Collaborative filtering recommendation system and method for assisting in preference acquisition by utilizing electroencephalogram signal

A collaborative filtering recommendation and EEG signal technology, which is applied in the biometric pattern based on physiological signals, data processing applications, instruments, etc., can solve the problem of similarity relationship between items that do not take into account the changes in user browsing emotions, and achieve recommendation The results are objective, the recommendation delay is reduced, and the effect of ensuring real-time performance

Active Publication Date: 2018-08-24
NORTHWEST UNIV
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Problems solved by technology

[0006] The existing collaborative filtering system only uses the known preference data of the current user or other users for some items to predict the potential preference of the current user for other items, and do

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  • Collaborative filtering recommendation system and method for assisting in preference acquisition by utilizing electroencephalogram signal
  • Collaborative filtering recommendation system and method for assisting in preference acquisition by utilizing electroencephalogram signal
  • Collaborative filtering recommendation system and method for assisting in preference acquisition by utilizing electroencephalogram signal

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Embodiment Construction

[0046] The technical solution of the present invention will be described in detail below in conjunction with the embodiments and the accompanying drawings, but is not limited thereto.

[0047] A collaborative filtering recommendation method using EEG signals to assist preference acquisition, as shown in the attached figure 1 As shown, it consists of a user terminal, an EEG signal acquisition module, a data processing module, a data synchronization and control module, a recommendation module and a storage module.

[0048] Among them, the user terminal will receive the recommendation results and collect user browsing records. At the same time, the EEG data acquisition device will collect the EEG signals when the user browses the products, and then amplify, filter, and denoise the EEG signal data, and then transmit the data to the data processing The module extracts the features of the EEG data through the fast Fourier transform, and selects the features in the co-space mode. The...

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Abstract

The invention discloses a collaborative filtering recommendation system and method for assisting in preference acquisition by utilizing an electroencephalogram signal. Through electroencephalogram signal data, a user emotion tendency is calculated and an implicit feedback acts on preference scoring of commodities browsed by a user; and in a recommendation process, a classification result of the electroencephalogram signal data is brought into a calculation category, so that the recommendation accuracy of the recommendation system is improved. By adopting the recommendation method for deeply mining user preferences, the user can quickly find required data from overloaded information data. On the other hand, along with miniaturization and productization of electroencephalogram equipment, therecommendation method provided by the invention provides a new direction for next development of the recommendation system in combination with professional knowledge of the field of brain-computer interfaces.

Description

technical field [0001] The invention belongs to the technical field of information recommendation and pattern recognition, and in particular relates to a collaborative filtering recommendation system and method for assisting preference acquisition by using electroencephalogram signals. Background technique [0002] Emotions often involve people's immediate needs and subjective attitudes, often have complex interrelationships with other psychological processes, and are a comprehensive state of thinking, feeling, and behavior. Since ancient times, China has said the seven emotions of "joy, anger, sorrow, joy, sorrow, and fear". Lange et al. proposed an emotion classification model based on two-dimensional space based on pleasure and arousal, so that people's different emotional experiences can be mapped to a two-dimensional emotional space through these two dimensions. [0003] The brain is the most complex part of human organs, it contains a wealth of physiological and psych...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06Q30/06
CPCG06Q30/0631G06V40/10G06V40/15G06F18/2134G06F18/2135
Inventor 高岭何丹曹瑞王伟杨康
Owner NORTHWEST UNIV
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