Abstract: In example, a natural language input is processed to generate a formal query that is executed to retrieve data from a data store. An indication as to which subparts of the natural language input were used to generate the formal query may be presented to a user. The user may debug the query, such that associations between natural language input subparts and formal query subparts may be changed, added, or removed by the user. Further, a set of steps may be generated that provide an indication to the user as to how the formal query is executed, for example using sample data from the data store. The user may manipulate the sample data, thereby causing the presented steps to be updated accordingly. Once the user has made adjustments and has finished debugging the query, the revised formal query may be executed to retrieve updated data from the data store.

Abstract: In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogeneous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units.

Abstract: A document re-finding system generates embeddings for concept clips provided by a user, the concept clips defining a concept for searching for content of interest to the user in a plurality of documents previously seen by the user. The re-finding system determines semantic relationships between the concept and document clips, related to respective document among the plurality of documents, based on the concept embedding and embeddings generated for the document clips. A graphical user interface depicting the semantic relationships is rendered to the user and is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.

Abstract: Classification predictions made by a concept classifier may be interactively visualized and explored in a user interface that displays visual representations of a plurality of data items in a star coordinate space spanned by a plurality of anchor concepts each mapping the data items onto respective finite real-valued scores. Positions of the visual representations of the data items in the star coordinate space are based on the scores for the plurality of anchor concepts, and may be updated responsive to a user manipulating the anchor concepts in the user interface, e.g., by moving or modifying definitions of anchor concepts, or by adding or deleting anchor concepts. The visual representations of the data items may reflect labels and/or classification predictions, and may be updated based on updated classification predictions following retraining the of the concept classifier based on added training data or new features.

Abstract: Classification predictions made by a concept classifier may be interactively visualized and explored in a user interface that displays visual representations of a plurality of data items in a star coordinate space spanned by a plurality of anchor concepts each mapping the data items onto respective finite real-valued scores. Positions of the visual representations of the data items in the star coordinate space are based on the scores for the plurality of anchor concepts, and may be updated responsive to a user manipulating the anchor concepts in the user interface, e.g., by moving or modifying definitions of anchor concepts, or by adding or deleting anchor concepts. The visual representations may of the data items may reflect labels and/or classification predictions, and may be updated based on updated classification predictions following retraining the of the concept classifier based on added training data or new features.

Abstract: Classification predictions made by a concept classifier may be interactively visualized and explored in a user interface that displays visual representations of a plurality of data items in a star coordinate space spanned by a plurality of anchor concepts each mapping the data items onto respective finite real-valued scores. Positions of the visual representations of the data items in the star coordinate space are based on the scores for the plurality of anchor concepts, and may be updated responsive to a user manipulating the anchor concepts in the user interface, e.g., by moving or modifying definitions of anchor concepts, or by adding or deleting anchor concepts. The visual representations may of the data items may reflect labels and/or classification predictions, and may be updated based on updated classification predictions following retraining the of the concept classifier based on added training data or new features.

Abstract: Classification predictions made by a concept classifier may be interactively visualized and explored in a user interface that displays visual representations of a plurality of data items in a star coordinate space spanned by a plurality of anchor concepts each mapping the data items onto respective finite real-valued scores. Positions of the visual representations of the data items in the star coordinate space are based on the scores for the plurality of anchor concepts, and may be updated responsive to a user manipulating the anchor concepts in the user interface, e.g., by moving or modifying definitions of anchor concepts, or by adding or deleting anchor concepts. The visual representations may of the data items may reflect labels and/or classification predictions, and may be updated based on updated classification predictions following retraining the of the concept classifier based on added training data or new features.

Abstract: Various embodiments enable, in a mapping context, various visual entities to be clustered into groups that do not occlude one another. In at least some embodiments, individual clusters are represented on a map by a puddle defined by a computed contour line. Users can interact with the puddle to acquire more information about the puddle's content. In at least some embodiments, user interaction can include zooming operations, clicking operations, hovering operations and the like.

Abstract: Information may be presented to a user in a way that reflects an awareness of the user's current situation. The relationship between user's situation, and various people and things, may be analyzed to determine the user's proximity to those people and things. (Proximity may refer not only to geographic proximity, but also temporal proximity, relevance proximity, etc.) A user interface may show people and things at different levels of proximity to the user's current situation, with the level of proximity being represented visually. The user may reposition the center of focus to one of the people or things depicted. When the center is repositioned, the level of proximity of people and things may be shown relative to the new center of focus, filtered based on existing relationships of those people and things to the user.

