Abstract: A continuous query identified by an archived relation of an application may be received. A physical query plan may be generated for the continuous query and/or a child operator plan may be identified. A buffer operator may be inserted between the child operator and its parent operator and/or the event information from the child operator may be stored in the buffer operator. A query operator may be identified in the physical query plan. It may be determined that the query operator identified in the physical query plan is a same type as a second query operator in a second continuous query concurrently executing. Further, a combined query plan may be generated based at least in part on the query operator identified in the physical query plan being the same type as the second query operator in the second continuous query.

Abstract: A system and method for converting an environmental signal surrounding the checkout terminal to a transmission signal is disclosed. The system verifies the accuracy of the transaction at the checkout terminal by analyzing the transmission signal produced by a signal transmission device, which activates upon a detection of a predetermined environmental signal caused around the vicinity of the checkout terminal. The detection of the predetermined environmental signal is performed by a sensor apparatus placed at the checkout terminal which monitors and senses environmental signals during the transaction of an item being purchased at a store.

Abstract: In an approach for visualizing metrics towards optimizing application performance, a processor identifies an application, running in a user interface, on a cloud platform. A processor calculates information metrics of the application. A processor presents the information metrics on the user interface with the application.

Abstract: Systems and methods are provided for organizing communications of multiple communication services. Specifically, techniques are described for organizing data according to detected identities represented aggregate accounts across multiple communication services, as opposed to merely on the basis of accounts on such services. An identity-aware data management system is disclosed that can generate, on the basis of communications of a first party among multiple communication services, a reduced connection graph of the first party. The reduced connection graph of the first party can reflect second parties with whom the first party has communicated, each second party representing an aggregation of multiple accounts of a second party across communication services. The identity-aware data management system may then enable the first party to search, filter, or organize communications according to the reduced connection graph.

Abstract: Systems and methods are provided for organizing communications of multiple communication services. Specifically, techniques are described for organizing data according to detected identities represented aggregate accounts across multiple communication services, as opposed to merely on the basis of accounts on such services. An identity-aware data management system is disclosed that can generate, on the basis of communications of a first party among multiple communication services, a reduced connection graph of the first party. The reduced connection graph of the first party can reflect second parties with whom the first party has communicated, each second party representing an aggregation of multiple accounts of a second party across communication services. The identity-aware data management system may then enable the first party to search, filter, or organize communications according to the reduced connection graph.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: Video frames from a video are compressed into a single image or a single data structure that represents a unique visual flowprint or visual signature for a given activity being modeled from the video frames. The flowprint comprises a computed summary of the original pixel values associated with the video frames within the single image and the flowprint is specific to movements occurring within the video frames that are associated with the given activity. In an embodiment, the flowprint is provided as input to a machine-learning algorithm to allow the algorithm to perform object tracking and monitoring from the flowprint rather than from the video frames of the video, which substantially improves processor load and memory utilization on a device that executes the algorithm, and substantially improved responsiveness of the algorithm.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A service may provide an e-commerce platform through which users may search for, view, and purchase products. To ensure users receive relevant results when querying for particular products or product classes, a list of ranked classes may be generated, from which the query results are based. For example, products may be classified into classes and particular text from search data may be associated with one or more of the products based on click log data. For instance, input text from previously performed queries may be associated with products interacted with following those queries (e.g., products clicked on to view/purchase). Training data that associates the particular text with the respective one or more classes into which the clicked on products are classified may be generated, and in response to receiving a query including the particular text as input, the list of ranked classes may be generated based on the training data.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A service may provide an e-commerce platform through which users may search for, view, and purchase products. To ensure users receive relevant results when querying for particular products or product classes, a list of ranked classes may be generated, from which the query results are based. For example, products may be classified into classes and particular text from search data may be associated with one or more of the products based on click log data. For instance, input text from previously performed queries may be associated with products interacted with following those queries (e.g., products clicked on to view/purchase). Training data that associates the particular text with the respective one or more classes into which the clicked on products are classified may be generated, and in response to receiving a query including the particular text as input, the list of ranked classes may be generated based on the training data.

Abstract: Detection and prevention of loss at a retail checkout are provided. At least one camera captures video streams during a transaction at a point of sale terminal. The video streams are analyzed to detect a scan activity during the transaction. Transaction data is collected from the point of sale terminal. The scan activity is compared with the transaction data in order to detect discrepancies between the detected scan activity and the scan activity recorded in the transaction data.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A computer system monitors a private network for presence of data traffic. In one embodiment, the private network is a retail environment in which a customer purchases an item scanned at a point-of-sale terminal. The data traffic can be point-of-sale transaction information generated in response to purchase of the item at the point-of-sale terminal. Subsequent to detecting presence of the data traffic in the network, the computer system analyzes the data traffic to identify private information in the data traffic. To protect the private information from improper disclosure to unauthorized entities, the computer system modifies the data traffic. Thus, techniques herein can include detecting occurrence of one or more point-of-sale events in a private network, anonymizing the event information (e.g., data traffic), and forwarding the anonymized event information associated with the point-of-sale events out of the private network to a remote resource.

Abstract: A service may provide an e-commerce platform through which users may search for, view, and purchase products. To ensure users receive relevant results when querying for particular products or product classes, a list of ranked classes may be generated, from which the query results are based. For example, products may be classified into classes and particular text from search data may be associated with one or more of the products based on click log data. For instance, input text from previously performed queries may be associated with products interacted with following those queries (e.g., products clicked on to view/purchase). Training data that associates the particular text with the respective one or more classes into which the clicked on products are classified may be generated, and in response to receiving a query including the particular text as input, the list of ranked classes may be generated based on the training data.