Abstract: Embodiments of the present disclosure relate to a method, a device and a computer-readable storage medium for data processing. The method for data processing comprises: obtaining a set of observation samples regarding a plurality of factors, one of the set of observation samples comprising respective observed values of the plurality of factors. The method further comprises: estimating, for each of the plurality of factors and based on the set of observation samples, a distribution that differences between observed values of the factor and estimated values of the factor follow. The method further comprises determining, based at least on the estimated distribution, a causal structure representing a causal relationship among the plurality of factors. Embodiments of the present disclosure further provide a device and a computer-readable storage medium for implementing the above method.

Abstract: Embodiments of the present disclosure relate to a method, device, and computer-readable storage medium for data processing. A method for data processing comprises obtaining a set of observed samples related to multiple factors, an observed sample in the set of observed samples comprising respective observed values of multiple factors. The method further comprises determining a set of dependency relationships between the multiple factors based on the set of observed samples, a dependency relationship in the set of dependency relationships indicating an interrelated factor pair among the multiple factors. The method further comprises determining a causality sequence of the multiple factors based on the set of dependency relationships, the causality sequence indicating that one factor is a cause of the other factor in the interrelated factor pair. Embodiments of the present disclosure further provide a device and computer-readable storage medium capable of performing the foregoing method.

Abstract: Embodiments of the present disclosure relate to a method, apparatus and computer-readable storage medium for data processing. The method may comprise: obtaining feature data for characterizing a plurality of factors of a user set, the plurality of factors comprising a target factor. The method may further comprise obtaining a condition factor from the plurality of factors based on the feature data, the obtained condition factor being a cause of the target factor. The method may further comprise determining a user having the condition factor from the user set. According to the technical solution of the present disclosure, accurate user positioning and strategy formulation may be realized based on the discovery of a high-dimensional causal structure. In addition, according to the technical solution of the present disclosure, information such as the user's satisfaction degree can be simulated without performing cumbersome and inefficient questionnaire surveys.

Abstract: Embodiments of the present disclosure provide a method of information processing, electronic device, and computer program product. The method comprises: obtaining a popularity level of a product and values of a plurality of attributes associated with the product; determining a plurality of influence factors of the plurality of attributes on the popularity level of the product by applying the popularity level and the values of the plurality of attributes to a data processing model; and determining, based on the plurality of influence factors, to adjust at least one attribute of the plurality of attributes to increase the popularity level of the product. Under the guidance of the embodiments of the present disclosure, a supplier of a product can effectively increase a popularity level of a product.

Abstract: Embodiments of the present disclosure relate to a method, a device and a computer-readable storage medium for data processing. The method for data processing comprises: obtaining a set of observation samples regarding a plurality of factors, one of the set of observation samples comprising respective observed values of the plurality of factors. The method further comprises: estimating, for each of the plurality of factors and based on the set of observation samples, a distribution that differences between observed values of the factor and estimated values of the factor follow. The method further comprises determining, based at least on the estimated distribution, a causal structure representing a causal relationship among the plurality of factors. Embodiments of the present disclosure further provide a device and a computer-readable storage medium for implementing the above method.