CN105260745A - Information push service system capable of carrying out emotion recognition and prediction based on big data - Google Patents
Information push service system capable of carrying out emotion recognition and prediction based on big data Download PDFInfo
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Abstract
The invention provides an information push service system capable of carrying out emotion recognition and prediction based on big data, which comprises a physiological signal acquisition module, a client, a cloud server and a cloud data center, and is characterized in that the physiological data acquisition module is used for acquiring individual physiological signal original data, a non-physiological information acquisition module of the client is used for acquiring individual non-physiological information data, and the client, the cloud server and the cloud data center are used for receiving and storing data and pushing information. The system provided by the invention combines big data of user emotion, carries out processing and analysis on the individual physiological signal data and the non-physiological information, performs classification and prediction according to individual emotion, and pushes a classification and prediction result to individual client software through the internet, thereby realizing efficient and accurate information push services.
Description
Technical field
The present invention relates to the communication technology, artificial intelligence field, especially relate to a kind of Information Push Service system of carrying out emotion recognition and prediction based on large data.
Background technology
One of product that Information Push Service develops as networked information era, contains much information with it, the high and Information Communication of real-time is convenient etc., and advantage is used by large-scale popularization.In prior art, information pushing is browsed mainly with the non-physiological signal datas such as individual voice, text, emoticon and About You and is recorded as according to predicting, relevant information is pushed according to predicting the outcome to user, this propelling movement mode randomness is large, personal mood, affective state can not be judged according to the analysis of individual physiological signal data, thus an acquisition Man's Demands carries out information pushing accurately, blindness is large, pushes effect undesirable.
Therefore, develop a kind of Information Push Service system of accurately carrying out emotion recognition and prediction based on large data to be necessary.
Summary of the invention
Technical matters to be solved by this invention is, a kind of individual Push Service system of carrying out various dimensions emotion recognition and prediction based on large data is provided, this system is in conjunction with the large data of user feeling, by to individual physiological signal data and individual's non-physiologic information data binding analysis, according to personal mood, emotion state classification and prediction, by classification with predict the outcome and be pushed to individual client by internet and hold in software, to realize efficiently, Information Push Service accurately.
The present invention is solved the problems of the technologies described above by following technical proposals:
Carry out a personal information Push Service system for emotion recognition and prediction based on large data, comprise physiological signal collection module, instruction sending module, non-physiology information detecting module, signal conversion module, signal processing module, data memory module, cloud server and high in the clouds data center:
Described instruction sending module is used for sending signals collecting instruction to described physiological signal collection module:
Described physiological signal collection module is used for Received signal strength acquisition instructions and gathers individual physiological signal raw data, by procotol, described individual physiological signal raw data is sent to described signal conversion module and described signal processing module:
Described signal conversion module is sent to described high in the clouds data center after being used for that described individual physiological signal raw data is stored into binary file:
Described signal processing module is used for the interference such as the power frequency noise of described individual physiological signal raw data to carry out filtering, based on the traditional characteristic of described individual physiological signal raw data, moment characteristics, feature is shaken in instantaneous frequency and local, described in nonlinear characteristic and the feature extraction of time domain local scale, the affective characteristics of individual physiological signal raw data is as individual physiological signal primary data, and described individual physiological signal primary data is sent to described cloud server, the wherein traditional characteristic of physiological signal, refer to the various affective characteristicses used in emotion recognition research in early days, the feature of emotion physiological data is measured by various statistical indicator, as average, variance, intermediate value etc.:
Described non-physiology information detecting module is for gathering individual non-physiologic information data and being stored to described data memory module:
The individual non-physiologic information data of described data memory module for storing different time length, and send it to described cloud server;
Described cloud server is for receiving described individual physiological signal primary data and the non-physiologic information data of described individual, and emotion recognition model is set up as support vector machine classifier to described individual physiological signal primary data, carry out emotional semantic classification, emotional semantic classification is carried out to described individual non-physiologic information data acquisition decision tree and NaiveBayes (naive Bayesian) algorithm, finally based on rough set theory, merger is carried out to both classification results, obtain the initial affective state result of individual and include the multi-dimensional data table collection of individual physiological signal primary data and the non-physiologic information data of individual, and multi-dimensional data table collection is sent to described high in the clouds data center, initial for individual affective state result is pushed in described non-physiology information detecting module by internet simultaneously:
Described high in the clouds data center is used for sorting out and preserving described individual physiological signal raw data and described multi-dimensional data table collection, in order to data mining.
