Data acquisition method and computing device cluster
By performing personalized data acquisition methods on terminal devices or servers, the problem of low data acquisition efficiency in the prior art is solved, and the user's patience and data acquisition efficiency are improved through personalized questionnaires.
Patent Information
- Application Number
- CN202311102946.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-30
- Publication Date
- 2025-02-28
AI Technical Summary
The existing joint selection-based analysis method has the problem of low data collection efficiency in market research. It is mainly due to the lack of patience and heterogeneity of preferences of consumers, which leads to the decline in patience when facing multiple selection tasks and may stop choosing halfway.
By performing a data acquisition method on a terminal device or server, the method includes obtaining information of multiple parameters and values selected by the user, determining a personalized questionnaire based on the information, and presenting it to the user to improve data acquisition efficiency.
Through personalized questionnaires, users' patience is improved, data collection is enhanced, and the quality and integrity of user data are ensured.
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Figure CN119539868A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of computer technology, and in particular to a data collection method and a computing device cluster. Background Art
[0002] It is necessary to quantify the value of products in the product design stage, product development stage or before product sales to help enterprises make better product decisions. At present, enterprises often indirectly quantify the value of products through choice-based conjoint analysis (CBC). This method assumes that a product is composed of multiple attributes (such as a mobile phone has appearance, price, brand and other attributes), and each attribute has multiple levels (such as the price attribute has 1000 yuan, 2000 yuan, 5000 yuan and other levels). By collecting consumers' preference data for multiple attributes of the product and multiple levels of each attribute, the value of the product can be quantified based on the preference data. For example, two virtual products are presented to consumers in the form of a selection task, one of which is brand A, priced at 1000 yuan, and has a low resolution, and the other virtual product is brand B, priced at 3000 yuan, and has a high resolution. Consumers can choose a virtual product they like more, that is, the consumer's preference data indicates the virtual product selected by the consumer, and the enterprise can quantify the value of the product based on the preference data.
[0003] However, CBC needs to meet two assumptions: Assumption 1: Consumers are homogeneous, that is, each consumer needs to complete the same multiple selection tasks; Assumption 2: Consumers have very good patience and are willing to complete multiple selection tasks. In actual market research, consumers are often less patient when facing multiple selection tasks, and consumers are often heterogeneous, with different consumers having different preferences. If a consumer is always not interested in an attribute in the selection task, such as asking people who don't like apples to choose which fruit they like more from apples and other fruits, it will also reduce consumers' patience and may cause consumers to stop choosing midway, affecting the efficiency of data collection. Summary of the invention
[0004] The embodiments of the present application provide a data collection method and a computer device cluster for improving the efficiency of data collection.
[0005] In a first aspect, an embodiment of the present application provides a data collection method, which can be executed by a terminal device or a server. Taking the method being executed by a terminal device as an example, the method includes: the terminal device can obtain first information, and the first information is used to indicate M parameters selected by a user, and to indicate at least one value of each parameter of the M parameters, the M parameters correspond to an object, and M is a positive integer; the terminal device can determine a questionnaire based on the first information, the questionnaire includes a first set, the first set includes N elements, each of the N elements includes the value of at least one parameter, the at least one parameter belongs to the M parameters, the parameters included in the N elements are the same, and at least one of the same parameters in the N elements has a different value, and N is a positive integer; the terminal device can obtain second information based on the questionnaire to complete data collection of the user, and the second information is used to indicate the element selected by the user from the N elements.
[0006] In the above scheme, the embodiment of the present application can obtain the user's preferences for multiple parameters of an object and multiple values of each parameter through the first information, so the set of questionnaires displayed to the user can be obtained based on the user's preference parameters and / or preference values, so that the questionnaire meets the user's personalized needs, which is conducive to improving the user's patience and thus improving the efficiency of data collection. In addition, the embodiment of the present application can further obtain the user's preferences for multiple parameters of an object and multiple values of each parameter through the questionnaire, so that the collected user data is more targeted, which is conducive to setting more personalized content for the user to improve the user experience.
[0007] In a possible implementation, when the terminal device determines the questionnaire based on the first information, the terminal device can determine that the first parameter among the M parameters is the first parameter in the first set, and determine that the N values of the first parameter are the N values of the first parameter in the first set, and the N values of the first parameter belong to at least one value of the first parameter among the M parameters; the terminal device can determine that the second parameter among the M parameters that meets the first condition is the i-th parameter in the first set, and determine that the N values of the second parameter are the N values of the i-th parameter in the first set, and the N values of the second parameter belong to at least one value of the second parameter among the M parameters, where i is an integer greater than 1.
[0008] The values of the parameters included in the first set in the questionnaire are the preference values of the user's preference parameters, so that the questionnaire meets the personalized needs of the user. In addition, the parameters other than the first parameter in the first set meet the first condition, so the first set that meets different needs can be obtained by setting different first conditions.
[0009] In a possible implementation, the first condition includes: the difference between the first weight and the second weight is less than a first threshold, the first weight is the weight corresponding to any one of the first parameter to the i-1th parameter in the first set, and the second weight is the weight corresponding to the second parameter; the remaining number of occurrences in the questionnaire is greater than a second threshold, the remaining number of occurrences is related to a preset total number of occurrences; and, it is different from the first parameter to the i-1th parameter in the first set. By setting the i-th parameter in the first set to satisfy the first condition, the difference between the weights of different parameters in the first set can be made not too large, so that the probability of the user selecting any one of the N elements in the first set is not too large. And it can also balance the number of occurrences of different parameters in the first set in the questionnaire.
[0010] In a possible implementation, the first condition includes: the remaining number of occurrences in the questionnaire is greater than a second threshold, the remaining number of occurrences is related to a preset total number of occurrences; and the first parameter to the i-1th parameter in the first set are all different. By setting the i-th parameter in the first set to satisfy the first condition, the number of occurrences of different parameters in the first set in the questionnaire can be balanced.
[0011] In one possible implementation, when the terminal device determines that the second parameter among the M parameters that satisfies the first condition is the i-th parameter in the first set, when the number of parameters among the M parameters that satisfy the first condition is greater than 1, the terminal device can determine a parameter from the parameters that satisfy the first condition as the second parameter, wherein the second parameter corresponds to a first distance, the first distance is the minimum value of the distances corresponding to the M parameters, and the first distance is the distance between the second parameter and the first parameter to the i-1-th parameter in the first set.
