CN113553417B - Feedback method for user terminal and system for implementing the method - Google Patents
Feedback method for user terminal and system for implementing the method Download PDFInfo
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- CN113553417B CN113553417B CN202110812565.XA CN202110812565A CN113553417B CN 113553417 B CN113553417 B CN 113553417B CN 202110812565 A CN202110812565 A CN 202110812565A CN 113553417 B CN113553417 B CN 113553417B
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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 feedback method for user terminal and a system for implementing the method are provided. The method comprises the following steps: step S1: the opened user terminal continuously transmits the collected voice near the user terminal to a database terminal, the database terminal analyzes the received voice into sentence text, and the user uses the meaning related text to be included into 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 or not, if not, the information is deleted, and if so, the S3 is switched to; step S3: and comparing the speaking statement calculated by the server with information data of a database end, and calculating whether the statement is related to user use meanings, if so, recording the statement by the server, and if not, deleting. The method is beneficial to the merchant to acquire the information fed back by the user after use, so that the product is optimized.
Description
Technical Field
The embodiment of the invention relates to the technical field of feedback methods, in particular to a feedback method used by a user terminal and a system for realizing the method.
Background
With the progress of technological development, the requirements of people on the functions of commodities are higher and higher, and the commodities purchased by people are expected to be intelligent and have a plurality of functions. User opinion on goods is often useful because these opinion are indeed problems the user encounters during use, and gathering user problems may further optimize the product. The general method for feeding back comments is to leave a message to customer service of the purchase channel, or leave a message on the official network, or make a call with a hot line. Users need to go to some specific channels to feedback on these problems they are experiencing. However, the user sometimes feels troublesome to feed back comments, and does not go to the official website of the commodity or leave a message to feed back comments in the official place, etc. If not a particular quality issue, affecting the interests of the user, the user will not typically be given a specified channel to make these comments. These ideas are in fact very valuable for improvement of the product.
Thus, there is a need for a method that can facilitate feedback of comments by a user to optimize a product.
Disclosure of Invention
In view of this, a feedback method and system for user terminals are presented herein. When a user uses a product, the method acquires voices near the product through the product, and obtains descriptions of which users say are aiming at the product through big data analysis, so that the opinion of the user is extracted. The method can enable the user to give precious comments under the condition that the user does not need to leave a message in a designated place, and is beneficial to the merchant to acquire information fed back after the user uses the information, so that the product is optimized.
According to an aspect of the embodiment of the present invention, the embodiment of the present invention provides a feedback method for user terminal, including the following steps:
step S1: the opened user terminal continuously transmits the collected voice near the user terminal to a database terminal, the database terminal analyzes the received voice into sentence text, and the user uses the meaning related text to be included into 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 or not, if not, the information is deleted, and if so, the step S3 is carried out;
step S3: and comparing the speaking statement calculated by the server with information data of a database end, and calculating whether the statement is related to user use meanings, if so, recording the statement by the server, and if not, deleting.
In some embodiments, the server in step S2 is a terminal side server; and is also provided with
The method for calculating whether the voice contains the speaking sentence at the server side is to analyze the voice into characters for judgment.
In some embodiments, the step S3 of comparing the speech sentence calculated by the server with the information data of the database side and calculating whether the sentence is related to the user' S use intention is performed by a big data classification algorithm.
In some embodiments, step S3 records the statement of user opinion of use and the feedback time in the form of a server blockchain.
According to another aspect of the embodiment of the present invention, the embodiment of the present invention provides a system for a user terminal to use a feedback method, including the following parts: user terminal, database terminal and server terminal, wherein
The user terminal collects surrounding voices and continuously sends the voices to the database terminal and the server terminal;
the database terminal is used for receiving the data sent by the user terminal, judging whether the data is in the user use intention related classification algorithm, if so, the data is included in the information data set, and if not, the data is deleted;
the server side calculates the sound data sent by the user terminal, calculates whether the sound data contains speaking sentences and judges whether the sound data is related to the user using meanings, if so, records the sentences, and if not, deletes the sentences.
In some embodiments, the user terminal sends the collected voice to the database end as a data set of big data analysis, so that the data set of big data analysis is enlarged continuously, and an algorithm is optimized continuously.
In some embodiments, the user terminal sends the collected voice to the server, the server calculates whether the voice obtained by analysis is a speaking sentence, determines whether the speaking sentence is related to the product opinion through big data analysis, if so, the server records the sentence on the blockchain, and if not, the server deletes the sentence.
In some embodiments, the server is the user terminal side server; and the server side records the statement of the user use opinion and the feedback time in the form of a block chain.
