CN113553417A - User terminal use feedback method and system for implementing same - Google Patents
User terminal use feedback method and system for implementing same Download PDFInfo
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- CN113553417A CN113553417A CN202110812565.XA CN202110812565A CN113553417A CN 113553417 A CN113553417 A CN 113553417A CN 202110812565 A CN202110812565 A CN 202110812565A CN 113553417 A CN113553417 A CN 113553417A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/332—Query formulation
- G06F16/3329—Natural language query formulation or dialogue systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3343—Query execution using phonetics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/338—Presentation of query results
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/01—Customer relationship services
- G06Q30/015—Providing customer assistance, e.g. assisting a customer within a business location or via helpdesk
- G06Q30/016—After-sales
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
A user terminal use feedback method and a system for realizing the method are provided. The method comprises the following steps: step S1: the opened user terminal continuously sends the collected voice near the user terminal to the database terminal, the database terminal analyzes the received voice into a sentence text, and brings the text related to the use opinions of the user into the information data; step S2: the user terminal continuously sends the collected voice near the user terminal to the server, when the server receives the voice information collected by the user terminal, the server calculates whether the voice contains a speaking sentence, if not, the information is deleted, and if yes, the S3 is switched to; step S3: and comparing the speaking sentence calculated by the server with the information data of the database end and calculating whether the sentence is related to the use opinions of the user, if so, recording the sentence by the server, and if not, deleting the sentence. The method is beneficial for merchants to obtain the information fed back by the users after use, thereby optimizing products.
Description
Technical Field
The embodiment of the invention relates to the technical field of feedback methods, in particular to a user terminal use feedback method and a system for realizing the method.
Background
Now, with the development and progress of science and technology, people have higher and higher requirements on the functions of commodities, and hope that commodities purchased by people can be intelligent and have a plurality of functions. User opinions about the goods are often useful because they are really problems that the user encounters during use, and gathering the user's problems can further optimize the product. The general opinion feedback method is to leave a message at a customer service place of a purchase channel, or leave a message on an official website, or dial a hotline. The user needs to go to some specific channels to feedback the problems he or she encounters. However, the user sometimes feels that the feedback is troublesome and does not leave a message or the like on the official website or the official place of the product. If it is not a special quality problem, it will not generally get the designated channel to propose the opinions, which affects the interests of the user. These opinions are really invaluable for the improvement of the product.
Therefore, there is a need for a method that can facilitate feedback from a user to optimize a product.
Disclosure of Invention
In view of the above, a method and system for user terminal usage feedback are provided. When a user uses a product, the method obtains the voice near the product through the product, and obtains which users speak the description of the product through big data analysis, so that the opinions of the users are extracted. The method enables the user to put forward valuable opinions without leaving a message at a designated place, and is beneficial to a merchant to obtain information fed back by the user after use, thereby optimizing the product.
According to an aspect of the embodiments of the present invention, an embodiment of the present invention provides a user terminal usage feedback method, including the following steps:
step S1: the opened user terminal continuously sends the collected voice near the user terminal to the database terminal, the database terminal analyzes the received voice into a sentence text, and brings the text related to the use opinions of the user into the information data;
step S2: the user terminal continuously sends the collected voice near the user terminal to the server, when the server receives the voice information collected by the user terminal, the server calculates whether the voice contains a speaking sentence, if not, the information is deleted, and if yes, the step S3 is carried out;
step S3: and comparing the speaking sentence calculated by the server with the information data of the database end and calculating whether the sentence is related to the use opinions of the user, if so, recording the sentence by the server, and if not, deleting the sentence.
In some embodiments, the server in step S2 is a terminal-side server; and is
The method for calculating whether the voice contains the speaking sentence at the server end is to judge by converting the voice analysis into characters.
In some embodiments, the step of comparing the utterance sentence calculated by the server with the database-side information data and calculating whether the sentence is related to the opinion used by the user in step S3 is performed by a big data classification algorithm.
In some embodiments, step S3 records the sentence of the user' S opinion for use and the feedback time in the form of a server blockchain.
