeline, receive a user input of one or more user data sources, map the data of the one or more user data sources to one or more of the predetermined data types, determine a data analytic goal for the mapped one or more user data sources, select one or more modular data processing tools configured to process the one or more predetermined data types mapped to data of the mapped one or more user data sources to generate the data analytic goal, and generate a data analysis pipeline configured to generate the data analytic goal.

Abstract: Among other things, one or more techniques and/or systems are provided for annotating content based upon user reaction data and/or for maintaining a searchable content repository. That is, a user may request and/or opt-in for user reaction data to be detected while a user is experiencing content (e.g., watching a movie, walking through a park, interacting with a website, participating on a phone conversation, etc.). Metadata associated with the content may be used to determine when and/or what sensors to use to detect the user reaction data (e.g., metadata specifying an emotional part of a movie). The content may be annotated with a reaction annotation corresponding to the user reaction data, which may be used to organize, search, and/or interact with the content. A search interface may allow users to search for content based upon annotation data and/or aggregated annotation data of one or more users who experienced the content.

Abstract: Among other things, one or more techniques and/or systems are provided for annotating content based upon user reaction data and/or for maintaining a searchable content repository. That is, a user may request and/or opt-in for user reaction data to be detected while a user is experiencing content (e.g., watching a movie, walking through a park, interacting with a website, participating on a phone conversation, etc.). Metadata associated with the content may be used to determine when and/or what sensors to use to detect the user reaction data (e.g., metadata specifying an emotional part of a movie). The content may be annotated with a reaction annotation corresponding to the user reaction data, which may be used to organize, search, and/or interact with the content. A search interface may allow users to search for content based upon annotation data and/or aggregated annotation data of one or more users who experienced the content.

Abstract: An application programming interface is provided that allows applications to request and receive distance measurements from multiple proximity sensors arranged on a computing device such as a smart phone or tablet. Users can input ranges of values to the applications by moving objects such as hands and fingers towards and away one or more of the multiple proximity sensors. Applications can use the ranges of values provided by the proximity sensors to allow for more nuanced and precise user interfaces than what is typically available using the binary output associated with a capacitive display. The values provided by the proximity sensors can be combined with values from one or more other sensors such as accelerometers to provide additional user interface options.

Abstract: An application programming interface is provided that allows applications to request and receive distance measurements from multiple proximity sensors arranged on a computing device such as a smart phone or tablet. Users can input ranges of values to the applications by moving objects such as hands and fingers towards and away one or more of the multiple proximity sensors. Applications can use the ranges of values provided by the proximity sensors to allow for more nuanced and precise user interfaces than what is typically available using the binary output associated with a capacitive display. The values provided by the proximity sensors can be combined with values from one or more other sensors such as accelerometers to provide additional user interface options.