Methods and systems are presented for retrieving data associated with one or more portions of a graph by a computer system. Multiple graph indices are generated based on the graph. Each of the multiple graph indices stores records of data representing the graph in different formats. Upon receiving a request for accessing a sub-graph of the graph, edge-based attributes of the sub-graph are analyzed. The sub-graph may be divided into a first portion and a second portion of the sub-graph. A first graph index may be selected for retrieving records associated with the first portion of the sub-graph based on the edge-based attributes of the first portion of the sub-graph. A second graph index may be selected for retrieving records associated with the second portion of the sub-graph based on the edge-based attributes of the second portion of the sub-graph.

An application activation method includes enabling an activation of one or more applications, including an activation of a first application, on a computing device. A first plurality of interactions of a user with the one or more applications on the computing device are detected. A first offer to renew the activation of the first application is generated based on the first plurality of interactions of the user. The first offer is provided to the user via the computing device. An acceptance of the first offer is received from the user, and the activation of the first application is renewed responsive to receiving the acceptance of the first offer.

A computing device is coupled to a display device, and includes a data monitoring software application program executing on a processor within a data monitoring system. Via the data monitoring software application program, various techniques are performed for generating user interfaces for data monitoring and event response. In a first technique, the data monitoring software application program displays a user interface that includes a first region including a data visualization and a second region including one or more images of a video stream. In a second technique, the data monitoring software application program generates a user interface associated with an event, receive an input corresponding to interaction with a user interface element in the user interface, and initiates an event channel associated with the event in response to the input.

Generally described, one or more aspects of the present application relate to data search system that can facilitate data searches such that the amount of computing resources such as processing power and bandwidth used to generate and output search results is reduced. For example, in response to a search request specifying a set of search criteria, the data search system may identify a combination of sub-criteria, access a pre-generated threshold corresponding to the combination of sub-criteria, determine a real-time index value corresponding to the combination of sub-criteria, identify a plurality of resources that satisfy the set of search criteria, and output a subset of the plurality of resources to the user computing device from which the search request was received.

A method is provided for determining command-to-process correspondence. The method includes identifying, by the hardware processor, initial processes resulting from executions of container immutability change events for each of multiple containers in a cluster, based on an execution time, a process identifier and a process group identifier for each of the container immutability change events. The method further includes checking, by the hardware processor, if an initial process from among the identified initial processes matches an entry in a database that stores external container commands and at least one respective process resulting from executing each of the external container commands. The method also includes designating, by the hardware processor, a particular external command, from among the external container commands stored in the database, as having a correspondence to the initial process, responsive to the initial process matching the at least one respective process resulting from executing the particular external command.

Embodiments are directed to data ingestion over a network. Raw data and integrated data associated with a plurality of separate data sources may be provided such that the raw data includes content associated with a plurality of subjects. Categorization models may be employed to categorize the raw data based on various features, such as, format, structure, data source, variability, volume, or associated entities. Matching models may be determined based on the categorization of the of the raw data, the integrated data and the content associated with the plurality of subjects. Matching models may generate a plurality of unified facts based on the raw data and the integrated data such that each unified fact is associated with a score associated with a quality of its match with a unified schema.

The application relates to providing medical information in response to a query, in particular, although not exclusively, to a method of querying a medical database using voice recognition. According to an embodiment, there is provided a medical query answering apparatus that is configured to convert detected audio signals into a natural language data stream; determine from the natural language data stream whether a voice command for information relating to a medical device or a medicament has been issued by a user; in response to a positive determination, convert at least part of the natural language data stream into a query for querying a medical database; supply the query to the medical database and receive a response therefrom; and provide an audio output based at least in part on the response from the medical database.

System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.

Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.

A computer divides a character string included in text data into a plurality of tokens. The computer searches, by performing matching processing between a token string indicating a specific number of consecutive tokens among the plurality of tokens and dictionary information including a plurality of named entities, the plurality of named entities for a similar named entity whose similarity to the token string is equal to or more than a threshold. The computer converts matching information indicating a result of the matching processing between the token string and the similar named entity into first vector data. The computer generates input data by using a plurality of pieces of vector data converted from the plurality of tokens and the first vector data. The computer generates a named entity recognition model that detects a named entity by performing machine learning using the input data.