According to another aspect of the embodiments of the present invention, there is provided a system for a user terminal to use a feedback method, including: user terminal, database terminal and server terminal, wherein
The user terminal collects surrounding voices and continuously sends the voices to the database end and the server end;
the database end is used for receiving the data sent by the user terminal, judging whether the data is in the opinion related classification algorithm used by the user, if the data is in the opinion related classification algorithm used by the user, the data is included in the information data set, and if the data is not in the opinion related classification algorithm used by the user, the data is deleted;
and the server calculates the sound data sent by the user terminal, calculates whether the sound data contains a speaking sentence and judges whether the sound data is related to the use opinions of the user, records the sentence if the sound data is related to the use opinions of the user, and deletes the sentence if the sound data is not related to the use opinions of the user.
In some embodiments, the user terminal sends the collected voice to the database terminal as a data set for big data analysis, so as to continuously enlarge the data set for big data analysis and continuously optimize an algorithm.
In some embodiments, the user terminal sends the collected voice to the server, the server calculates and analyzes whether the obtained voice is a speaking sentence, and judges whether the speaking sentence is related to the product opinion through big data analysis, if so, the server records the sentence on a block chain, and if not, the sentence is deleted.
In some embodiments, the server is the user terminal side server; and the server side records the statement of the user opinion and the feedback time in a block chain mode.
In some embodiments, the server calculates whether the spoken sentence is included by determining from a speech utterance to a text utterance; the judgment of whether the opinion is related to the user use opinion is calculated by comparing the voice calculated by the server with the information data of the database side and calculating through a big data classification algorithm.
In some embodiments, the server at the server side periodically receives the optimized calculation model at the database side, so that a more optimized calculation model is used when the big data analysis statement text is related to the opinion used by the user.
The invention relates to a method for feeding back the use of a user terminal such as an electronic product and a system for realizing the method. When a user uses a product, the method and the system acquire the voice near the product through the product, and obtain the description of which users say the product through big data analysis, thereby extracting the opinions of the users. The method and the system enable the user to put forward valuable opinions without leaving a message at a designated place, and are beneficial to a merchant to obtain information fed back by the user after use, thereby optimizing the product.
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Fig. 1 is a flowchart of a user terminal usage feedback method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a system for a user terminal to use a feedback method according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
The embodiment of the invention provides a user terminal use feedback method and a system for realizing the method.
According to an aspect of an embodiment of the present invention, an embodiment of the present invention provides a user terminal usage feedback method.
Referring to fig. 1, fig. 1 is a flowchart illustrating a user terminal feedback method according to an embodiment of the present invention.
As shown in fig. 1, the method includes:
step S1: the opened user terminal continuously sends the collected voice near the user terminal to the database terminal, the database terminal analyzes the received voice into a sentence text, and the text related to the use opinions of the user is brought into the information data.
The user terminal may be a mobile device such as a mobile phone, a Personal Digital Assistant (PDA), a tablet computer, and a portable device (e.g., a laptop computer, a pocket computer, or a handheld computer); or a stationary device such as a desktop computer.
The evaluation of products on the network can be used as an input set, which can make the prediction algorithm more accurate.
Step S2: the user terminal continuously sends the collected voice near the user terminal to the server, when the server receives the voice information collected by the user terminal, the server calculates whether the voice contains a speaking sentence, if not, the information is deleted, and if yes, the step S3 is carried out.
Step S3: and comparing the speaking sentence calculated by the server with the information data of the database end and calculating whether the sentence is related to the use opinions of the user, if so, recording the sentence by the server, and if not, deleting the sentence.
The method of the embodiment of the invention can provide valuable opinions without a complicated mode of leaving messages at the appointed place, and is beneficial to a merchant to obtain the feedback information used by the user, thereby optimizing the product. According to the method, when the user uses the product, the voice around the product is obtained through the product, and the words spoken by the user are obtained through big data analysis, so that the precious opinions of the user are obtained according to the description of the product, and the product optimization is facilitated.