Preferably, described instruction sending module, described non-physiology information detecting module, described signal conversion module, described signal processing module and described data memory module are integrated in a client.
Preferably, described client is mobile phone or computer.
Preferably, described physiological signal collection module comprises skin electrical signal collection module, ecg signal acquiring module, electroencephalogramsignal signal acquisition module, blood pressure signal acquisition module, breath signal acquisition module, body temperature acquisition module, eye signal acquisition module.
Preferably, described non-physiology information detecting module comprises browser, micro-letter, microblogging.
Preferably, described individual physiological signal raw data comprises muscle and skin tension signal, palm sweat signal, heart rate signal, pulse signal, EEG signals, electromyographic signal, blood pressure signal, oxygen saturation signal, blood volume beat signals, breath signal, temperature signals and electromyogram signal.
Preferably, described non-physiologic information data comprise voice, text, emoticon, individual photo, limbs behavior, dailyly browse webpage information data, to the selection data of PUSH message and weather data.
Preferably, described cloud server propelling movement content comprises the relevant commodity of affective state result initial with individual; With individual physiological, advertisement that health status is relevant, suggestion, news, picture and video.
Preferably, the propelling movement object of described Cloud Server is other users similar with individual affective state.
The invention has the beneficial effects as follows: carry out in the Push Service system of message push existing according to the non-physiologic information data prediction of individual, add individual physiological signal data, by to individual physiological signal data and individual's non-physiologic information data binding analysis, according to personal mood, emotion state classification and prediction, to predict the outcome and be pushed to individual client by internet and hold in software, realize efficiently, Information Push Service accurately; Storage and the analysis of individual physiological signal raw data contribute to psychology, medical research, individual also can be assisted to understand the affective state of oneself so that appropriateness regulates, prevent the mental diseases such as such as depression, simultaneously for affective state classification industry standard provides foundation: special, storing of multi-dimensional data table collection helps auxiliary social network sites exploitation New function, auxiliary media industry improves the accuracy of service, the exploitation of the exploitation of assistant voice assistant and intelligent robot, artificial intelligence.
Accompanying drawing explanation
Fig. 1 is the function structure chart carrying out the Information Push Service system of emotion recognition and prediction based on large data of the embodiment of the present invention.
Embodiment
Understand technical scheme of the present invention better to make those skilled in the art can be implemented, below in conjunction with the drawings and specific embodiments, the present invention is further described, but illustrated embodiment is not as a limitation of the invention.
