Abstract: Detecting propensity profile for a person may comprise receiving artifacts associated with the person; detecting profile characteristics for the person based on the artifacts; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time, each of the plurality of predefined profiles specifying an indication of propensity; matching the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time.

Abstract: Detecting propensity profile for a person may comprise receiving artifacts associated with the person; detecting profile characteristics for the person based on the artifacts; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time, each of the plurality of predefined profiles specifying an indication of propensity; matching the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time.

Abstract: Detecting propensity profile for a person may comprise receiving artifacts associated with the person; detecting profile characteristics for the person based on the artifacts; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time, each of the plurality of predefined profiles specifying an indication of propensity; matching the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time.

Abstract: Detecting propensity profile for a person may comprise receiving artifacts associated with the person; detecting profile characteristics for the person based on the artifacts; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time, each of the plurality of predefined profiles specifying an indication of propensity; matching the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time.

Abstract: One embodiment of the present method and apparatus for robust input interpretation by conversation systems includes receiving a user request containing at least one un-interpretable term. The present invention conveys the conversation system's interpretation capabilities to the user, for example by suggesting at least one alternative request in context of the un-interpretable user request, where the alternative request is phrased in a manner that is substantially fully interpretable. A user may then select a suggested alternative request or formulate a new request in accordance with knowledge of the conversation system capabilities learned from the conveyed information. In another embodiment, a method may independently (e.g., without user prompting) adapt the un-interpretable user request in accordance with learned information regarding the meaning of any un-interpretable terms in the user request.

Abstract: Methods and apparatus are provided for integrating a visual query interface and a natural language interface. The disclosed interface embeds a first of the visual query interface and the natural language interface into a second of the visual query interface and the natural language interface. The disclosed interface can also receives one or more natural language expressions in the natural language interface and one or more visual query expressions in the visual query interface in a same search turn. The disclosed interface can also receive a first query comprised of a first of a natural language query and a visual query; process the first query; and creates a substantially equivalent query to the first query in a second of the natural language query and the visual query The disclosed interface can process a natural language query to determine if a portion of the natural language query is not understood; and convert at least a portion of the natural language query to a visual query.