When a user uses a product, namely when an electronic switch of the product is turned on, the range of the sound acquired by the product is limited, and only the sound close to the product can be acquired, and the sentence described by the human voice can be analyzed only by the close sound. When a user uses a product, the user can spit the groove product, for example, when a children story player is used, some users can say that the songs of the machine are just a few, and the songs cannot be updated by themselves; if the machine can update songs by itself, the sound of the machine is too big, and the sound is turned to the minimum or is noisy, so that a child can listen to the music; or, the baby really likes the toy, and if the button is simpler, the toy is better. And so on. After sentences relevant to the product opinions are identified through big data analysis, the problems are fed back to the merchant, and therefore the method for feeding back the use condition of the user is achieved.
In some embodiments, the server in step S2 is a terminal-side server; and is
The method for calculating whether the voice contains the speaking sentence at the server end is to judge by converting the voice analysis into characters.
Generally, the product is used regionally, and is basically used at home. The method of calculating by using the terminal side server can greatly improve the speed of big data analysis, and the statement analysis is transmitted to the server for being carried out, so that the use of a user is not influenced at all.
In some embodiments, the step of comparing the utterance sentence calculated by the server with the database-side information data and calculating whether the sentence is related to the opinion used by the user in step S3 is performed by a big data classification algorithm.
In some embodiments, step S3 records the sentence of the user' S opinion for use and the feedback time in the form of a server blockchain.
User feedback sentences obtained by analyzing the big data are recorded through the block chain and fed back to the merchant, so that the effectiveness, the safety and the non-tamper property of the data are ensured.
In one embodiment, the specific steps of the feedback method used by the user terminal, such as an electronic product, are as follows:
1) a user opens and uses a terminal (e.g., an electronic product device);
2) the terminal continuously sends the collected voice near the terminal to a database end such as a cloud end, the cloud end analyzes the collected information into a sentence text, and brings the text information into an information data set, and an algorithm is continuously optimized;
3) the terminal continuously sends the collected voice near the terminal to the server, when the server receives the information collected by the terminal, the server starts to calculate whether the voice contains a speaking sentence, and if not, the information is deleted;
4) after the server analyzes the voice into words, the server calculates whether the sentence is related to the use opinions of the user by using a big data classification algorithm through an algorithm updated by the cloud;
5) if the opinion is related to the user opinion, the server records the sentence, and records the information fed back by the user and the time when the feedback is carried out in the form of a block chain.
The merchant can regularly check the content on the block chain to acquire the feedback condition of the user, so that the product of the merchant is optimized.
According to another aspect of the embodiments of the present invention, there is provided a system for a user terminal to use a feedback method.
Referring to fig. 2, fig. 2 is a flowchart of a system for a user terminal to use a feedback method according to an embodiment of the present invention.
As shown in fig. 2, the system includes the following parts: the system comprises a user terminal, a database terminal and a server terminal.
The user terminal collects surrounding voices and continuously sends the voices to the database terminal and the server terminal;
the database end is used for receiving data sent by the user terminal, judging whether the data is in the opinion related classification algorithm used by the user, if the data is in the opinion related classification algorithm used by the user, the data is included in the information data set, and if the data is not in the opinion related classification algorithm used by the user, the data is deleted;
the server calculates the sound data sent by the user terminal, calculates whether the sound data contains a speaking sentence and judges whether the speaking sentence is related to the use opinion of the user, if so, the sentence is recorded, and if not, the sentence is deleted.
The system of the embodiment of the invention can provide valuable opinions without a complicated mode that a user leaves a message in a specified place, and is beneficial to a merchant to obtain feedback information used by the user, thereby optimizing products.
In some embodiments, the user terminal sends the collected voice to the database terminal as a data set for big data analysis, so that the data set for big data analysis is expanded continuously, and the algorithm is optimized continuously.
In some embodiments, the user terminal sends the collected voice to the server, the server calculates and analyzes whether the obtained voice is a speaking sentence, and judges whether the speaking sentence is related to the product opinion through big data analysis, if so, the server records the sentence on the block chain, and if not, the sentence is deleted.
