Abstract: Disclosed are a method for determining the dangerousness of a person, an apparatus, a system and a storage medium. The method includes: generating a historical trajectory of a specific person according to historical data of the specific person acquired by a plurality of devices within a designated time period, where the historical data includes a person identifier of the specific person, an acquisition time and a device identifier; determining suspicious behaviors of the specific person appearing in the historical trajectory by means of analyzing behaviors of the specific person according to the historical trajectory of the specific person; determining a suspicious level of the specific person according to a frequency of at least one of the suspicious behaviors appearing in a corresponding historical trajectory; and determining that the specific person is dangerous in a case that the suspicious level exceeds a first set threshold.

Abstract: The present disclosure provides a prediction method of wind power output, an electronic device, a storage medium and a system, and relates to the technical field of wind power. The method includes: periodically acquiring an initial meteorological data set corresponding to each received time node, wherein the initial meteorological data set includes initial meteorological sub-data of at least one dimension of at least one meteorological element; after acquiring the latest initial meteorological data set, identifying and smoothing the abnormal sub-data to obtain a smoothed meteorological data set; determining an average wind energy density in a target time period; taking the smooth meteorological data set and the average wind energy density in the target time period as the input features of the model, and obtaining a wind power output predictive value via the model.

Abstract: The present application disclose a multi-product production planning method and device, computer equipment and storage medium. The method includes: obtaining production information, where the production information includes a maximum demand for each kind of products in a variety of kinds of products, at least two kinds of products have at least one identical production material, and the production materials of at least one kind of products include replaceable production materials marked with priorities; establishing a linear programming model having a goal and constraint conditions according to the production information; and solving the linear programming model to obtain a production planning scheme.

Abstract: A method for recommending information includes: acquiring video information of a presentation area where a display terminal is located; performing face image recognition on the video information; acquiring, in response to determining that a user to which a face image acquired by the recognition belongs is paying attention to the display terminal, preference degrees of the user for a plurality of pieces of to-be-presented information; and sending target to-be-presented information with a target preference degree to the display terminal.

Abstract: The present disclosure discloses a recommendation method, computing device, and storage medium. An implementation of the method includes: acquiring user operation data from a first terminal; invoking at least one recommendation algorithm in response to the user operation data to calculate at least one first recommendation result; displaying user information and an algorithm identifier of the invoked recommendation algorithm on a display apparatus of the computer device or a second terminal; displaying first recommendation result information calculated by a corresponding recommendation algorithm on the display apparatus of the computer device or the second terminal in response to an operation on the algorithm identifier.

Abstract: A method and device for generating a painting display sequence, and a computer storage medium are provided. The method for generating a painting display sequence comprises the following steps: acquiring painting data of a region of interest (ROI); clustering the painting data in a predetermined group and obtaining clustering results; and generating the painting display sequence according to the clustering result.

Abstract: The embodiments of the present disclosure disclose an information recommendation method, device and storage medium. The method includes: determining, in a case where a user behavior is detected, an object to which the user behavior is directed as an object to be processed; determining similar objects of the object to be processed based on object similarity relationships; and recommending the similar objects; wherein the object similarity relationships are established by: acquiring labels of a plurality of sample objects; clustering the labels to obtain a plurality of label categories; for each of the sample objects, calculating similarities between a label of the sample object and the plurality of label categories to obtain a similarity set corresponding to the sample object; and establishing, according to the similarity set corresponding to each sample object, a similarity relationship between the sample object and any other one sample object of the plurality of sample objects.

Abstract: The present disclosure provides a painting label generation method and an electronic device. The method includes: obtaining painting basic information and painting brief introduction information of a target painting; generating painting attribute information by pre-processing the painting basic information; generating a painting theme word by extracting a theme word from the painting brief introduction information; and generating a painting label for the target painting according to the painting attribute information and the painting theme word.

Abstract: An information recommendation method and device and a storage medium. The information recommendation method includes: determining a target recommendation parameter corresponding to a page identifier of a page, according to the page identifier and a correspondence between a page identifier and a recommendation parameter; determining a corresponding target recommendation strategy according to the target recommendation parameter; querying a correspondence between a recommendation strategy and a recommendation result according to the target recommendation strategy, so as to obtain at least one initial recommendation result; and fusing the at least one initial recommendation result according to a corresponding weight to obtain a target recommendation result.