In some embodiments, the method of the server calculating whether to include a speaking statement is to determine that the voice is parsed into text; whether the voice is relevant to the user's use intention is judged by comparing the voice calculated by the server with the information data of the database terminal, and calculating by a big data classification algorithm.
In some embodiments, the server side server periodically receives the database side optimized calculation model, so that a more optimized calculation model is used when the big data analysis statement text is related to the user's use intention.
The invention relates to a feedback method for user terminals such as electronic products and a system for realizing the method. When a user uses a product, the method and the system acquire voices near the product through the product, and obtain descriptions of which users say the voices are aimed at the product through big data analysis, so that the opinion of the user is extracted. The method and the system can enable the user to give precious comments under the condition that the user does not need to leave a message in a designated place, and are beneficial to the merchant to acquire information fed back after the user uses the information, so that the product is optimized.
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Fig. 1 is a flowchart of a feedback method used by a user terminal 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 the particular system architecture, 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 feedback method for a user terminal and a system for realizing the method.
According to an aspect of the embodiment of the invention, the embodiment of the invention provides a feedback method for a user terminal.
Referring to fig. 1, fig. 1 is a flowchart of a feedback method used by a ue according to an embodiment of the present invention.
As shown in fig. 1, the method includes:
step S1: the opened user terminal continuously transmits the collected voice near the user terminal to the database terminal, and the database terminal analyzes the received voice into sentence text and brings the text related to user's use intention into information data.
The user terminal may be a mobile device such as a mobile phone, a personal digital assistant (PersonalDigital Assistant, PDA), a tablet computer, a portable device (e.g., a portable computer, a pocket computer, or a handheld computer); or may be a stationary device such as a desktop computer.
The evaluation of the product 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 or not, if not, the information is deleted, and if so, the step S3 is carried out.
Step S3: and comparing the speaking statement calculated by the server with information data of a database end, and calculating whether the statement is related to user use meanings, if so, recording the statement by the server, and if not, deleting.
The method of the embodiment of the invention can also provide precious comments in a complex mode that the user does not need to run to a designated place to leave a message, is beneficial to the merchant to acquire feedback information used by the user, and thus optimizes the product. According to the invention, when a user uses the product, the voice near the product is obtained through the product, and the descriptions of which users say are aimed at the product are obtained through big data analysis, so that the precious opinion of the user is obtained, and the product optimization is facilitated.
When a user uses the product, namely when an electronic switch of the product is turned on, the range of sound acquired by the product is limited, only the sound which is very close to the product is acquired, and only the sound which is very close can analyze the statement of the voice description. When a user uses a product, the problem of spitting the product is likely, for example, when a child story player is used, some users can say that the songs of the machine are just a few, and the users cannot update the machine; if the machine can update the song by itself, the sound of the machine is too loud, the sound is minimized, or the machine is noisy, so that the child can hear where the song is received; alternatively, the baby really likes the toy, and the toy is better if the keys are simpler. Etc. After sentences related to the product opinion are identified through big data analysis, the problems are fed back to the merchant, so that a method for feeding back the service condition of the user is realized.
In some embodiments, the server in step S2 is a terminal side server; and is also provided with
The method for calculating whether the voice contains the speaking sentence at the server side is to analyze the voice into characters for judgment.
The product is usually used geographically, basically in the home. The method for calculating by using the server at the terminal side can greatly improve the speed of analyzing big data, and sentence analysis is carried out by transmitting the sentence analysis to the server, so that the use of users is not affected at all.
In some embodiments, the step S3 of comparing the speech sentence calculated by the server with the information data of the database side and calculating whether the sentence is related to the user' S use intention is performed by a big data classification algorithm.
In some embodiments, step S3 records the statement of user opinion of use and the feedback time in the form of a server blockchain.
The user feedback statement obtained by analyzing the big data is recorded through the block chain and is 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) The user opens and uses the terminal (e.g., 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 sentence texts, the text information is included in an information data set, and an algorithm is continuously optimized;
3) The terminal continuously transmits 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 statement or not, 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 intention of the user or not by using a big data classification algorithm through an algorithm updated with the cloud;
5) If the user is related to the user's use intention, the server records the statement, and records the information fed back by the user and the time of feedback in the form of a blockchain.
Merchants can periodically view content on the blockchain to obtain user feedback to optimize their own products.
According to another aspect of the embodiment of the present invention, the embodiment of the present invention provides 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: the system comprises a user terminal, a database terminal and a server terminal.
