Examples of the present application disclose a data processing method and apparatus, and a storage medium. According to the data processing method, stay time length information of a target person for each of a plurality of vehicle models is obtained, wherein the stay time length information is determined based on at least one visit of the target person. An attention vehicle model of the target person is determined based on the stay time length information for each vehicle model. Information of the attention vehicle model of the target person is sent to a terminal. Thus, the terminal displays the information of the attention vehicle model of the target person on a first interface.

The present disclosure relates to systems and methods for recommending locations. The systems may receive data related to a plurality of historical service requests, generate a plurality of feature matrices based on each of a plurality of candidate points of interest (POIs) associated with the plurality of historical service requests, generate a set of sample POIs from the plurality of candidate POIs based on the plurality of feature matrices, train a preliminary POI recommendation model using the set of sample POIs with associated feature matrixes; and determine at least one target POI based on a trained POI recommendation model.

A method for multi-dimensional identification of flexible load demand response effects, including: step 1. determining a target object, a target area and a demand response project that participate in the multi-dimensional identification of flexible load demand response effects; step 2. acquiring flexible load evaluation data of the target area and the target object; step 3. performing data cleaning; step 4. preprocessing the flexible load evaluation data; step 5. constructing four characteristic extraction indicators, a peak load reduction rate, a peak-to-valley difference ratio, a load factor ratio and a response status, inputting a predicted value and an actual collected value of maximum and minimum daily loads before and after the flexible load demand response that are obtained from the prepossessing, to generate a matrix for clustering; step 6. clustering the matrix for clustering generated in step 5; step 7. guiding a more targeted development of demand response projects.

The present disclosure relates to systems and methods for distributing a request. The methods comprise obtaining a user request from a first device; determining a departure location and a departure time based on the user request; determining a target time based on the departure location and departure time; and distributing the user request to a second device based on the target time.

The present disclosure relates to a system, method and non-transitory computer readable medium. The system includes at least one computer-readable storage medium including a set of instructions and at least one processor in communication with the at least one computer-readable storage medium. When executing the set of instructions, the at least one processor is directed to: receive a triggering event in the absence of input from a user terminal associated with a user; obtain one or more candidate destinations based on the triggering event; obtain a trained ranking model; determine a ranking result of the one or more candidate destinations based on the trained ranking model; and transmit the ranking result to the user terminal in response to the triggering event.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a search engine for identifying analogies. One of the methods includes: receiving data that includes a set of user selected features and a user selected feature weight for at least one of the user selected features; generating a reference vector based on the received data; determining a level of similarity between the generated reference vector and each of a plurality of analogy vectors that each represent a potential analogy; providing, for output on a display of a user device, a set of one or more analogies based on the determined level of similarity; receiving a subsequent request to evaluate the set of one or more analogies based on a common attribute; determining, for each of the one or more analogies, a representation of the common attribute for each analogy over a time period; and providing, for display on the user device, a representation of the common attribute for each analogy over the time period.

Systems and methods for objectively conducting an operational due diligence (ODD) assessment of an investment vehicle manager's operations include providing, to each of a population of managers, an electronically-fillable questionnaire including a number of questions regarding risk factors, each risk factor belonging to one of a number of practice aspects, each question requiring selection from a number of standardized answer options. The answers collected from the number of managers may be combined to identify a propensity for exhibiting each of the number of risk factors across portions of the manager population. Each manager may be benchmarked against the propensity of manager population(s) to provide an objective assessment of manager performance and, in combination, portfolio performance in relation to real world common practices. Results of analysis and benchmarking may be provided in an interactive report for review.

Some embodiments provide a program that provides a view of a map that includes a geometry representing a geographical region belonging to a first level in a plurality of levels of a geographical hierarchy. The program further receives a request to focus on a geometry representing a geographical region belonging to a first level in the plurality of levels. The program further provides, in the view of the map, a subset of a set of geometries representing a set of geographical regions belonging to the second level in the plurality of levels of the geographical hierarchy. The program also provide, in the view of the map, a point for each record in the dataset having a spatial point in the location field that falls within the geometry representing the geographical region belonging to the first level in the plurality of levels.

An apparatus for generating merchant clusters based upon monitored consumer transaction activity can include a processor configured to communicate with a consumer transaction database. The processor can be configured to obtain transaction activity of consumers. The processor can be configured to generate a reference cluster based on the obtained transaction activity. The processor can be configured to generate at least one regional merchant cluster for each of a plurality of different geographic regions based on the obtained transaction activity. The processor can be configured to generate a cluster labeling scheme, for each of the different geographic regions, based on comparing each regional merchant cluster for that corresponding geographic region against the reference cluster. The processor can be configured to realign cluster labels for each regional merchant cluster for each of the different geographic regions based on the corresponding cluster labeling scheme generated for the corresponding geographic region.

A computer-implemented method includes receiving an account number identifier associated with a consumer's account. Using the account number identifier, the consumer's recent transaction history in a transaction data warehouse is located. The transaction data warehouse stores records of purchases made by the consumer with the account at one or more merchants. Computational segmentation scoring is applied to identify a group of leading merchant category codes based on the consumer's recent transaction history. The group of leading merchant category codes are correlated with corresponding merchant offers stored in a central offer repository to provide merchant offers that are customized to the consumer's spending behavior. The customized merchant offers are presented to the consumer at a display interface of a device. The customized offers may be presented as an award or mystery offer in an interactive game.