[0012] By determining at least one parameter from the M parameters whose remaining number of occurrences in the questionnaire is greater than the second threshold, and determining from the at least one parameter a parameter with the smallest distance from all the parameters determined in the first set as the i-th parameter in the first set, not only the number of occurrences of different parameters in the first set in the questionnaire is balanced, but also the difference between the weights of different parameters in the first set will not be too large, so that the probability of the user selecting any one element from the N elements in the first set will not be too large.
[0013] In one possible implementation, the distance between the second parameter and the first parameter to the i-1th parameter in the first set is the minimum value of the difference between the weight of the second parameter and the weight of the first parameter to the i-1th parameter in the first set.
[0014] The distance between any parameter and some parameters in any set is defined as the minimum value of the difference between the weight of any parameter and the weight of some parameters in any set, so that it is possible to determine whether the difference between the weight of any parameter and the weights of all parameters determined in the first set is too large through the distance between any parameter and all parameters determined in the first set.
[0015] In a possible implementation, the questionnaire further includes a second set, the second set being a set determined before the first set is determined, and the first condition includes: the second parameter is included in the second set; and the second parameter is different from the first parameter to the i-1th parameter in the first set. By setting the i-th parameter in the first set to satisfy the first condition, when the number of remaining occurrences of a parameter different from any parameter determined in the first set is insufficient in the questionnaire, a parameter different from any parameter determined in the first set can be determined from the previously determined second set as the i-th parameter in the first set.
[0016] In one possible implementation, when the terminal device determines that the second parameter among the M parameters is the i-th parameter in the first set, when the number of parameters among the M parameters that satisfy the first condition is greater than 1, the terminal device can determine a parameter from the parameters that satisfy the first condition as the second parameter; wherein the second parameter corresponds to a second distance, the M parameters also include a third parameter that satisfies the second condition, the third parameter corresponds to a third distance, the sum of the second distance and the third distance is the smallest, the second distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set, and the third distance is the distance between the third parameter and all parameters in the second set except the second parameter.
[0017] By traversing the previously determined second set, the second parameter in the second set is used as the i-th parameter in the first set. Since the distance from the second parameter to all the parameters determined in the first set is the smallest as is the sum of the distances from the third parameter to all the parameters in the second set except the second parameter, the difference between the weights of different parameters in the first set will not be too large, and thus the probability of the user selecting any one of the N elements in the first set will not be too large.
[0018] In a possible implementation, the second condition includes: the remaining number of occurrences in the questionnaire is greater than a second threshold; and the parameters other than the second parameter in the second set are different. By setting the third parameter to satisfy the second condition, the number of occurrences of different parameters in the second set in the questionnaire can be balanced after the second parameter in the second set is replaced by the third parameter.
[0019] In a possible implementation manner, after the terminal device determines a parameter from the parameters that satisfy the first condition as the second parameter, the terminal device may also replace the second parameter in the second set with the third parameter.
[0020] Since the remaining number of occurrences of the third parameter in the questionnaire is greater than the second threshold, the number of occurrences of different parameters in the second set in the questionnaire can be balanced. And since the sum of the distance from the second parameter to all parameters determined in the first set and the distance from the third parameter to all parameters in the second set except the second parameter is the smallest, the difference between the weights of different parameters in the second set will not be too large, so that the probability of the user selecting any one element from the N elements in the second set will not be too large.
[0021] In one possible implementation, the terminal device may also determine a third set based on the first information; the terminal device may also determine a first loss corresponding to the third set, the first loss being used to indicate the difference between the prior probabilities corresponding to the N values of the fourth parameter in the third set, the fourth parameter being any one parameter in the third set; the terminal device may also perform a first update operation on the N values of the fourth parameter in the third set to obtain the first set, wherein at least one value of the N values of the fourth parameter in the first set is different from that of the N values of the fourth parameter in the third set, the first set corresponds to a second loss, the second loss being used to indicate the difference between the prior probabilities corresponding to the N values of the fourth parameter in the first set, and the second loss being less than the first loss.
[0022] The first set is obtained by replacing any one of the N values of the fourth parameter in the third set with a value different from the value, and the difference between the prior probabilities corresponding to the N values of the fourth parameter in the first set is lower than that of the third set, so that the probability of the user selecting any one of the N elements in the first set is not too large.
[0023] In a possible implementation, when the terminal device performs a first update operation on the N values of the fourth parameter in the third set to obtain the first set, the terminal device may perform a first update operation on the N values of the fourth parameter in the third set to obtain a fourth set; the terminal device may determine a first difference corresponding to the fourth set, the first difference being used to indicate the difference between the utilities corresponding to the N elements in the fourth set, and the utility corresponding to any one of the N elements being used to indicate the sum of prior probabilities corresponding to the values of all parameters included in the any one element; the terminal device may perform a second update operation on the N values of the fifth parameter in the fourth set to obtain the first set, wherein the fifth parameter is any one of the parameters in the fourth set, the value of the fifth parameter of the first element in the first set is the value of the fifth parameter of the second element in the fourth set, the value of the fifth parameter of the second element in the first set is the value of the fifth parameter of the first element in the fourth set, the first set corresponds to a second difference, the second difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, and the second difference is smaller than the first difference.
[0024] The first set is obtained by exchanging the value of the fifth parameter of the first element in the fourth set with the value of the fifth parameter of the second element. The difference between the utilities corresponding to the first element and the second element in the first set is lower than that in the fourth set, so that the probability of the user selecting any one of the N elements in the first set is not too large.
[0025] In a possible implementation, when the terminal device performs a second update operation on the N values of the fifth parameter in the fourth set to obtain the first set, the terminal device may perform a second update operation on the N values of the fifth parameter in the fourth set to obtain the fifth set; the terminal device may determine the number of times the value of the fifth parameter of the first element in the fifth set has appeared in the questionnaire; if the number of times the value of the fifth parameter of the first element in the fifth set is greater than a third threshold, the terminal device may perform a third update operation on the value of the fifth parameter of the first element in the fifth set to obtain the first set; wherein the number of times the value of the fifth parameter of the first element in the first set has appeared in the questionnaire is less than the third threshold, the first set corresponds to a third difference, the third difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, the third difference is less than or equal to the second difference, the first set corresponds to a third loss, the third loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the first set, the fifth set corresponds to a fourth loss, the fourth loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the fifth set, and the difference between the third loss and the fourth loss is less than the fourth threshold.