The user terminal collects the surrounding voice and continuously sends the voice to the database terminal and the server terminal;
the database terminal is used for receiving the data sent by the user terminal, judging whether the data is in the user use intention related classification algorithm, if so, the data is included in the information data set, and if not, the data is deleted;
the server side calculates the voice data sent by the user terminal, calculates whether the voice data contains speaking sentences and judges whether the voice data is related to the user using meanings, if so, records the sentences, and if not, deletes the sentences.
The system of the embodiment of the invention can also provide precious comments in a complex mode that the user does not need to run to a designated place to leave a message, is beneficial to the merchant to acquire feedback information used by the user, and thus optimizes the product.
In some embodiments, the user terminal sends the collected voice to the database end as the data set of big data analysis, thereby expanding the data set of big data analysis and optimizing the algorithm.
In some embodiments, the user terminal sends the collected voice to the server, the server calculates and analyzes whether the collected 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 blockchain, and if not, the server deletes the sentence.
The method records the user using the meaning related information by using the blockchain, and ensures 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 also provided with
The server side records sentences of user use opinions and feedback time in a block chain mode.
The server on the terminal side means the server closest to the terminal. The terminal side server is used for greatly improving the speed of big data analysis, sentence analysis is carried out by being transmitted to the server, and the use of users is not affected at all.
In some embodiments, the method of the server calculating whether to include the speaking statement is to determine that the voice analysis is changed into text;
whether the voice is relevant to the user's use intention is judged by comparing the voice calculated by the server with the information data of the database terminal, and calculating by a big data classification algorithm.
In some embodiments, the server-side server periodically receives the database-side optimized computing model, thereby using a more optimized computing model when the big data analysis statement text is relevant to the user's use of the intent.
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. use terminals, e.g. children's electronic toys
(1) When a user uses a terminal, first the development of the electronic device must be already open.
The terminal collects sounds around the terminal and continuously sends the sounds to the cloud and the terminal side server.
The terminal sends the collected sound to the cloud as a data set for big data analysis, so that the data set for big data analysis is continuously expanded, and the algorithm is continuously optimized.
Meanwhile, the terminal sends the collected sound to a server at the terminal side, the server calculates and analyzes whether the obtained sound is a speaking sentence, whether the speaking sentence is related to the product opinion is judged through big data analysis, and if so, information is recorded on a block chain.
2. The server side server means the server closest to the terminal.
(1) The terminal side server receives the voice data transmitted from the terminal, and calculates whether the voice data contains a speaking sentence or not by performing an operation on the server side (here, the analysis voice is a very general technology, for example, the text can be converted by the micro-message transmission voice).
(2) After the server analyzes the voice into words, the server calculates whether the sentence is related to the user's use intention or not through big data analysis.
(3) If the user feedback information is related to the user using intention, the server records the statement, and records the user feedback information each time in the form of a blockchain.
(4) And the server regularly receives the cloud-optimized calculation model. A more optimal calculation model is used when whether the big data analysis statement text is related to the user's use intention.
3. Cloud end, e.g. database end
(1) The method is used for receiving the data sent by the terminal, expanding the data set and continuously optimizing the algorithm.
(2) Classification algorithm for judging whether sentence characters are related to user's using meaning or not:
because the rules of the text classification model algorithm are that there is a data set, some data is manually marked, such information is relevant to the user's use of the idea, and the other information is irrelevant. Such as "songs of this machine are so few that they are not updated by themselves. If the machine can update the song by itself, the sound of the machine is too loud, the sound is tuned to be minimum or loud, the child hears where the child is, or the toy is liked by the baby, the toy is better if the key is simpler.
The inventors found that the description habits of the user are: if XX is good, the machine XX, how the toy is, etc. By labeling these keywords, a model is 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 one section value when the user uses the result of the opinion.
Because the information of the user is transmitted to the cloud end each time, the cloud end has a large amount of information data sets, and the information data sets can be used for making a basis of data modeling. The specific analysis method adopted by the message analysis module belongs to the prior art.
The algorithm of using feedback statement that whether the statement is recorded as a toy is:
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 which keywords are contained in the evaluation to be an effective evaluation for the product. Such as: not imagined, worn out, machine updated, etc.
When a sentence is collected by the toy, it is predicted by big data analysis that the sentence is a return value for an evaluation sentence of the toy. [0,1] may be a range of 0 to 1.
The person who uses the device frequently (e.g. the sound of the owner of the toy) can be known by daily collection of speech. If the sound collected is of the toy owner then a value of 0.1 is added on the basis of the return value, otherwise 0.1 is subtracted (since the comment meaning may not be great if it is not a person who uses the device frequently).
The time of the frequent use of the device can also be known by daily voice acquisition. If the time at which sound is collected is the time at which the toy is played frequently, a value of 0.1 is added on the basis of the return value, otherwise 0.1 is subtracted (because if it is not the usual time, it may not be that the person who is using the device at ordinary times is using, the meaning of comments is not great).