The invention provides a kind of Information Push Service system of carrying out emotion recognition and prediction based on large data, specifically as shown in Figure 1, comprise physiological signal collection module 2, client, cloud server 6 and high in the clouds data center 4, client is integrated with instruction sending module 1, non-physiology information detecting module 8, signal conversion module 3, signal processing module 5 and data memory module 7:
Instruction sending module 1 sends signals collecting instruction to physiological signal collection module 2, physiological signal collection module 2 is integrated with skin electrical signal collection module, heart rate signal acquisition module, electroencephalogramsignal signal acquisition module, blood pressure signal acquisition module, breath signal acquisition module, body temperature acquisition module, the physiological signal collection modules such as eye signal acquisition module, be used for gathering individual muscle and skin tension signal, palm sweat signal, heart rate signal, pulse signal, EEG signals, electromyographic signal, blood pressure signal, oxygen saturation signal, blood volume beat signals, breath signal, the individual physiological signal raw data such as temperature signals and electromyogram signal, and by procotol, the individual physiological signal raw data collected is sent to signal conversion module 3 and the signal processing module 5 of client:
Non-physiology information detecting module 8 gathers individual non-physiologic information data, and be stored to the data memory module 7 of client, non-physiology information detecting module 8 is for being integrated in the popular software of client, as browser, micro-letter, microblogging etc., non-physiologic information data are specially user and use the daily interchange custom language used during client integrated software for a long time, as voice, text, emoticon, individual photo, limbs behavior etc., also comprise that user is daily browses webpage information data, selection data and weather data etc. to PUSH message;
Signal conversion module 3 sends to high in the clouds data center 4 after the individual physiological signal raw data received is stored into binary file, rear persistence is sorted out: the interference such as the power frequency noise of the individual physiological signal raw data received are carried out filtering by signal processing module 5 by high in the clouds data center 4, based on the traditional characteristic of described individual physiological signal raw data, moment characteristics, feature is shaken in instantaneous frequency and local, the affective characteristics of individual physiological signal raw data described in nonlinear characteristic and the feature extraction of time domain local scale is as the individual physiological signal primary data being convenient to cloud server 6 computing again:
Cloud server 6 receives individual physiological signal primary data and the non-physiologic information data of individual, and emotion recognition model is set up as support vector machine classifier to described individual physiological signal primary data, carry out emotional semantic classification, emotional semantic classification is carried out to described individual non-physiologic information data acquisition decision tree and NaiveBayes algorithm, finally based on rough set theory, merger is carried out to both classification results, obtain the initial affective state result of individual and include the multi-dimensional data table collection of individual physiological signal primary data and the non-physiologic information data of individual, and multi-dimensional data table collection is sent to high in the clouds data center 4 and carries out permanent storage in order to data mining, initial for individual affective state result is pushed to individual client by internet to hold in software simultaneously.
According to the initial affective state result of individual, associate other users similar with individual affective state and carry out information pushing and realize the social functions such as instant messaging; The commodity that association and individual mood or mood are correlated with push: associate and push with individual physiological, advertisement, suggestion, news, picture, video etc. that health status is relevant.
Below for electrocardiogram (ECG) data, to illustrate using mobile phone as client and gather the whole flow process that individual psychology signal data carries out Information Push Service.
Mobile phone sends electrocardiosignal to ecg signal acquiring module and adopts instruction, ecg signal acquiring module is received instruction and is gathered individual electrocardiosignal raw data, and by procotol, individual electrocardiosignal raw data is sent to cell-phone customer terminal, cell-phone customer terminal constantly receives individual electrocardiosignal raw data, and draw cardiogram according to individual electrocardiosignal raw data, be regularly sent to high in the clouds data center after individual electrocardiosignal raw data being stored into binary file simultaneously and store.Cell-phone customer terminal is according to the cardiogram drawn, basic physiological characteristic value and heart rate value is obtained by algorithm, heart rate value is sent on cloud server, cloud server receives heart rate value and carries out pre-service to it, obtain the operation result needed, in conjunction with existing anticipation result (according to user version, emoticon, the result that the Recent data such as voice are analyzed out) refinement affective state, obtain the initial affective state result of individual and include the multi-dimensional data table collection of heart rate value and existing anticipation result, and multi-dimensional data table collection is sent to high in the clouds data center and carries out permanent storage in order to data mining, initial for individual affective state result is pushed to individual client by internet to hold in software simultaneously.According to the initial affective state result of individual, the commodity that association is relevant with individual mood or mood push: associate the advertisement, suggestion, news, picture, video etc. of being correlated with individual physiological, health status and push: associate other users similar with individual affective state and carry out propelling movement and realize the social functions such as instant messaging, high in the clouds data center stores individual electrocardiosignal raw data and can be used for medical research, medical diagnosis on disease etc.
