5 results about "MultiDimensional eXpressions" patented technology

Described herein are systems and methods for use with a multidimensional database environment, for providing bottom-up multidimensional data analysis in complex formula types. Complex formulas expressions with conditional branches executed over very sparse regions can result in large computational overheads when the iteration is performed in a top-down mode without a knowledge of the target multidimensional cells that have real base data for evaluation. In accordance with an embodiment, the system employs a bottom-up approach that allows identification of those target cells having real data, and executes only those intersections for complex multidimensional expression evaluation. The bottom-up query path functionality can be activated in autonomous mode. The described approach minimizes the amount of redundant executions that have no base data, in some instances to zero level.

Described herein are systems and methods for use with a multidimensional database environment, for providing bottom-up multidimensional data analysis in complex formula types. Complex formulas expressions with conditional branches executed over very sparse regions can result in large computational overheads when the iteration is performed in a top-down mode without a knowledge of the target multidimensional cells that have real base data for evaluation. In accordance with an embodiment, the system employs a bottom-up approach that allows identification of those target cells having real data, and executes only those intersections for complex multidimensional expression evaluation. The bottom-up query path functionality can be activated in autonomous mode. The described approach minimizes the amount of redundant executions that have no base data, in some instances to zero level.

The present invention discloses a natural language query method and system for a multidimensional database. The method comprises the following steps: collecting a user's natural language question and extracting data required for a multidimensional expression; constructing a prompt word template; using a retrieval enhancement technology to perform similarity calculation on vectors of external knowledge documents required for the multidimensional expression to obtain the external knowledge documents corresponding to the vectors; constructing a multidimensional database with a tree structure according to dimensions and metrics, and then performing dimension filtering on the multidimensional database to obtain a filtered dimensional tree structure string; using a retrieval enhancement technology to calculate the similarity between vector data in the vector database and the user's natural language question to obtain a question-multidimensional expression sample corresponding to the vector; inputting the above content as prompt words into a large model to generate a multidimensional expression; performing syntax and hallucination checking on the multidimensional expression to obtain an executable multidimensional expression; and performing reverse parsing to obtain the rows, columns, pages, and conditions queried in the multidimensional expression to complete the natural language query.

The application discloses a kind of based on multi-modal fusion sentiment analysis method and system, comprising the following steps: S1, obtain multi-modal data and the initial feature representation of each mode;S2, the initial feature representation of each mode is input into multi-head attention mechanism and is preliminarily fused, generates primary fusion feature;S3, generate timing feature in conjunction with bidirectional long short-term memory network and multi-scale causal convolution network;S4, utilize multi-layer graph neural network to construct hierarchical dependency relationship network between modes, form global context perception feature representation;S5, dynamically generate and adjust the fusion weight of each mode;S6, utilize multi-layer fully connected network and multi-task learning framework joint classification and regression output, generate the multidimensional expression of emotional state;S7, by migration learning and individualized modeling technique, group sentiment model is migrated to specific sentiment analysis of individual user.The application utilizes multi-modal fusion and adaptive weight adjustment, realizes high-precision, multidimensional sentiment analysis.

This invention discloses a semi-automatic annotation method and system for student facial expression data based on multimodal fusion, comprising: S1 generating multidimensional expressions based on a semantic conditional diffusion model, and simultaneously outputting discrete expression classifications and continuous VAD emotion dimension labels through text prompts in an educational setting; S2 obtaining synthetic expression images and their corresponding 68 facial key point coordinates based on S1, performing classroom scene-adaptive style transfer, and using a key point-constrained adversarial generative network to preserve expression features and adapt to classroom lighting and viewing angle; S3 identifying the classification probability of discrete expression categories and the three-dimensional predicted value of the continuous VAD emotion dimension, using hybrid uncertainty-driven active learning, and combining classification entropy and regression variance to select high-value samples; S4 performing identity decoupling and privacy anonymization on the selected high-value samples, reconstructing the face through a 3D deformation model and specifically blurring the eyebrow region to achieve anonymity protection. This invention can ensure privacy compliance, reduce annotation costs, and improve model accuracy and robustness.