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2 results about "Time perception" patented technology

Time perception is a field of study within psychology, cognitive linguistics and neuroscience that refers to the subjective experience, or sense, of time, which is measured by someone's own perception of the duration of the indefinite and unfolding of events. The perceived time interval between two successive events is referred to as perceived duration. Though directly experiencing or understanding another person's perception of time is not possible, such a perception can be objectively studied and inferred through a number of scientific experiments. Time perception is a construction of the sapient brain, but one that is manipulable and distortable under certain circumstances. These temporal illusions help to expose the underlying neural mechanisms of time perception.

Online education group question and answer matching method based on user style and time perception

ActiveCN118170876BData setProcessing
This invention discloses an online education group question-and-answer matching method based on user style and time awareness, relating to the field of question-and-answer matching using deep learning natural language processing technology. The method involves constructing a BigData dataset; dividing the BigData dataset into training, validation, and test sets; building user style-aware and time-aware question-and-answer matching models; training the models using the training set and obtaining performance metrics using the validation set to find the optimal hyperparameters; and inputting the test set into the final user style-aware and time-aware question-and-answer matching model to obtain the matching results. This invention enhances question extraction by recognizing user style through user style awareness, reducing the impact of noise caused by severe imbalances between the number of questions and other types of dialogue. It also reduces the noise caused by a large number of potential answers to a single question through time awareness. Compared with other traditional question-and-answer matching models, this method improves the model's question-and-answer matching performance and reduces the impact of data noise.
Owner:NORTHEASTERN UNIV CHINA