Abstract: Systems and methods for rearranging tags on a graphical user interface (GUI) based on known and unknown levels of web traffic are disclosed. To provide users with real estate listings that have popular home attributes with respect to a given region, the system uses known user interaction information to determine predicted user interaction information for real estate listing phrases (e.g., tags) that are associated with unknown user interaction information. The system then ranks the real estate listing phrases based on each real estate listing phrase's user interaction information. Based on the ranked real estate listing phrases, the system generates for display the highest ranked real estate listing phrase in association with a real estate listing being associated with the real estate listing phrase.

Abstract: Systems and methods for providing visual indications of time sensitive real estate listing information on a Graphical User Interface (GUI) are disclosed. To provide users with visual indications of real estate listings that may sell soon with respect to a given region, the system uses days-sold information, real estate listing attributes, and user interaction data corresponding to a set of real estate listings associated with a given region to train a machine learning model to generate a selling soon prediction. The system then provides a days-on-market value, a set of home attributes, and user interaction data associated with a subject real estate listing as input to the machine learning model. The system then generates a selling soon prediction by applying the machine learning model and generates for display, on a GUI displaying information of the subject real estate listing, a visual indication of the selling soon prediction.

Abstract: Systems and methods for reducing personalized real estate collection suggestion delays via batch generation are disclosed. The systems and methods use user interaction information, home attribute information, and one or more machine learning models to generate sets of suggested real estate listings corresponding to personalized real estate collections. The system generates a set of personalized collection identifiers in a batch process with a first set of suggested real estate listings corresponding to respective personalized collection identifiers. The system also generates a second set of suggested real estate listings corresponding to respective personalized collection identifiers of the set of personalized collection identifiers. To reduce delays associated with providing personalized real estate collections, the system selects the first set of suggested real estate listings based on the generation of the second set of suggested real estate listings to satisfy a threshold value.

Abstract: Systems and methods for rearranging tags on a graphical user interface (GUI) based on known and unknown levels of web traffic are disclosed. To provide users with real estate listings that have popular home attributes with respect to a given region, the system uses known user interaction information to determine predicted user interaction information for real estate listing phrases (e.g., tags) that are associated with unknown user interaction information. The system then ranks the real estate listing phrases based on each real estate listing phrase's user interaction information. Based on the ranked real estate listing phrases, the system generates for display the highest ranked real estate listing phrase in association with a real estate listing being associated with the real estate listing phrase.

Abstract: A network-based service is disclosed for disambiguating search queries based on a location-based clustering of search results corresponding to the query. In one embodiment, a user may submit a query for travel items, such as hotel accommodations. The service can determine, based on the query, an initial set of hotels providing such accommodations. The service can then cluster the hotels according to their geographic positions. If the service identifies multiple clusters, the user can be prompted to select a specific cluster to receive additional information regarding the cluster. Illustratively, if a user submits a query for a hotel in “Springfield,” the service may ask the user to select among multiple clusters of results, each corresponding to a different city named “Springfield” in which results have been located.

Abstract: A network-based service is disclosed for disambiguating search queries based on a location-based clustering of search results corresponding to the query. In one embodiment, a user may submit a query for travel items, such as hotel accommodations. The service can determine, based on the query, an initial set of hotels providing such accommodations. The service can then cluster the hotels according to their geographic positions. If the service identifies multiple clusters, the user can be prompted to select a specific cluster to receive additional information regarding the cluster. Illustratively, if a user submits a query for a hotel in “Springfield,” the service may ask the user to select among multiple clusters of results, each corresponding to a different city named “Springfield” in which results have been located.

Abstract: A network-based service is disclosed for disambiguating search queries based on a location-based clustering of search results corresponding to the query. In one embodiment, a user may submit a query for travel items, such as hotel accommodations. The service can determine, based on the query, an initial set of hotels providing such accommodations. The service can then cluster the hotels according to their geographic positions. If the service identifies multiple clusters, the user can be prompted to select a specific cluster to receive additional information regarding the cluster. Illustratively, if a user submits a query for a hotel in “Springfield,” the service may ask the user to select among multiple clusters of results, each corresponding to a different city named “Springfield” in which results have been located.

Abstract: A network-based service is disclosed for disambiguating search queries based on a location-based clustering of search results corresponding to the query. In one embodiment, a user may submit a query for travel items, such as hotel accommodations. The service can determine, based on the query, an initial set of hotels providing such accommodations. The service can then cluster the hotels according to their geographic positions. If the service identifies multiple clusters, the user can be prompted to select a specific cluster to receive additional information regarding the cluster. Illustratively, if a user submits a query for a hotel in “Springfield,” the service may ask the user to select among multiple clusters of results, each corresponding to a different city named “Springfield” in which results have been located.

Abstract: Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.

Abstract: Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.

Abstract: Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.

Abstract: Methods, computer readable media, and apparatuses provide robotic explosive hazard detection. A robot intelligence kernel (RIK) includes a dynamic autonomy structure with two or more autonomy levels between operator intervention and robot initiative A mine sensor and processing module (ESPM) operating separately from the RIK perceives environmental variables indicative of a mine using subsurface perceptors. The ESPM processes mine information to determine a likelihood of a presence of a mine. A robot can autonomously modify behavior responsive to an indication of a detected mine. The behavior is modified between detection of mines, detailed scanning and characterization of the mine, developing mine indication parameters, and resuming detection. Real time messages are passed between the RIK and the ESPM. A combination of ESPM bound messages and RIK bound messages cause the robot platform to switch between modes including a calibration mode, the mine detection mode, and the mine characterization mode.