After calculation, sentences with a result higher than 0.5 are considered as recordable sentences, while sentences with a result lower than 0.5 are not recorded.
When the user uses the product, the user terminal uses the feedback method and the system to acquire the voice nearby the product through the product, and obtains the descriptions of which users say are aiming at the product through big data analysis, so as to extract the opinion of the user. The method and the system of the invention can enable the user to provide precious comments without leaving a message in a designated place, and are beneficial to the merchant to acquire the information fed back by the user after use, thereby optimizing the product.
The reader will appreciate that in the description of this specification, a description of terms "one embodiment," "some embodiments," "examples," "specific examples," 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, schematic representations of the above terms are not necessarily directed 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, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of 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, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be further understood that, in the embodiments of the present invention, the sequence numbers of the foregoing processes do not mean the execution sequence, and the execution sequence of each process should be determined by the functions and the internal logic of each process, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (9)
1. A feedback method for user terminal comprises the following steps:
step S1: the opened user terminal continuously sends the collected voice near the user terminal to the cloud, the cloud analyzes the received voice into sentence text, and the user uses the intention related text to be included into 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 or not, if not, the information is deleted, and if so, the step S3 is carried out;
step S3: comparing the speaking sentence calculated by the server with the cloud information data, and calculating whether the sentence is related to the user's use meaning, if so, recording the sentence by the server, if not, deleting,
wherein the server in step S2 is a terminal side server, the server of the server side periodically receives the cloud-optimized calculation model,
in step S3, a return value of the speaking sentence for an evaluation sentence of the user terminal is predicted by big data analysis,
the person who frequently uses the user terminal can know through daily voice collection, if the collected voice is the voice of the user terminal, a preset value is added on the basis of the return value, otherwise, the preset value is subtracted,
the time of frequently using the user terminal can be known by daily voice collection, if the time of collecting the voice is the time of frequently using the user terminal, a preset value is added on the basis of the return value, otherwise, the preset value is subtracted,
after calculation, the speech sentences with the result higher than the threshold are considered as sentences that can be recorded, while speech sentences with the result lower than the threshold are not recorded.
2. The method according to claim 1, wherein the step S2 of calculating whether the speech includes a speaking sentence is performed by converting the speech analysis into text.
3. The method according to claim 1, wherein the step S3 of comparing the speech sentence calculated by the server with the cloud information data and calculating whether the sentence is related to the user' S intention is performed by a big data classification algorithm.
4. The method of claim 1, wherein step S3 records the statement of user opinion of use and the feedback time in the form of a server blockchain.
5. A system for a user terminal to use a feedback method, comprising: user terminal, cloud end and server end, wherein
The user terminal collects surrounding voices and continuously sends the voices to the cloud end and the server end;
the cloud end is used for receiving the data sent by the user terminal, judging whether the data is in a user use intention related classification algorithm, if so, the data is included in the information data set, and if not, the data is deleted;
the server side calculates the voice data sent by the user terminal, calculates whether the voice data contains speaking sentences and judges whether the voice data is related to the user using meanings, if so, records the sentences, if not, deletes the sentences,
wherein the server is a user terminal side server, the server of the server side periodically receives the cloud-optimized calculation model,
by big data analysis, a return value of the speaking sentence for an evaluation sentence of the user terminal is predicted,
the person who frequently uses the user terminal can know through daily voice collection, if the collected voice is the voice of the user terminal, a preset value is added on the basis of the return value, otherwise, the preset value is subtracted,
the time of frequently using the user terminal can be known by daily voice collection, if the time of collecting the voice is the time of frequently using the user terminal, a preset value is added on the basis of the return value, otherwise, the preset value is subtracted,
after calculation, the speech sentences with the result higher than the threshold are considered as sentences that can be recorded, while speech sentences with the result lower than the threshold are not recorded.
6. The system of claim 5, wherein the user terminal transmits the collected voice to the cloud as a data set for big data analysis.
7. The system of claim 5, wherein the user terminal transmits the collected voice to the server terminal, the server terminal calculates and analyzes whether the collected 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 blockchain, and if not, the server terminal deletes the sentence.
8. The system of claim 5, wherein the server side records the statement of user opinion of use and the feedback time in the form of a blockchain.
9. The system of claim 5, wherein the server calculates whether the speech sentence is included by determining that the speech analysis is text;
whether the voice is related to the user using intention is judged by comparing the voice calculated by the server with information data of the cloud, and calculating by a big data classification algorithm.
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| Publication number | Priority date | Publication date | Assignee | Title |
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