The above; above embodiment is only in order to illustrate technical scheme of the present invention; be not intended to limit; protection scope of the present invention is not limited thereto; anyly be familiar with those skilled in the art in the technical scope that the present invention discloses; simple change or the equivalence of the technical scheme that can obtain apparently are replaced, and all belong to protection scope of the present invention.
Claims (9)
1. one kind is carried out the Information Push Service system of emotion recognition and prediction based on large data, it is characterized in that, comprise physiological signal collection module, instruction sending module, non-physiology information detecting module, signal conversion module, signal processing module, data memory module, cloud server and high in the clouds data center;
Described instruction sending module is used for sending signals collecting instruction to described physiological signal collection module;
Described physiological signal collection module is used for Received signal strength acquisition instructions and gathers individual physiological signal raw data, by procotol, described individual physiological signal raw data is sent to described signal conversion module and described signal processing module;
Described signal conversion module is sent to described high in the clouds data center after being used for that described individual physiological signal raw data is stored into binary file;
Described signal processing module is used for the power frequency noise jamming of described individual physiological signal raw data to carry out filtering, shake the affective characteristics of individual physiological signal raw data described in feature, nonlinear characteristic and the feature extraction of time domain local scale as individual physiological signal primary data based on the traditional characteristic of described individual physiological signal raw data, moment characteristics, instantaneous frequency and local, and described individual physiological signal primary data is sent to described cloud server;
Described non-physiology information detecting module is for gathering individual non-physiologic information data and being stored to described data memory module;
The individual non-physiologic information data of described data memory module for storing different time length, and send it to described cloud server;
Described cloud server is for receiving described individual physiological signal primary data and the non-physiologic information data of described individual, and emotion recognition model is set up to described individual physiological signal primary data carry out emotional semantic classification, emotional semantic classification is carried out to described individual non-physiologic information data acquisition decision tree and NaiveBayes algorithm, finally based on rough set theory, merger is carried out to both classification results, obtain the initial affective state result of individual and include the multi-dimensional data table collection of individual physiological signal primary data and the non-physiologic information data of individual, and multi-dimensional data table collection is sent to described high in the clouds data center, initial for individual affective state result is pushed in described non-physiology information detecting module by internet simultaneously,
Described high in the clouds data center is used for sorting out and preserving described individual physiological signal raw data and described multi-dimensional data table collection, in order to data mining.
2. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, it is characterized in that, described instruction sending module, described non-physiology information detecting module, described signal conversion module, described signal processing module and described data memory module are integrated in a client.
3. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 2, is characterized in that, described client is mobile phone or computer.
4. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, it is characterized in that, described physiological signal collection module comprises skin electrical signal collection module, ecg signal acquiring module, electroencephalogramsignal signal acquisition module, blood pressure signal acquisition module, breath signal acquisition module, body temperature acquisition module, eye signal acquisition module.
5. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, is characterized in that, described non-physiology information detecting module comprises browser, micro-letter, microblogging.
6. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, it is characterized in that, described individual physiological signal raw data comprises muscle and skin tension signal, palm sweat signal, heart rate signal, pulse signal, EEG signals, electromyographic signal, blood pressure signal, oxygen saturation signal, blood volume beat signals, breath signal, temperature signals and electromyogram signal.
7. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, it is characterized in that, described non-physiologic information data comprise voice, text, emoticon, individual photo, limbs behavior, dailyly browse webpage information data, to the selection data of PUSH message and weather data.
8. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, is characterized in that, described cloud server pushes content and comprises the relevant commodity of affective state result initial with individual; With individual physiological, advertisement that health status is relevant, suggestion, news, picture and video.
9. Information Push Service system of carrying out emotion recognition and prediction based on large data according to claim 1, is characterized in that, the propelling movement object of described cloud server is other users similar with individual affective state.
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