[0026] By replacing the value of a parameter with a higher frequency of occurrence in the questionnaire with the value of a parameter with a lower frequency of occurrence in the questionnaire, the frequency of occurrence of different values of any parameter in the questionnaire is balanced.
[0027] In the second aspect, the present application also provides a data acquisition device, which can exist alone, or can be set in a terminal device or in a server. The device has the function of implementing the method described in the first aspect or any possible design of the first aspect, and the function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, such as an interface unit, a processing unit, etc., and can also include a storage unit. The interface unit can be a human-computer interaction interface, or a human-computer interaction interface, or an input and output port of a device, etc., which is not limited to the embodiments of the present application. The processing unit can be a processor or a processing chip, etc., which is not limited to the embodiments of the present application. The storage unit can be used to store multiple index libraries, and of course the storage unit can also be set in other devices, such as access network devices, core network devices, etc., which is not limited to the embodiments of the present application.
[0028] An interface unit, used to obtain first information, where the first information is used to indicate M parameters selected by a user and at least one value of each of the M parameters, where the M parameters correspond to one object, and M is a positive integer;
[0029] a processing unit, configured to determine a questionnaire according to the first information, the questionnaire comprising a first set, the first set comprising N elements, each of the N elements comprising a value of at least one parameter, the at least one parameter belonging to the M parameters, the parameters included in the N elements are the same, and at least one of the same parameters in the N elements has a different value, and N is a positive integer;
[0030] The interface unit is used to obtain second information according to the questionnaire to complete the data collection of the user, and the second information is used to indicate the element selected by the user from the N elements.
[0031] In a possible implementation, the processing unit is specifically used to: determine that a first parameter among the M parameters is the first parameter in the first set, and determine that N values of the first parameter are N values of the first parameter in the first set, and the N values of the first parameter belong to at least one value of the first parameter among the M parameters; determine that a second parameter among the M parameters that satisfies the first condition is the i-th parameter in the first set, and determine that the N values of the second parameter are N values of the i-th parameter in the first set, and the N values of the second parameter belong to at least one value of the second parameter among the M parameters, where i is an integer greater than 1.
[0032] In one possible implementation, the first condition includes: the difference between the first weight and the second weight is less than a first threshold, the first weight is the weight corresponding to any one of the first parameter to the i-1th parameter in the first set, and the second weight is the weight corresponding to the second parameter; the remaining number of occurrences in the questionnaire is greater than a second threshold; and, is different from the first parameter to the i-1th parameter in the first set.
[0033] In a possible implementation, the first condition includes: the remaining number of occurrences in the questionnaire is greater than a second threshold; and is different from the first parameter to the i-1th parameter in the first set.
[0034] In a possible implementation, the processing unit is specifically used to: when the number of parameters that satisfy the first condition among the M parameters is greater than 1, determine a parameter from the parameters that satisfy the first condition as the second parameter, wherein the second parameter corresponds to a first distance, the first distance is the minimum value of the distances corresponding to the M parameters, and the first distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set.
[0035] In one possible implementation, the distance between the second parameter and the first parameter to the i-1th parameter in the first set is the minimum value of the difference between the weight of the second parameter and the weight of the first parameter to the i-1th parameter in the first set.
[0036] In one possible implementation, the questionnaire also includes a second set, where the second set is a set determined before the first set is determined, and the first condition includes: the second parameter is included in the second set; and is different from the first to i-1th parameters in the first set.
[0037] In a possible implementation, the processing unit is specifically used to: when the number of parameters that satisfy the first condition in the M parameters is greater than 1, determine a parameter from the parameters that satisfy the first condition as the second parameter; wherein the second parameter corresponds to a second distance, the M parameters also include a third parameter that satisfies the second condition, the third parameter corresponds to a third distance, the sum of the second distance and the third distance is the smallest, the second distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set, and the third distance is the distance between the third parameter and all parameters in the second set except the second parameter.
[0038] In a possible implementation, the second condition includes: the remaining number of occurrences in the questionnaire is greater than a second threshold; and is different from all parameters in the second set except the second parameter.
[0039] In a possible implementation manner, the processing unit is further used to: replace the second parameter in the second set with the third parameter.
[0040] In one possible implementation, the processing unit is further used to: determine a third set based on the first information; determine a first loss corresponding to the third set, the first loss being used to indicate the difference between the prior probabilities corresponding to N values of the fourth parameter in the third set, the fourth parameter being any parameter in the third set; perform a first update operation on the N values of the fourth parameter in the third set to obtain the first set, wherein at least one value of the N values of the fourth parameter in the first set is different from that of the N values of the fourth parameter in the third set, the first set corresponds to a second loss, the second loss being used to indicate the difference between the prior probabilities corresponding to the N values of the fourth parameter in the first set, and the second loss being less than the first loss.
[0041] In a possible implementation, the processing unit is further used to: perform a first update operation on the N values of the fourth parameter in the third set to obtain a fourth set; determine a first difference corresponding to the fourth set, the first difference being used to indicate a difference between utilities corresponding to the N elements in the fourth set, and the utility corresponding to any one of the N elements being used to indicate a sum of prior probabilities corresponding to values of all parameters included in the any one element; perform a second update operation on the N values of the fifth parameter in the fourth set to obtain the first set, wherein the fifth parameter is any one of the parameters in the fourth set, the value of the fifth parameter of the first element in the first set is the value of the fifth parameter of the second element in the fourth set, the value of the fifth parameter of the second element in the first set is the value of the fifth parameter of the first element in the fourth set, the first set corresponds to a second difference, the second difference is used to indicate a difference between utilities corresponding to the N elements in the first set, and the second difference is smaller than the first difference.
