Microsoft Technology Licensing, LLC

Donald Brinkman

Emmanouil Koukoumidis

Joseph Edwin Johnson, Jr

Hailong Mu

Dustin Isaac Abramson

Hudong Wang

Di Li

Ying Wang

Kati Amanda London

Zhan Chen

Matthew W Schuerman

Steven G Zittrower

Kelli A Stuckart

Maria A Rangel

Pengfei Hao

Steven Mark Drucker

Danyel Aharon Fisher

Jian Zhao

Oussama Elachqar

Maria Alexandropoulou

Youssef Hammad

Dan Vann

Joseph Edwin Johnson

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.

Memorable event detection, recording, and exploitation

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.

Conversational system user behavior identification

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.

Conversation bot discovery and response fusion

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.

Conversational system user experience

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.

Systems and methods for a personality consistent chat bot

Technology for rendering representations of multi-faceted data are disclosed. As one example, the technology includes organizing and rendering multiple subsets of a dataset according to temporal or other linear attributes, e.g., for visual comparison and/or other visualization. A collection of subsets may be determined in response to a selection of a facet having multiple facet attributes. Each subset may include the entries of the dataset that have the facet attribute corresponding to that subset. Optionally, the multiple subsets may be rendered in alignment with corresponding portions of a hierarchical depiction, e.g., to visually represent the parameters of the subsets.

Relational rendering of multi-faceted data

A navigation mechanism for hierarchical data uses a climb/dive and rotate inputs to traverse a hierarchical dataset. The hierarchical dataset may be arranged in a filial-heir arrangement for easy traversal. The navigation mechanism may be used with several different ways of displaying the data, some of which may display both overall context and detailed view of the data. One such example may have a context section and a detail section, where the context section may present the overall context of a focus node in relation to the overall dataset and the detail section may display other nodes that are at the same or lower level than the focus node.

Navigation of hierarchical data using climb/dive and spin inputs

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Seattle, WA, United States of America

Donald Brinkman