And recording the opinion related information used by the user by using a block chain method, so as to ensure that the information cannot be tampered. The algorithm of the invention adopts a classification algorithm and marks keywords.
In some embodiments, the server is a user terminal side server; and is
And the server side records the statement of the user opinion and the feedback time in a block chain mode.
The server on the terminal side means a server closest to the terminal. The speed of big data analysis can be greatly improved by using the terminal side server, and the statement analysis is transmitted to the server, so that the use of a user is not influenced at all.
In some embodiments, the server calculates whether the speech sentence is included by determining from the speech analysis to the text;
the judgment of whether the opinion is related to the user use opinion is calculated by comparing the voice calculated by the server with the information data of the database side and calculating through a big data classification algorithm.
In some embodiments, the server at the server side periodically receives the optimized calculation model at the database side, so that a more optimized calculation model is used when the big data analysis statement words are related to the user use opinions.
More specifically, the system for the user terminal to use the feedback method of the present invention comprises the following parts and specifically operates as follows:
1. using terminals, e.g. electronic toys for children
(1) When a user uses the terminal, the first is when the development of the electronic device must be already on.
The terminal collects the sound around the terminal and continuously sends the sound to the cloud and the terminal side server.
The terminal sends the collected sound to the cloud end as a data set of big data analysis, so that the data set of big data analysis is continuously expanded, and an algorithm is continuously optimized.
Meanwhile, the terminal sends the collected sound to a server at the terminal side, the server calculates and analyzes the sound, whether the obtained sound is a speaking sentence or not is judged through big data analysis, whether the speaking sentence is related to the product opinion or not is judged, and if the speaking sentence is related to the product opinion, the information is recorded on a block chain.
2. The server on the server side and the server on the terminal side mean the server closest to the terminal.
(1) The server at the terminal side receives the voice data sent by the terminal, and performs calculation at the server side to calculate whether the spoken sentence is included (here, the spoken sentence is converted into a character by analyzing the voice, which is a very common technology, for example, the spoken sentence can be converted into a character by sending the voice by wechat).
(2) After the server analyzes the voice into characters, the characters are analyzed through big data, and whether the sentence is relevant to the use opinions of the user or not is calculated.
(3) If the comments are related to the user opinions, the server records the sentence and records the user feedback information and time each time in the form of a block chain.
(4) And the server periodically receives the computing model after cloud optimization. A more optimized computational model is used when the big data analysis statement text is related to the user's opinion.
3. Cloud, e.g. database side
(1) The method is used for receiving data sent by the terminal, expanding the data set and continuously optimizing the algorithm.
(2) Whether the sentence words are related to the opinion used by the user or not is determined as follows:
because the rule of the character classification model algorithm is that a data set is provided, some data are manually marked, such information is relevant to the use opinion of the user, and other information is irrelevant. For example, "songs of this machine are just a few, and are not updated by themselves. If the machine can update the song by itself, if the sound of the machine is too loud, if the sound is turned to the minimum or is too loud, the child hears where the child gets, or if the baby really likes the toy, if the button is simply pressed, the sound is better.
The inventor finds that the description habit of the user is as follows: if XX is good, the machine XX, how the toy is, etc. By means of these keyword labels, models are built, and the result of calculating and predicting a text message should be to return an interval value. That is, the predicted text information is a result of returning an interval value when the user uses the opinion.
Because the information of the user is transmitted to the cloud every time, a large amount of information data sets exist in the cloud, and the information data sets can be used as the basis of data modeling. The specific analysis method adopted by the message analysis module belongs to the prior art.
The algorithm for using the feedback statement whether to record the statement as a toy is as follows:
the server side is provided with a big data text algorithm library, and the evaluation of the product by the user on the network is used as an input set to extract the evaluation of the keywords which is an effective evaluation aiming at the product. Such as: not imagine good, bad, machine update, etc.
When a sentence is collected by the toy, the sentence is predicted to be a return value of an evaluation sentence for the toy through big data analysis. [0,1] may be an interval of 0 to 1.