[0042] In a possible implementation, the processing unit is further used to: perform a second update operation on the N values of the fifth parameter in the fourth set to obtain a fifth set; determine the number of times the value of the fifth parameter of the first element in the fifth set has appeared in the questionnaire; if the number of times the value of the fifth parameter of the first element in the fifth set has appeared is greater than a third threshold, perform a third update operation on the value of the fifth parameter of the first element in the fifth set to obtain the first set; wherein the number of times the value of the fifth parameter of the first element in the first set has appeared in the questionnaire is less than the third threshold, the first set corresponds to a third difference, the third difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, the third difference is less than or equal to the second difference, the first set corresponds to a third loss, the third loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the first set, the fifth set corresponds to a fourth loss, the fourth loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the fifth set, and the difference between the third loss and the fourth loss is less than the fourth threshold.
[0043] In a third aspect, an embodiment of the present application further provides a computing device cluster, including at least one computing device, and the structure of each computing device includes a processor and a memory. The processor is configured to support a terminal device or a server to execute the method of the first aspect or any possible design of the first aspect. The memory is coupled to the processor, which stores program instructions and data necessary for the communication device. The communication device may also include a communication interface for communicating with other devices.
[0044] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium includes computer program instructions. When the computer program instructions are executed by a computing device cluster, the computing device cluster executes the method of the first aspect or any possible design of the first aspect.
[0045] In a fifth aspect, an embodiment of the present application further provides a computer program product comprising instructions, which, when executed by a computing device cluster, enables the computing device cluster to execute the method of the first aspect or any possible design of the first aspect.
[0046] In a sixth aspect, an embodiment of the present application further provides a chip, which can be coupled to a memory and used to call a computer program stored in the memory to execute the method of the first aspect or any possible design of the first aspect.
[0047] The beneficial effects of the above-mentioned second to sixth aspects and possible designs thereof can refer to the description of the beneficial effects of the method described in the above-mentioned first aspect and any possible design thereof. BRIEF DESCRIPTION OF THE DRAWINGS
[0048] Figure 1 It is a schematic diagram of the principle of the selection-based conjoint analysis method;
[0049] Figure 2 A structural diagram of a data acquisition system provided in an embodiment of the present application;
[0050] Figure 3 A flow chart of a data collection method provided in an embodiment of the present application;
[0051] Figure 4a A schematic diagram of an interface provided in an embodiment of the present application;
[0052] Figure 4b Another interface schematic diagram provided for an embodiment of the present application;
[0053] Figure 4c Another interface schematic diagram provided for an embodiment of the present application;
[0054] Figure 4d Another interface schematic diagram provided for an embodiment of the present application;
[0055] Figure 5 A schematic diagram of the structure of a computing device provided in an embodiment of the present application;
[0056] Figure 6 A schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application;
[0057] Figure 7 A schematic diagram of a connection method between computing device clusters provided in an embodiment of the present application. DETAILED DESCRIPTION
[0058] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.
[0059] Before introducing the specific solutions provided in the embodiments of the present application, some terms in the embodiments of the present application are explained to facilitate understanding by those skilled in the art, and the terms in the present application are not limited.
[0060] (1) In the embodiments of the present application, "multiple" refers to two or more than two. In view of this, in the embodiments of the present application, "multiple" can also be understood as "at least two". "At least one" can be understood as one or more, for example, one, two or more. For example, including at least one means including one, two or more, and there is no restriction on which ones are included. For example, including at least one of A, B and C, then the included ones may be A, B, C, A and B, A and C, B and C, or A, B and C. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / ", unless otherwise specified, generally indicates that the previously and subsequently associated objects are in an "or" relationship.
[0061] Unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of the present application are used to distinguish multiple objects and are not used to limit the order, timing, priority or importance of the multiple objects.
[0062] (2) Value quantification: The value of a product needs to be quantified during the product design stage, product development stage, or before the product is sold to help companies make better product decisions. For example, the value of product 1 can be quantified by the benefits brought by the difference between product 1 and product 2, where product 2 is a product similar to product 1 on the market, i.e. direct quantification; or, the value of product 1 can be quantified by consumers' preferences for the attributes that make up product 1 (e.g., a mobile phone has attributes such as appearance, price, and brand) and the levels of the attributes (e.g., the price attribute has levels of 1,000 yuan, 2,000 yuan, 5,000 yuan, etc.), i.e. indirect quantification.
[0063] (3) Conjoint analysis is a method for indirectly quantifying the value of a product. This method assumes that a product is composed of multiple attributes, and each attribute has multiple levels. Since consumers will comprehensively consider multiple attributes of a product and multiple levels of each attribute in the process of selecting a product, this method can quantify the value of a product by studying the role of multiple attributes of a product and multiple levels of each attribute in consumers’ product selection. That is, this method can collect consumers’ preference data for multiple attributes of a product and multiple levels of each attribute, and quantify the value of the product based on the preference data.
[0064] Conjoint analysis methods include scoring-based conjoint analysis and choice-based conjoint analysis (CBC). Among them, scoring-based conjoint analysis does not quite conform to the purchasing behavior of consumers in real scenarios, so it is rarely used in actual market research. The choice-based conjoint analysis method better simulates the purchasing behavior of consumers in real scenarios through consumers' choices between multiple attributes of the product and multiple levels of each attribute.
[0065] For example, Figure 1 The schematic diagram of the principle of the selection-based joint analysis method is as follows: Figure 1 As shown in the figure, the core is to orthogonally combine multiple attributes of a product with multiple levels of each attribute to generate multiple virtual products. Through orthogonal comparison of multiple virtual products, consumers can choose preferred virtual products to collect consumers' preference data for multiple attributes of the product and multiple levels of each attribute, and quantify the value of the product based on the preference data. The specific steps are as follows:
[0066] Step 1: Determine the attributes and attribute levels of the product. For example, the attributes of the product may be brand and resolution, and the attribute levels may be various specific brands and various specific resolutions.
[0067] Step 2: Construct a virtual product with orthogonal characteristics, that is, the levels of the attributes that constitute the virtual product have orthogonal characteristics. For example, if a product has 5 attributes and each attribute has 4 levels, when a full factorial experimental design is used, there should be 4×4×4×4×4=1024 virtual products, which far exceeds the rational judgment range of consumers. Therefore, the joint analysis method based on selection adopts an orthogonal experimental design and selects orthogonal locals to represent the whole, thereby reducing the number of virtual products.