Abstract: Search results may be rendered on a map utilizing one or more points of interest. An individual point of interest may include a casing layer and a core layer. Casing layers and/or core layers may be configured to change in size and color at different levels of detail associated with zoom operations. Zoom operations may further include de-clustering overlapping points of interest to eliminate overlap. A hover input associated with a cluster may render a numerical value associated with a corresponding number of points of interest that appear in the cluster. Various embodiments provide a visual language that enables a continuous representation, at different levels of detail, that range from a single discrete point to multiple points that are near each other or clustered together to unify the look-and-feel of represented elements and provide interactive consistency across various map properties and platforms.

Abstract: Methods are provided for displaying image results responsive to a search query. In addition to displaying responsive results for a query, responsive results are also provided for related queries. The results are ordered along a plurality of display axes, including at least one axis corresponding to the ordering of the various search queries. The results can be displayed in an aligned or non-aligned manner. The results can then be translated along one or more of the display axes to allow a user to browse the various results.

Abstract: Methods are provided for displaying image results responsive to a search query. In addition to displaying responsive results for a query, responsive results are also provided for related queries. The results are ordered along a plurality of display axes, including at least one axis corresponding to the ordering of the various search queries. The results can be displayed in an aligned or non-aligned manner. The results can then be translated along one or more of the display axes to allow a user to browse the various results.

Abstract: Methods are provided for displaying image results responsive to a search query. In addition to displaying responsive results for a query, responsive results are also provided for related queries. The results are ordered along a plurality of display axes, including at least one axis corresponding to the ordering of the various search queries. The results can be displayed in an aligned or non-aligned manner. The results can then be translated along one or more of the display axes to allow a user to browse the various results.

Abstract: A system for displaying hybrid image data produced by embedding additional media objects within street-level panoramic images includes a user interface through which a user may view, search for, and/or navigate through additional media objects in the context of browsing a virtual environment of a location at street level. In response to user input indicating a request to view a geographic location and/or an additional media object, street-level panoramic image data associated with the geographic location, in which one or more additional media objects also associated with the geographic location have been embedded, may be provided for display through the user interface. The user interface may be provided by a client device including one or more processors that receive hybrid image data produced by one or more processors of a server and display the image data to the user.

Abstract: Information may be presented to a user in a way that reflects an awareness of the user's current situation. The relationship between user's situation, and various people and things, may be analyzed to determine the user's proximity to those people and things. (Proximity may refer not only to geographic proximity, but also temporal proximity, relevance proximity, etc.) A user interface may show people and things at different levels of proximity to the user's current situation, with the level of proximity being represented visually. The user may reposition the center of focus to one of the people or things depicted. When the center is repositioned, the level of proximity of people and things may be shown relative to the new center of focus, filtered based on existing relationships of those people and things to the user.

Abstract: Various embodiments provide a visual language that enables a continuous representation, at different levels of detail, that range from a single discrete point to multiple points that are near each other or clustered together to unify the look-and-feel of represented elements and provide interactive consistency across various map properties and platforms.

Abstract: A system for displaying hybrid image data produced by embedding additional media objects within street-level panoramic images includes a user interface through which a user may view, search for, and/or navigate through additional media objects in the context of browsing a virtual environment of a location at street level. In response to user input indicating a request to view a geographic location and/or an additional media object, street-level panoramic image data associated with the geographic location, in which one or more additional media objects also associated with the geographic location have been embedded, may be provided for display through the user interface. The user interface may be provided by a client device including one or more processors that receive hybrid image data produced by one or more processors of a server and display the image data to the user.

Abstract: A system for displaying hybrid image data produced by embedding additional media objects within street-level panoramic images includes a user interface through which a user may view, search for, and/or navigate through additional media objects in the context of browsing a virtual environment of a location at street level. In response to user input indicating a request to view a geographic location and/or an additional media object, street-level panoramic image data associated with the geographic location, in which one or more additional media objects also associated with the geographic location have been embedded, may be provided for display through the user interface. The user interface may be provided by a client device including one or more processors that receive hybrid image data produced by one or more processors of a server and display the image data to the user.

Abstract: Assisted clustering systems and methods are described herein that provide a user interface by which a user can easily create clusters and selectively associate data items with such clusters. Information regarding data item-cluster associations made by the user is processed by a recommendation engine to learn a clustering model. The clustering model is then be used to generate recommendations for the user regarding which unassociated data items should be associated with which clusters. In certain embodiments, after the user has determined that the clustering model is performing at a satisfactory level based on the quality of the recommendations, the user can cause the system to automatically cluster a large quantity of remaining unassociated data items. In accordance with further embodiments, a user can specify arbitrary data item types for clustering as well as features of such data types that should be considered in generating the clustering model.

Abstract: Methods are provided for displaying image results responsive to a search query. In addition to displaying responsive results for a query, responsive results are also provided for related queries. The results are ordered along a plurality of display axes, including at least one axis corresponding to the ordering of the various search queries. The results can be displayed in an aligned or non-aligned manner. The results can then be translated along one or more of the display axes to allow a user to browse the various results.