Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: A technique is described herein for controlling equipment in a local environment. The technique can use a conversational interface component to receive messages from any user in a group of users. In a media-related context, a media BOT receives each message and determines whether it contains a command to play a particular media item. If so, the media BOT formulates the message as an input query and sends the input query to a search system, with instruction to perform a domain-specific search. The search system identifies a top-ranked media item based on the input query, selected from among a curated media-specific corpus. By virtue of the use of the scoped search system, the technique can successfully leverage preexisting linguistic processing mechanisms. The technique can also generate group profiles associated with users who interact with the conversational interface component, and then use the group profiles to automatically select media items.

Abstract: A technique is described herein for controlling equipment in a local environment. The technique can use a conversational interface component to receive messages from any user in a group of users. In a media-related context, a media BOT receives each message and determines whether it contains a command to play a particular media item. If so, the media BOT formulates the message as an input query and sends the input query to a search system, with instruction to perform a domain-specific search. The search system identifies a top-ranked media item based on the input query, selected from among a curated media-specific corpus. By virtue of the use of the scoped search system, the technique can successfully leverage preexisting linguistic processing mechanisms. The technique can also generate group profiles associated with users who interact with the conversational interface component, and then use the group profiles to automatically select media items.

Abstract: A technique is described herein for controlling equipment in a local environment. The technique can use a conversational interface component to receive messages from any user in a group of users. In a media-related context, a media BOT receives each message and determines whether it contains a command to play a particular media item. If so, the media BOT formulates the message as an input query and sends the input query to a search system, with instruction to perform a domain-specific search. The search system identifies a top-ranked media item based on the input query, selected from among a curated media-specific corpus. By virtue of the use of the scoped search system, the technique can successfully leverage preexisting linguistic processing mechanisms. The technique can also generate group profiles associated with users who interact with the conversational interface component, and then use the group profiles to automatically select media items.

Abstract: A technique is described herein for controlling equipment in a local environment. The technique can use a conversational interface component to receive messages from any user in a group of users. In a media-related context, a media BOT receives each message and determines whether it contains a command to play a particular media item. If so, the media BOT formulates the message as an input query and sends the input query to a search system, with instruction to perform a domain-specific search. The search system identifies a top-ranked media item based on the input query, selected from among a curated media-specific corpus. By virtue of the use of the scoped search system, the technique can successfully leverage preexisting linguistic processing mechanisms. The technique can also generate group profiles associated with users who interact with the conversational interface component, and then use the group profiles to automatically select media items.

Abstract: Computer-implemented functionality is described herein for assisting a user in interacting with an environment. In one implementation, the functionality operates by: determining that a particular user is within a prescribed proximity to an electronic sign, or will be in prescribed proximity to the electronic sign, based on sensor information provided by one or more sensors within the environment; determining an identity of the user; determining at least one destination of the user based at least on calendar information; providing directions to the destination(s), to provide unfiltered direction information; optionally filtering the unfiltered direction information with respect to restriction information (e.g., privacy information, security information, etc.), to produce filtered direction information; composing sign information based on the filtered direction information; and sending the sign information to the electronic sign for presentation by the sign.

Abstract: Hierarchical structures are visualized and navigated using an orbital model. Sibling nodes are orbitally displayed in a generally circular arrangement along an orbital path. Choosing one of the orbitally displayed nodes opens it, moving down in the hierarchy. Nodes which were not chosen are undisplayed, and child node(s) of the chosen node are orbitally displayed. Node movements may be animated. A history displays recently chosen nodes. Choosing a parent node of the orbiting nodes undisplays the child nodes, and the parent node and its siblings are orbitally displayed, thereby moving up in the hierarchy. A user may select nodes from different parts of the hierarchy by moving them into a selection tray. Selected nodes can then be subjected to a specified batch operation. Controls are available for sorting nodes and/or for altering node appearance in the display.

Abstract: Hierarchical structures are visualized and navigated using an orbital model. Sibling nodes are orbitally displayed in a generally circular arrangement along an orbital path. Choosing one of the orbitally displayed nodes opens it, moving down in the hierarchy. Nodes which were not chosen are undisplayed, and child node(s) of the chosen node are orbitally displayed. Node movements may be animated. A history displays recently chosen nodes. Choosing a parent node of the orbiting nodes undisplays the child nodes, and the parent node and its siblings are orbitally displayed, thereby moving up in the hierarchy. A user may select nodes from different parts of the hierarchy by moving them into a selection tray. Selected nodes can then be subjected to a specified batch operation. Controls are available for sorting nodes and/or for altering node appearance in the display.

Abstract: A method and computer-readable medium are provided for constructing a classifier for classifying search queries. The classifier is constructed by receiving a query from a user and applying the query to a classifier to identify the task. An unsupervised mapping between the query and the task is then identified and is used to train a new classifier. Under one embodiment, the unsupervised mapping is identified based on a user's selection of the task.

Abstract: A method and computer-readable medium are provided for constructing a classifier for classifying search queries. The classifier is constructed by receiving a query from a user and applying the query to a classifier to identify the task. An unsupervised mapping between the query and the task is then identified and is used to train a new classifier. Under one embodiment, the unsupervised mapping is identified based on a user's selection of the task.