[0068] Step 3: Randomly select at least two virtual products from the constructed multiple virtual products to generate a selection task, and the number of selection tasks generated in the end is not less than the number of attribute levels. For example, two virtual products are selected to generate a selection task and displayed to consumers. One virtual product is brand A, priced at 1,000 yuan, and has a low resolution, and the other virtual product is brand B, priced at 3,000 yuan, and has a high resolution. Consumers can choose which virtual product they like more.
[0069] Step 4: Consumers select their preferred virtual products from all selection tasks in turn.
[0070] Step 5: Analyze the data collected in step 4 and quantify the value of the product.
[0071] However, the above steps 1-3 need to meet two assumptions when generating selection tasks: Assumption 1: Consumers are homogeneous, that is, each consumer needs to complete the same multiple selection tasks; Assumption 2: Consumers have very good patience and are willing to complete multiple selection tasks. In actual market research, consumers are often less patient when facing multiple selection tasks, and consumers are often heterogeneous, with different consumers having different preferences. If a certain attribute that a consumer is not interested in always appears in the selection task, such as asking people who don't like apples to choose which fruit they like more from apples and other fruits, it will also reduce consumers' patience and may cause consumers to stop choosing midway, affecting the efficiency of data collection and the subsequent value quantification process.
[0072] In view of the problem of low efficiency of data collection described in the above content, an embodiment of the present application provides a data collection method. The method can be applied to collect user preference data for multiple parameters (i.e., the above-mentioned attributes) of an object (i.e., the above-mentioned product) and multiple values of each parameter (i.e., the above-mentioned levels), so as to quantify the value of the object based on the preference data. The method can be applied to a data collection system, which may include one or more terminal devices and / or one or more servers. Of course, in addition to terminal devices and servers, the data collection system provided in the embodiment of the present application may also include other devices, such as access network devices, core network devices, etc., which are not limited to the embodiment of the present application. And, any device in the embodiment of the present application may integrate functions into an independent physical unit, or distribute functions over multiple independent physical units, which are not limited to the embodiment of the present application.
[0073] For example, Figure 2 A structural diagram of a data acquisition system provided in an embodiment of the present application. Figure 2A schematic diagram of a terminal device and a server is given, which are terminal device 100 and server 200 respectively. However, in actual applications, the number of terminal devices and / or servers included in the system is not limited thereto.
[0074] In a possible implementation, after obtaining the first information, the terminal device 100 may determine a questionnaire according to the first information, and obtain the second information according to the questionnaire to complete the data collection of the user.
[0075] In another possible implementation, after acquiring the first information, the terminal device 100 may send the first information to the server 200. The server 200 may determine a questionnaire based on the first information and send the questionnaire to the terminal device 100. The terminal device 100 may acquire second information based on the questionnaire and send the second information to the server 200 to complete the data collection of the user.
[0076] It is understandable that the terminal device 100 may be a device equipped with a display screen and capable of human-computer interaction through the display screen. For example, the terminal device 100 may be a mobile phone, a tablet computer, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a wearable device, etc. The embodiment of the present application does not impose any restrictions on the specific type of the terminal device 100.
[0077] The server 200 may refer to a single server or a server cluster composed of multiple servers. The server 200 may specifically be a cloud server, also known as a cloud, cloud, cloud server or cloud controller. A cloud server is a general term for devices or components with data processing capabilities, such as physical devices such as hosts or processors, virtual devices such as virtual machines or containers, and chips or integrated circuits.
[0078] The information interaction between the terminal device 100 and the server 200 may refer to direct interaction between the terminal device 100 and the server 200 via a wired or wireless manner, or may refer to indirect interaction between the terminal device 100 and the server 200 via one or more other devices, which is not limited to this embodiment of the present application.
[0079] The above content describes the possible application scenarios and applicable system architecture of the data collection method provided in the embodiment of the present application. Figure 2The structure of the data acquisition system shown further introduces the data acquisition method provided in the embodiment of the present application.
[0080] For example, Figure 3 A flow chart of a data collection method provided in an embodiment of the present application, which can be applied to Figure 2 As shown or with Figure 2 The data acquisition system with similar functional structure is not specifically limited in the present application embodiment. The specific process of the data acquisition method is described as follows. Figure 2 For example, the terminal device described below may be Figure 2 The terminal device 100 in the system shown in the figure, the server described below may be Figure 2 The server 200 in the system shown. In the embodiment of the present application, the data acquisition system is taken as an example to introduce the execution subject of the method, or the execution subject of the method can also be other devices or systems, such as a chip, chip system or processor applied to the data acquisition system.
[0081] S301. Obtain first information.
[0082] In an embodiment of the present application, the first information can be used to indicate M parameters selected by the user, and to indicate at least one value of each of the M parameters, where the M parameters correspond to one object, and M is a positive integer.
[0083] The M parameters may include at least one target parameter selected by a user from at least one candidate parameter of an object. The at least one value of each parameter in the M parameters may include at least one target value selected by a user from at least one candidate value of each target parameter in the at least one target parameter.
[0084] The object may be a salable product or service, such as a mobile phone, a television, etc.; the parameters of the object may be the parameters that constitute the object, such as a mobile phone having parameters such as brand, price, and appearance; the value of the parameter may be various specific parameters, such as a price having values such as 1,000 yuan, 2,000 yuan, or 3,000 yuan.
[0085] In a specific implementation, the terminal device can display the following on the display screen: Figure 4aAn interface shown in the figure may display at least one candidate parameter of a vehicle display screen, such as display screen type, material, blue light certification, sound playback mode, interaction mode, content source, resolution and other parameters, as well as text prompting the user to select at least one target parameter from the at least one candidate parameter of the vehicle display screen, such as "Please select the parameter you think is relatively important from the following parameters". The user can select the display screen type, blue light certification and sound playback mode from the display screen type, material, blue light certification, sound playback mode, interaction mode, content source and resolution.
[0086] When the terminal device detects the user's operation of selecting the display type, blue light authentication and sound playing mode, in response to the operation, the terminal device can display the following information on the display screen: Figure 4b An interface is shown, in which at least one candidate value of display screen type, blue-ray certification and sound playing mode can be displayed, such as display screen type: type 1, type 2, type 3; blue-ray certification: with blue-ray certification, without blue-ray certification; sound playing mode: player play, headphone play, player play and headphone play, and text prompting the user to select at least one target value from at least one candidate value, such as "Please select the value of the parameter that you think is relatively important among the following parameter values". The user can select type 1 and type 3 from type 1, type 2 and type 3.
