5 results about "Multiple dimension" patented technology

This invention relates to the field of data processing and discloses a method, system, and electronic device for generating multimodal data from multiple dimensions. The method includes: acquiring raw data from at least two dimensions; integrating and synchronizing the raw data from each dimension; annotating the data characteristics of different dimensions using corresponding analysis methods; extracting semantic information and structured features of each dimension to obtain annotation results for each dimension; analyzing each annotation result using a corresponding analysis model to obtain modal analysis results; assigning appropriate weights to each modal analysis result based on the credibility, historical accuracy, and importance of the raw data; fusing the modal analysis results using a weighted fusion method to generate multimodal data; and generating final multimodal data after iteration. This application achieves the technical effects of multimodal data alignment, annotation, fusion, and generation of new data.

Dimension decomposition convolution systems and techniques are described. The system receives a tensor having a first dimension. The system processes the variants of the tensor using a convolution function having a second dimension to generate a processed tensor. The first dimension is greater than the second dimension. A plurality of dimensions from a first dimension of the tensor are grouped into dimensions of variants of the tensor to reduce the dimensions of the variants of the tensor to a second dimension.

The embodiment of the application discloses a data fluctuation attribution analysis method, system and related device, the method comprises the following steps: obtaining the current data of each sub-dimension under each dimension participating in statistics, obtaining historical statistical data different from the target statistical data collection time, calculating the data fluctuation measurement value corresponding to the current data of each sub-dimension under each sub-dimension, and determining the root cause dimension from the multiple dimensions according to the data fluctuation measurement value. Considering that the current data of a certain sub-dimension may be shared by other sub-dimensions under the same dimension, the application can not only quantitatively reflect the data changes of each sub-dimension level, but also feedback the influence of the current data of a certain sub-dimension on the current data of other sub-dimensions under the same dimension, so that the data mutual exclusion or data overlap scene between sub-dimensions can be finally analyzed, thereby accurately inferring which dimension in the upper layer is the root cause dimension causing the data fluctuation, and promoting the process of subsequent application.