A system includes persistent storage containing an archive, a first interface to a messaging system that includes a plurality of channels, a second interface to a machine learning system that includes a query detection model and a reply detection model, and a processor configured to perform operations including receiving, from the message system, messages that appeared in a particular channel of the plurality of channels. The operations also include providing, to the machine learning system, the messages, where reception of the messages causes the query detection model to detect a query within the messages and the reply detection model to detect, within the messages, replies to the query. The operations further include receiving, from the machine learning system, the query and the replies, and storing, in the archive, the query, the replies, and an indication that the replies relate to the query.

During a query compilation process, a query is received that is directed to a set of source tables, each source table from the set of source tables being organized into at least one micro-partition and the query including at least one pruning operation. During the query compilation process, a modification of the query is performed for adjusting the at least one pruning operation, the modification being based on a set of statistics collected for previous pruning operations on at least a portion of the set of source tables and a set of heuristics, the set of statistics indicating at least an amount of execution time for each previous query associated with each of the previous pruning operations. The query is compiled including the modification of the query. The compiled query is provided to an execution node of a database system for execution.

An example operation may include one or more processing transactions of a plurality of blocks of a blockchain of the blockchain network to determine a user of a plurality of users that is a party of the respective transaction and a mining pool of one or more mining pools that included the respective transaction in the blockchain, performing a statistical analysis of the transactions to determine if the transactions of a user of the plurality of users is distributed across the one or more mining pools in a statistically expected manner, determining that the user has a special relationship with one or more of the one or more mining pools if the transactions of the user are not distributed across the mining pools in a statistically expected manner, and for a user that is determined to have a special relationship, determining one or more of the mining pools with which the determined user has a special relationship.

Embodiments are directed to a system, computer program product, and method for dynamic object mining. A received file is segmented, re-formatted, and organized into buffers, while maintaining the order of the received file. Multiple buffers are processed in parallel for object mining. A listener is encoded into the buffers to support asynchronous processing, and more specifically ordering of mined objects. An output file of the mined objected or associated frames is created. The file is populated with a sequential ordering of the objects that follows the order of the received file.

Systems and methods for modeling higher-level metrics from graph data derived from already-collected but not yet connected data are disclosed. A method includes extracting a first set of actor-related data, a second set of object-related data, and a third set of temporal data from the set of the already-collected but not yet connected data representative of a unit-level contribution to the target activity. The method further includes generating graph data for a graph using the set of the already-collected but not yet connected data, where each of the plurality of nodes of the graph corresponds to the actor or the object, and where an attribute associated with each of the plurality of edges of the graph corresponds to a measurement associated with the target activity. The method further includes modeling a relationship between graph attributes associated with the graph data and a higher-level metric associated with the target activity.

The present disclosure discloses a query method, an apparatus, an electronic device, and a storage medium, and relates to the technical field of spatio-temporal big data in big data technologies. The specific implementation scheme is as follows: receiving a query request sent by a terminal device, where the query request is used to request to query dynamic association relationships of a target entity and includes an identifier of the target entity and query starting and ending time; determining at least one time bucket to be queried in a query database according to the query starting and ending time, where each time bucket stores the dynamic association relationships of the target entity in a time period corresponding to the time bucket; and querying the dynamic association relationships of the target entity in the at least one time bucket according to the identifier of the target entity.

A prediction device includes: a normal prediction unit configured to predict first prediction values for target ranges of respective models, based on respective pieces of spatio-temporal observation data including observation values for respective observation locations and respective observation times observed for a given time period and the respective models for predicting variations of the pieces of spatio-temporal observation data for the respective target ranges defined for at least one of an observation location or a period; a residual extraction unit configured to extract, based on residuals between the respective pieces of spatio-temporal observation data being observed and the models corresponding to the respective pieces of spatio-temporal observation data based on the pieces of spatio-temporal observation data and the models, the respective pieces of spatio-temporal observation data with residuals greater than or equal to a threshold value, as spatio-temporal residual data; a residual prediction unit configured to predict, based on the spatio-temporal residual data, second prediction values for the target ranges corresponding to the spatio-temporal residual data in accordance with a predetermined prediction technique; and a synthesis unit configured to output prediction values obtained by synthesizing the first prediction values and the second prediction values.

One or more computing devices, systems, and/or methods are provided. In an example, a dataset associated with a plurality of dimensions and a plurality of metrics is identified. A subset of dimensions of the plurality of dimensions and a subset of metrics of the plurality of metrics are selected based upon historical dataset queries. A plurality of sets of results is generated, using the dataset, based upon the subset of dimensions and the subset of metrics. A plurality of significance scores is determined based upon the plurality of sets of results. One or more first sets of results of the plurality of sets of results are selected based upon the plurality of significance scores.

Method and system for displaying an orthodontic related image including one or more image segments, selecting one or more movement indicators associated with a corresponding one or more of the image segments, and dynamically displaying a modified orthodontic related image based on the selected one or more movement indicators are provided.

The present disclosure relates to methods and systems for ingesting content from data feeds and to generate an enhanced output of relevant content for presentation to a user to facilitate analysis of the relevant content. Content is received from data feeds, and filtered to identify relevant content with respect to a particular context. The relevant content is then processed, e.g., using natural language processes, to extract entities involved, and to also identify particular activities detailed in the relevant content. Activity-mining is applied to the identified relevant data to classify and assigned activity tags to the extracted entity. Based on the extracted and identified information, an enhanced output is generated for presentation to facilitate research operations. The enhanced output may include overlaid graphical annotations, indicators, and graphical controls over the relevant articles to provide a means for updating a database based on the relevant content.