[0087] In a possible implementation, when the terminal device displays at least one candidate value of a target parameter on a display screen, the terminal device may determine whether to display the at least one candidate value of the target parameter based on the relationship of the at least one candidate value of the target parameter. The relationship of the at least one candidate value of the target parameter includes a parallel relationship, a mutually exclusive relationship, and an inclusive relationship.
[0088] For example, three candidate values of display screen types (such as type 1, type 2, and type 3) are in a parallel relationship, and the user can select at least one target value from these three candidate values. Therefore, the terminal device can display these three candidate values on the display screen for the user to select.
[0089] For example, the two candidate values of blue light authentication (such as blue light authentication and no blue light authentication) are mutually exclusive, and the user can only select one target value from these two candidate values. Therefore, the terminal device may not display these two candidate values on the display screen for the user to choose, but directly use these two candidate values as target values.
[0090] For another example, the three candidate values for playing sound (such as player play, headphone play, player play and headphone play) are in an inclusion relationship, player and headphone play are parent candidate values, player play and headphone play are child candidate values, and the user selects the parent candidate value as the target value, which is equivalent to selecting all the child candidate values of the parent candidate value as the target values. Therefore, the terminal device can display the child candidate values among the three candidate values on the display screen for the user to select, but does not display the parent candidate value among the three candidate values on the display screen for the user to select, but directly uses the parent candidate value among the three candidate values as the target value.
[0091] In another possible implementation, before the terminal device displays at least one candidate value of a target parameter on the display screen, the prior probability of each candidate value of the at least one candidate value of the target parameter can be determined by a preliminary experiment. The prior probability of the first candidate value of the target parameter indicates the probability of the user selecting the first candidate value from the at least one candidate value of the target parameter. For example, a brand has three parameters, namely brand 1, brand 2 and brand 3. When brand 1 is used as the benchmark, the prior probability of brand 1 is 0, the prior probability of brand 2 is 0.1, and the prior probability of brand 3 is 0.2.
[0092] After the user determines at least one target value from at least one candidate value of the target parameter, that is, after the terminal device obtains at least one target value of the target parameter, the terminal device can update the prior probability of each target value in the at least one target value of the target parameter. The prior probability of the first target value of the target parameter indicates the probability of the user selecting the first target value from the at least one target value of the target parameter. For example, after the user selects Brand 2 and Brand 3 from Brand 1, Brand 2 and Brand 3, the prior probabilities of Brand 2 and Brand 3 are updated. When Brand 2 is used as the benchmark, the prior probability of Brand 2 is updated to 0, and the prior probability of Brand 3 is updated to 0.1.
[0093] S302: Determine a questionnaire based on the first information.
[0094] In an embodiment of the present application, a questionnaire may include a first set. The first set includes N elements, each of the N elements includes the value of at least one parameter, at least one parameter belongs to the M parameters indicated by the first information obtained in S302, the parameters included in the N elements are the same, and the values of at least one of the same parameters in the N elements are different, and N is a positive integer. A questionnaire is a way to display the first set. The present application can display the first set to the user through a questionnaire to determine the preferred elements selected by the user from different elements in the first set. Of course, the present application can also display the first set in other ways, and the embodiment of the present application does not impose specific restrictions on this.
[0095] For example, the questionnaire includes set 1, set 1 includes element 1 and element 2, and the relationship between element 1 and element 2 in set 1 can be shown in Table 1.
[0096] Collection 1 Element 1 Element 2 brand Brand 1 Brand 2 price 6000 NTD 5000 NTD Resolution High resolution Low resolution
[0097] Table 1
[0098] In a specific implementation, after the terminal device obtains the first information, the terminal device may determine the questionnaire according to the first information. Alternatively, after the terminal device obtains the first information, the terminal device may also send the first information to the server, and the server may determine the questionnaire according to the first information and send the questionnaire to the terminal device. The embodiment of the present application does not impose specific restrictions on this. For the convenience of explanation, the present application takes the example of a terminal device determining the questionnaire according to the first information.
[0099] In a possible implementation, the number of sets in the questionnaire may be one or more. Specifically, the terminal device may determine the number of sets in the questionnaire according to the number of parameters indicated by the first information and the number of parameter values. For example, the first information indicates 4 parameters (i.e., M is 4), namely parameter 1, parameter 2, parameter 3, and parameter 4, parameter 1 has 2 values, parameter 2 has 3 values, parameter 3 has 4 values, and parameter 4 has 4 values, then the number of sets in the questionnaire is 2+3+4+4-4+5=14.
[0100] In another possible implementation, when there are multiple sets in the questionnaire, the terminal device may determine the multiple sets at one time according to the first information, and then display the multiple sets in sequence through the display screen to collect the user's preference data for different elements in each of the multiple sets; or, the terminal device may determine a set according to the first information, and then display the set in sequence through the display screen to collect the user's preference data for different elements in the one set, and then determine another set according to the first information, and display the another set in sequence through the display screen to collect the user's preference data for different elements in the another set, wherein the latter set may be related to or unrelated to the user's preference data for different elements in the previous set. The embodiments of the present application do not impose specific restrictions on this. For ease of explanation, the present application takes the example of a terminal device determining multiple sets at one time according to the first information.
[0101] Exemplarily, the terminal device may perform the following steps A1-A2 to determine the first set:
[0102] Step A1: Determine that a first parameter among M parameters is the first parameter in a first set, and determine that N values of the first parameter are the N values of the first parameter in the first set, and the N values of the first parameter belong to at least one value of the first parameter among the M parameters.
[0103] Specifically, the terminal device may perform unequal probability sampling on M parameters to obtain the first parameter, and perform unequal probability sampling on at least one value of the first parameter to obtain N values of the first parameter.
[0104] Among them, the sampling probability of any one of the M parameters is positively correlated with the remaining number of occurrences of the parameter in the questionnaire, the sampling probability of any value of the parameter is positively correlated with twice the remaining number of occurrences of the parameter in the questionnaire, the remaining number of occurrences of the parameter in the questionnaire is the total number of occurrences of the parameter in the questionnaire minus the number of occurrences of the parameter in the questionnaire, and the total number of occurrences of the parameter in the questionnaire is negatively correlated with the number of values of the parameter.
