Systems and methods are disclosed for utilizing sender-recipient pair data to establish sender-level trust in future communication. One method comprises receiving raw communication data over a network and testing the received raw communication data against trained machine learning data to predict whether the raw communication data is associated with expected communication data. The raw communication data is sorted for expected communication data, which is further analyzed for sender-recipient pair data and assigned an expected communication pair data score. Senders associated with an expected communication pair data score that meets or exceeds a threshold are labeled and stored in a database as trusted. As a result of the sender-recipient pair analysis, recipients at-risk for being scammed can be identified, senders misidentified as spammers can be properly classified, and machine learning techniques utilized for analyzing raw communication data can be fine-tuned.

A data sorting method, apparatus and device, a storage medium, and a program product. The method includes: obtaining a data sorting and updating request, where the data sorting and updating request includes data to be updated and an update type; determining a current cursor node, according to the data sorting and updating request, from a circular doubly linked list corresponding to a binary heap storing original data and according to pointing of the current cursor node pointer; determining a node to be updated corresponding to the data to be updated in the binary heap according to the update type and the current cursor node; and performing updating and sorting operations on the original data according to the node to be updated and the data to be updated.

A data sorting method, apparatus and device, a storage medium, and a program product. The method includes: obtaining a data sorting and updating request, where the data sorting and updating request includes data to be updated and an update type; determining a current cursor node, according to the data sorting and updating request, from a circular doubly linked list corresponding to a binary heap storing original data and according to pointing of the current cursor node pointer; determining a node to be updated corresponding to the data to be updated in the binary heap according to the update type and the current cursor node; and performing updating and sorting operations on the original data according to the node to be updated and the data to be updated.

A method of identifying causal relationships between time series may include accessing a hierarchy of nodes in a data structure, where each node in the plurality of nodes may include a time series of data. The method may also include identifying a subset of nodes in the plurality of nodes for which causal relationships may exist in the corresponding time series. The method may additionally include generating a model for each of the subset of nodes, where the model may receive the subset of nodes and generate coefficients indicating how strongly each of the subset of nodes causally affects other nodes in the subset of nodes. The method may further include generating a ranked output of nodes that causally affect a first node in the subset of nodes based on an output of the corresponding model.

A system and method for knob refinement. A method includes determining an ordered list of knobs organized with respect to impact on the target metric for a system based on a plurality of historical sets of target metric measurements; determining a second system configuration based on the ordered list of knobs and a first set of target metric measurements recorded for the system when the system is configured according to a first system configuration, the system having a plurality of knobs, wherein the second system configuration includes at least one knob of the plurality of knobs that is reconfigured as compared to the first system configuration; and applying one of the first system configuration and the second system configuration, wherein the applied system configuration is determined based on the first set of target metric measurements and a second set of target metric measurements.

A computer implemented method is used for sorting data elements of a given set. The method includes performing an evaluation of a first type of usage of each data element. The method includes determining a set of data element candidates dependent on the evaluation of the first type of usage. The method includes performing an evaluation of a second type of usage of each data element of the set of data element candidates. The method includes sorting the data elements of the set of data element candidates dependent on the evaluation of the second type of usage of each data element of the set of data element candidates. The method includes providing the sorted data elements of the set of data element candidates, and in response, receiving a request for a data processing based on the provided sorted data elements of the set of data element candidates.

Disclosed are a partitioning method, an encoder, a decoder and a computer storage medium. The method includes: determining location information of a point of a point cloud to be partitioned; when i is less than or equal to M−1, determining right-shift number N.sub.i of ith LOD layer in the point cloud, M representing a preset maximum quantity of layers for LOD partitioning; for the ith LOD layer, shifting location information of the point rightwards by N.sub.i-digit, performing storing in a preset storage area based on right-shifted location information; determining location information of a parent point corresponding to a current point in the ith LOD layer; according to determined location information of the parent point, searching the preset storage area for a neighbor point of the parent point; partitioning the current point into an (i+1)th LOD layer, or the neighbor point into the ith LOD layer.

Disclosed are a partitioning method, an encoder, a decoder and a computer storage medium. The method includes: determining location information of a point of a point cloud to be partitioned; when i is less than or equal to M−1, determining right-shift number N.sub.i of ith LOD layer in the point cloud, M representing a preset maximum quantity of layers for LOD partitioning; for the ith LOD layer, shifting location information of the point rightwards by N.sub.i-digit, performing storing in a preset storage area based on right-shifted location information; determining location information of a parent point corresponding to a current point in the ith LOD layer; according to determined location information of the parent point, searching the preset storage area for a neighbor point of the parent point; partitioning the current point into an (i+1)th LOD layer, or the neighbor point into the ith LOD layer.

Disclosed are an information output method and apparatus. One specific implementation of the method comprises: acquiring order data to be sorted; determining whether items to be sorted matching the order data to be sorted are stored in a shelf set; in response to having determined that items to be sorted matching the order data to be sorted are stored in the shelf set, determining, from the shelf set, a shelf storing an item to be sorted, and adding same to a candidate shelf set; choosing a candidate shelf from the candidate shelf set and adding same to a target shelf set, where the target shelf set stores the items to be sorted matching the order data; and outputting an identifier of a target shelf in the target shelf set.

Disclosed are an information output method and apparatus. One specific implementation of the method comprises: acquiring order data to be sorted; determining whether items to be sorted matching the order data to be sorted are stored in a shelf set; in response to having determined that items to be sorted matching the order data to be sorted are stored in the shelf set, determining, from the shelf set, a shelf storing an item to be sorted, and adding same to a candidate shelf set; choosing a candidate shelf from the candidate shelf set and adding same to a target shelf set, where the target shelf set stores the items to be sorted matching the order data; and outputting an identifier of a target shelf in the target shelf set.