There is provided a method and apparatus for generating a competition commentary based on artificial intelligence, and a storage medium. The method comprises: obtaining commentator's words commentaries and structured data of historical competitions; generating a commentating model according to obtained information; during live broadcast of a competition, determining a corresponding words commentary according to the commentating model with respect to the structured data obtained each time.

In one embodiment, a method includes using a first computing device to access digital data representing a contract set of contract documents and digital contract metadata, weight differences between data field values, use the weighted differences to calculate distance scores, use the distance scores and a temporal ordering of the contract documents to generate and cause displaying a time curve graph comprising a geometric shape that comprises time curves and a spatial proximity at a second computing device, a measure of each time curve calculated to indicate an amount of time between a creation of two contract documents, the spatial proximity calculated to indicate a metric of similarity between the contract documents, in response to determining that the geometric shape indicates a lack of convergence over a threshold amount of time, generate and cause displaying a notification indicating that the contract set is at risk at the second computing device.

Time-series data indicating a temporal variation of an index, which indicates a usage state of each of resources that are used by multiple processes, is acquired, and an operation-data matrix including vectors is generated based on the time-series data such that each of the vectors indicates the time-series data at a predetermined time interval and includes as an element the index indicating the usage state of one of the resources at the predetermined time interval. A basis matrix including a predetermined number of basis vectors is generated by performing nonnegative matrix factorization on the operation-data matrix. Component values, which respectively correspond to the resources, indicated by each of the predetermined number of the basis vectors are extracted, and information on the extracted component values is output as usage states of the resources that are used by each of the multiple processes.

Methods and devices for searching for a missing person. Data sources are accessed through an IP network to obtain information about the missing person. Based on the obtained information, potential scenarios are develop of the current location of the missing person. The information is disseminated to search entities that search the geographic areas of the potential scenarios. Additional information is obtained about the missing person during the search to further develop the potential scenarios and focus the search areas.

Operating a low-latency database analysis system using domain-specific chronometry may include obtaining chronometry configuration data including chronometric instance data describing an instance of a chronometric unit of a domain-specific chronometry dataset that describes an era, such that the chronometry configuration data includes respective chronometric instance data describing each instance of the first chronometric unit of the domain-specific chronometry dataset for the era of the domain-specific chronometry dataset, generating, in the low-latency database analysis system, a domain-specific chronometry dataset in accordance with the chronometry configuration data, such that the domain-specific chronometry dataset describes a chronometric unit such that a temporal location expressed with reference to the chronometric unit and indicative of an epoch value differs from a temporal location indicative of the epoch value and expressed in accordance with a canonical chronometry, and storing the domain-specific chronometry dataset in the low-latency database analysis system.

A method is provided to produce a custom calendar user interface (UI) display on an electronic device display screen comprising: providing a search query to a user device; sending the search query over the network to a server system; receiving over the network by one or more user devices from a server system, information that identifies one or more code objects that match the search query; using the identified one or more identified code objects by the one or more user devices to generate one or more visual content items within a calendar user interface (UI) grid display on their device display screens.

Systems and methods for expanding a multi-relational data structure tunable for generating a non-linear dataset from a time-dependent query. The systems include a processor and a memory. The memory may store processor-executable instructions that, when executed, configure the processor to: receive the query of the multi-relational data structure, wherein the query includes at least one entity node at a queried time relative to the time data; obtain, based on the query, a temporal representation vector based on a diachronic embedding of the multi-relational data structure, the diachronic embedding based on a combination of a first sub-function associated with a temporal feature and a second sub-function associated with a persistent feature; determine, from the temporal representation vector, at least one time-varied score corresponding to the queried time; and generate a response dataset based on the at least one time-varied score determined from the temporal representation vector.

A processor-implemented method is disclosed. The method includes: obtaining, from an activity logging system, activity data associated with one or more defined computing tasks, the activity data indicating progress towards completion of the one or more defined computing tasks, the defined computing tasks being associated with one or more projects; obtaining, from a resource usage monitoring system, time-based resource tracking data associated with at least one of the projects, the resource tracking data including project identifying data associated with the at least one project and project time data identifying one or more time periods reflecting use of a computing resource in association with the at least one project; determining mappings of the one or more time periods to the one or more defined computing tasks based on the project identifying data and the activity data associated with the one or more defined computing tasks; determining, based on the mappings, that at least one task-based resource usage criterion is satisfied; and in response to determining that the at least one task-based resource usage criterion is satisfied, generating a notification of resource usage for display on a computing device.

A method for time series forecasting includes receiving a time series forecasting query from a user requesting the data processing hardware to perform a plurality of time series forecasts. Each time series forecast is a forecast of future data based on respective current data Simultaneously, for each time series forecast of the plurality of time series forecasts requested by the time series forecasting query, the method includes training a plurality of models for the respective time series forecast. The method also includes determining which model of the plurality of models best fits the respective time series forecast and forecasting the future data based on the determined best fitting model and the respective current data. The method also includes returning, to the user, the forecasted future data for each of the plurality of time series forecasts request by the timer series forecasting query.

Systems, devices, computer-implemented methods, and tangible non-transitory computer readable media for performing multilayered generation and processing of computer instructions are provided. For example, a computing device may receive a request with instructions in a first computer language, parse the instructions in the first computer language, analyze the instructions in the first computer language in view of information describing structure of a first application, generate instructions in a second computer language different from the first computer language where the instructions in the second computer language are generated based on the instructions in the first computer language and the information describing structure of the first application, obtain a result from a second application where the result comprises information based on the instructions in the second computing language, and provide the result in response to the request comprising the instructions in the first computer language.