[0105] For example, the first information indicates 4 parameters (i.e., M is 4), namely parameter 1, parameter 2, parameter 3 and parameter 4, and parameter 1 has 3 values, namely value 1, value 2 and value 3. Parameter 1, parameter 2, parameter 3 and parameter 4 are sampled with unequal probability to obtain the first parameter in the first set. Among them, the sampling probability of parameter 1 Q1∝(T1-T2), ∝ is the symbol of positive proportion, T1 is the total number of times parameter 1 appears in the questionnaire, T1∝(1 / 2), and T2 is the number of times parameter 1 has appeared in the questionnaire. When the values of parameter 1 are sampled with unequal probability to obtain N values of the first parameter, the sampling probability of value 1 Q2∝(2*T1).
[0106] Step A2: Determine that the second parameter among the M parameters is the i-th parameter in the first set, and determine that the N values of the second parameter are the N values of the i-th parameter in the first set, the second parameter satisfies the first condition, the N values of the second parameter belong to at least one value of the second parameter among the M parameters, and i is an integer greater than 1.
[0107] Specifically, the terminal device may determine the second parameter through three solutions according to the three first conditions. The specific implementation of the three solutions is described in detail below in conjunction with specific examples:
[0108] Solution 1: Determine any parameter among the M parameters that meets the first condition in the first possible implementation as the second parameter.
[0109] In a first possible implementation, the first condition may include: the difference between the first weight and the second weight is less than a first threshold, the first weight is the weight corresponding to any one of the first parameter to the i-1th parameter in the first set, and the second weight is the weight corresponding to the second parameter; the remaining number of occurrences in the questionnaire is greater than the second threshold; and, it is different from the first parameter to the i-1th parameter in the first set.
[0110] The weight of a parameter may be the difference between the first prior probability of the parameter and the second prior probability of the parameter. The first prior probability of the parameter is the prior probability of the value with the largest prior probability among the values of the parameter, and the second prior probability of the parameter is the prior probability of the value with the smallest prior probability among the values of the parameter. For example, a brand has four parameters, namely brand 1, brand 2, and brand 3. When brand 1 is used as the benchmark, the prior probability of brand 1 is 0, the prior probability of brand 2 is 0.1, and the prior probability of brand 3 is 0.2. Therefore, the weight of the brand is the difference between the prior probability of brand 3 and the prior probability of brand 1, which is 0.2.
[0111] For example, the first information indicates 4 parameters (i.e., M is 4), namely parameter 1, parameter 2, parameter 3 and parameter 4, parameter 1 has 2 values, parameter 2 has 3 values, parameter 3 has 4 values, and parameter 4 has 4 values. After determining that parameter 1 is the first parameter of the first set, if the difference between the weights of parameter 2, parameter 3 and parameter 4 and the weight of parameter 1 is less than the first threshold, the remaining number of occurrences of parameter 2 and parameter 3 in the questionnaire is greater than the second threshold, and the remaining number of occurrences of parameter 4 in the questionnaire is less than or equal to the second threshold, it can be determined that parameter 2 and parameter 3 both meet the first condition in the first possible implementation mode, and parameter 4 does not meet the first condition in the first possible implementation mode. Therefore, unequal probability sampling can be performed on parameter 2 and parameter 3 to obtain the second parameter of the first set. Among them, the sampling probability of parameter 2 is Q3∝(T3-T4), T3 is the total number of occurrences of parameter 2 in the questionnaire, T3∝(1 / 3), and T4 is the number of occurrences of parameter 2 in the questionnaire. The sampling probability of parameter 3 is Q4∝(T5-T6), where T5 is the total number of times parameter 3 appears in the questionnaire, and T5∝(1 / 4), where T6 is the number of times parameter 3 has appeared in the questionnaire.
[0112] Solution 2: When the number of parameters satisfying the first condition in the second possible implementation manner among the M parameters is greater than 1, one parameter is determined as the second parameter from the parameters satisfying the first condition.
[0113] In a second possible implementation, the first condition may include: the remaining number of occurrences in the questionnaire is greater than a second threshold; and is different from the first parameter to the i-1th parameter in the first set.
[0114] Wherein, the second parameter corresponds to the first distance (also called the first rank distance). The first distance is the minimum value among the distances corresponding to the M parameters. The first distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set. The distance between the second parameter and the first parameter to the i-1th parameter in the first set is the minimum value among the differences between the weight of the second parameter and the weight of the first parameter to the i-1th parameter in the first set.
[0115] For example, the first information indicates five parameters (i.e., M is 5), namely, parameter 1, parameter 2, parameter 3, parameter 4, and parameter 5. After determining parameter 1 as the first parameter of the first set, and determining parameter 2 as the second parameter of the first set, if the difference between the weights of parameter 3, parameter 4, and parameter 5 and the weight of parameter 1 is greater than or equal to the first threshold, and the difference between the weights of parameter 3, parameter 4, and parameter 5 and the weight of parameter 2 is also greater than or equal to the first threshold, the remaining number of occurrences of parameter 3 and parameter 4 in the questionnaire is greater than the second threshold, and the remaining number of occurrences of parameter 5 in the questionnaire is less than or equal to the second threshold, then it can be determined that parameter 3, parameter 4, and parameter 5 do not meet the first condition in the first possible implementation mode, parameter 3 and parameter 4 meet the first condition in the second possible implementation mode, and parameter 5 does not meet the first condition in the second possible implementation mode.
[0116] Therefore, the first distance d1 corresponding to parameter 3 and the first distance d2 corresponding to parameter 4 can be determined. Among them, d1 is the minimum value of r1 and r2, r1 is the difference between the weight of parameter 3 and the weight of parameter 1, and r2 is the difference between the weight of parameter 3 and the weight of parameter 2. d2 is the minimum value of r3 and r4, r3 is the difference between the weight of parameter 4 and the weight of parameter 1, and r4 is the difference between the weight of parameter 4 and the weight of parameter 2. If d1 is less than d2, it can be determined that parameter 3 is the third parameter of the first set.
[0117] Solution three: when the number of parameters satisfying the first condition in the third possible implementation manner among the M parameters is greater than 1, a parameter satisfying the first condition is determined as the second parameter.
