Abstract: A method includes receiving a plurality of product query arrays each including a plurality of individual product queries received during a single user search session. The method further includes inputting the plurality of product query arrays into the query rewrite model. Text of each of the plurality of individual product queries in each product query array is treated as a whole token. The method further includes receiving a product query from a user electronic device. The method further includes determining a query rewrite for the product query using the query rewrite model and determining search results for the product query using the query rewrite. The method further includes sending information for presenting the search results on a display of the user electronic device responsive to the product query.

Abstract: A system and method for machine learning classification of user sentiment is disclosed. The method includes storing including a plurality of category information. The plurality of category information includes a set of domain-specific category information. The method further includes extracting a plurality of aspects from textual data. The method further includes generating a sentiment by a machine learning model. The method further includes receiving the plurality of aspects and the set of domain-specific category information.

Abstract: A method includes retrieving, by a processor in an image classification system, a plurality of product images from a memory. A first image classifier is applied to a first of the plurality of product images. The first of the plurality of product images is associated with a first category. A second image classifier is applied to a second of the plurality of product images. The second of the plurality of product images is associated with a second category. A first result of the first image classifier for the first of the plurality of product images is stored in the memory. A second result of the second image classifier for the second of the plurality of product images is stored in the memory.

Abstract: A method includes receiving a plurality of product query arrays each including a plurality of individual product queries received during a single user search session. The method further includes inputting the plurality of product query arrays into the query rewrite model. Text of each of the plurality of individual product queries in each product query array is treated as a whole token. The method further includes receiving a product query from a user electronic device. The method further includes determining a query rewrite for the product query using the query rewrite model and determining search results for the product query using the query rewrite. The method further includes sending information for presenting the search results on a display of the user electronic device responsive to the product query.

Abstract: Aspects of the subject disclosure may include, for example, a process by which first data is received from a mobile device regarding first objects detected by the mobile device in an area, the first data having been collected by the mobile device at a number of first collection points while moving along a first path from an initial position in the area to a boundary of the area. The first data is aggregated with second data previously collected regarding second objects in the area, the second data having been collected at a number of second collection points along a second path different from the first path. The second data includes a position indicator for each of the second objects indexed by the initial position. A map of the area is generated based on the aggregating and the map is transmitted to the mobile device. Other embodiments are disclosed.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: Aspects of the subject disclosure may include, for example, a process by which first data is received from a mobile device regarding first objects detected by the mobile device in an area, the first data having been collected by the mobile device at a number of first collection points while moving along a first path from an initial position in the area to a boundary of the area. The first data is aggregated with second data previously collected regarding second objects in the area, the second data having been collected at a number of second collection points along a second path different from the first path. The second data includes a position indicator for each of the second objects indexed by the initial position. A map of the area is generated based on the aggregating and the map is transmitted to the mobile device. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a mobile device determines a current position and direction; detects objects within an area including the current position; collects first data regarding the objects; buffers the first data; and transmits the first data to a remote system responsive to the mobile device reaching a boundary of the area. The method also comprises obtaining a map of the area from the remote device; the map includes information based on second data previously collected regarding objects in the area, the second data includes a position indicator and a direction indicator for each of the second objects indexed by the current position, and the remote device aggregates the first data and the second data to generate an updated map of the area. Navigation instructions are generated based on the current position and the map, Other embodiments are disclosed.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a mobile device determines a current position and direction; detects objects within an area including the current position; collects first data regarding the objects; buffers the first data; and transmits the first data to a remote system responsive to the mobile device reaching a boundary of the area. The method also comprises obtaining a map of the area from the remote device; the map includes information based on second data previously collected regarding objects in the area, the second data includes a position indicator and a direction indicator for each of the second objects indexed by the current position, and the remote device aggregates the first data and the second data to generate an updated map of the area. Navigation instructions are generated based on the current position and the map, Other embodiments are disclosed.

Abstract: More efficient mobile device location data can be obtained by estimating a most likely location point in a coverage pattern using a kernel density estimation technique. The kernel density estimation technique can provide a continuous estimate of the most frequented locations of a mobile device(s) within a coverage area. For each wireless sector, the collected location data can grouped to the closest geographic coordinate system, and an inference can be made based on the grouped data.