A person who uses the device frequently (e.g., the sound of the owner of the toy) can be known by collecting voices on a daily basis. A value of 0.1 is added to the returned value if the sound collected is that of the owner of the toy, and 0.1 is subtracted otherwise (since the comment may not be meaningful if it is not a person who uses the device frequently).
The time of using the device frequently can also be known by collecting voices daily. If the time of collecting the sound is the time of frequently playing the toy, a value of 0.1 is added on the basis of the return value, and otherwise 0.1 is subtracted (because if the time is not the frequently-used time, the comment is not significant because the comment is not used by the person who uses the device at ordinary times).
After calculation, sentences with a result higher than 0.5 are considered to be recordable sentences, and sentences lower than 0.5 are not recorded.
According to the user terminal use feedback method and system provided by the embodiment of the invention, when the user uses the product, the voice near the product is obtained through the product, and the description of which user says the product is obtained through big data analysis, so that the opinion of the user is extracted. The method and the system of the invention can make the user put forward valuable opinions without leaving a message at the appointed place, and are beneficial to the merchant to obtain the information fed back by the user after use, thereby optimizing the product.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should also be understood that, in the embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A user terminal use feedback method comprises the following steps:
step S1: the opened user terminal continuously sends the collected voice near the user terminal to the database terminal, the database terminal analyzes the received voice into a sentence text, and brings the text related to the use opinions of the user into the information data;
step S2: the user terminal continuously sends the collected voice near the user terminal to the server, when the server receives the voice information collected by the user terminal, the server calculates whether the voice contains a speaking sentence, if not, the information is deleted, and if yes, the step S3 is carried out;
step S3: and comparing the speaking sentence calculated by the server with the information data of the database end and calculating whether the sentence is related to the use opinions of the user, if so, recording the sentence by the server, and if not, deleting the sentence.
2. The method according to claim 1, wherein the server in step S2 is a terminal side server; and is
The method for calculating whether the voice contains the speaking sentence at the server end is to judge by converting the voice analysis into characters.
3. The method according to claim 1, wherein the step S3 of comparing the utterance sentence calculated by the server with the database-side information data and calculating whether the sentence is related to the opinion used by the user is performed by a big data classification algorithm.
4. The method according to claim 1, wherein the step S3 records the sentence of the user' S opinion and the feedback time in the form of server block chain.
5. A system for a user terminal to use a feedback method, comprising: user terminal, database terminal and server terminal, wherein
The user terminal collects surrounding voices and continuously sends the voices to the database end and the server end;
the database end is used for receiving the data sent by the user terminal, judging whether the data is in the opinion related classification algorithm used by the user, if the data is in the opinion related classification algorithm used by the user, the data is included in the information data set, and if the data is not in the opinion related classification algorithm used by the user, the data is deleted;
and the server calculates the sound data sent by the user terminal, calculates whether the sound data contains a speaking sentence and judges whether the sound data is related to the use opinions of the user, records the sentence if the sound data is related to the use opinions of the user, and deletes the sentence if the sound data is not related to the use opinions of the user.
6. The system of claim 5, wherein the user terminal sends the collected voice to the database as a data set for big data analysis.
7. The system according to claim 5, wherein the user terminal sends the collected voice to the server, and the server calculates and analyzes whether the obtained voice is a speaking sentence, and judges whether the speaking sentence is related to the product opinion through big data analysis, if so, the server records the sentence on the block chain, and if not, the sentence is deleted.
8. The system according to claim 5, wherein the server is the user terminal side server; and is
And the server side records the statement of the user opinion and the feedback time in a block chain mode.
9. The system of claim 5, wherein the server calculates whether the spoken sentence is included by determining whether the speech parsing is changed to text;
the judgment of whether the opinion is related to the user use opinion is calculated by comparing the voice calculated by the server with the information data of the database side and calculating through a big data classification algorithm.
10. The system of claim 5, wherein the server-side server periodically receives the database-side optimized computational model.
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