[0118] In a third possible implementation, if there are multiple sets in the questionnaire, the questionnaire may further include a second set. The second set is a set determined before the first set is determined, and the second set includes N elements, each of the N elements includes the value of at least one parameter, at least one parameter belongs to the M parameters obtained in S302, the parameters included in the N elements are the same, and at least one of the same parameters in the N elements has a different value. The first condition may include: the second parameter is included in the second set; and, it is different from the first parameter to the i-1th parameter in the first set.
[0119] Among them, the second parameter corresponds to the second distance, the M parameters also include a third parameter that meets the second condition, the third parameter corresponds to the third distance, the sum of the second distance and the third distance is the smallest, the second distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set, and the third distance is the distance between the third parameter and all parameters in the second set except the second parameter. The second condition includes: the remaining number of occurrences in the questionnaire is greater than the second threshold; and, it is different from all parameters in the second set except the second parameter.
[0120] Optionally, after determining a parameter as the second parameter from the parameters satisfying the first condition in the third possible implementation manner, the second parameter in the second set may be replaced by the third parameter.
[0121] For example, the first information indicates 5 parameters (i.e., M is 5), namely parameter 1, parameter 2, parameter 3, parameter 4, and parameter 5. After determining parameter 1 as the first parameter of the first set, and determining parameter 2 as the second parameter of the first set, if the difference between the weights of parameter 3, parameter 4, and parameter 5 and the weight of parameter 1 is greater than or equal to the first threshold, and the difference between the weights of parameter 3, parameter 4, and parameter 5 and the weight of parameter 2 is also greater than or equal to the first threshold, and the remaining number of occurrences of parameter 3, parameter 4, and parameter 5 in the questionnaire is less than or equal to the second threshold, it can be determined that parameter 3, parameter 4, and parameter 5 do not meet the first condition of the first and second possible implementations described above.
[0122] If the second set includes three parameters, namely parameter 1, parameter 3 and parameter 4, it can be determined that parameter 3 and parameter 4 both meet the first condition in the third possible implementation. If the remaining number of occurrences of parameter 2 in the questionnaire is greater than the second threshold, it can be determined that parameter 2 meets the second condition.
[0123] Therefore, the first distance d1 corresponding to parameter 3, the first distance d2 corresponding to parameter 4, the second distance d3 corresponding to parameter 2 (the second parameter in the second set: parameter 3), and the second distance d4 (the second parameter in the second set: parameter 4) can be determined. Among them, d1 is the minimum value of r1 and r2, r1 is the difference between the weight of parameter 3 and the weight of parameter 1, and r2 is the difference between the weight of parameter 3 and the weight of parameter 2. d2 is the minimum value of r3 and r4, r3 is the difference between the weight of parameter 4 and the weight of parameter 1, and r4 is the difference between the weight of parameter 4 and the weight of parameter 2. d3 is the minimum value of r5 and r6, r5 is the difference between the weight of parameter 2 and the weight of parameter 1, and r4 is the difference between the weight of parameter 2 and the weight of parameter 3. d4 is the minimum value of r5 and r7, and r7 is the difference between the weight of parameter 2 and the weight of parameter 4. If d1+d3 is less than d2+d4, it can be determined that parameter 3 is the third parameter of the first set, and parameter 2 is parameter 3 of the first set, that is, the first set includes parameter 1, parameter 2 and parameter 3, and the second set includes parameter 1, parameter 2 and parameter 4.
[0124] The above scheme uses unequal probability sampling to balance the number of times different parameters appear in multiple sets that users need to choose from, and by limiting the difference between the weights of different parameters of an element, when users select preferred elements from multiple sets, there will be no invalid sets where the difference between the weights of different parameters of an element is too large, thereby improving the efficiency of collecting user preference data for different elements in multiple sets.
[0125] In one possible implementation, after the terminal device determines the first set, the difference between the prior probabilities of different values of any parameter in the first set may be too large. For example, one parameter of the first element and the second element in set 1 is price, and the price value of the first element is 1,000 yuan (the prior probability is 0.7), while the price value of the second element is 10,000 yuan (the prior probability is 0.1). The probability that the user prefers the first element over the first element and the second element in set 1 is too large, resulting in low efficiency in collecting the user's preference data for the first element and the second element in set 1. Therefore, the terminal device can also perform the following steps B1-B3 to optimize the first set determined by the above steps A1-A2 to reduce the difference between the prior probabilities of different values of any parameter corresponding to the first set:
[0126] Step B1: Determine the third set according to the first information.
[0127] For step B1, please refer to the introduction of steps A1-A2 above, which will not be repeated here.
[0128] Step B2: Determine the first loss corresponding to the third set.
[0129] Among them, the first loss is used to indicate the difference between the prior probabilities corresponding to N values of the fourth parameter in the third set, the prior probability corresponding to any one of the N values is used to indicate the probability of the user selecting any one value from at least one value of the fourth parameter, and k is a positive integer.
[0130] For example, set 1 includes 3 parameters, namely parameter 1, parameter 2 and parameter 3. The prior probability of parameter 1 value 1 is 0.1, the prior probability of parameter 1 value 2 is 0.4, and the difference between the prior probabilities of the two values is 0.3, that is, the first loss corresponding to set 1 is 0.3.
[0131] Step B3: Perform a first update operation on the N values of the fourth parameter in the third set to obtain a first set.
[0132] Among them, at least one value of the N values of the fourth parameter in the first set is different from the N values of the fourth parameter in the third set, the first set corresponds to a second loss, the second loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fourth parameter in the first set, and the second loss is less than the first loss.
[0133] Optionally, the N values of the fourth parameter in the first set are N values with the smallest second loss corresponding to at least one value of the fourth parameter.
[0134] For example, the values of parameter 1 include value 1, value 2, value 3, value 4, and value 5. Traverse the values of parameter 1, and select two different values from value 3 (prior probability 0.2), value 4 (prior probability 0.4), and value 5 (prior probability 0.5) as the two values of parameter 1 in set 2. When value 3 and value 4 are selected as the two values of parameter 1 in set 2, the second loss corresponding to set 2 is 0.2 (less than the first loss 0.3 corresponding to set 1); when value 3 and value 5 are selected as the two values of parameter 1 in set 2, the second loss corresponding to set 2 is 0.3 (equal to the first loss 0.3 corresponding to set 1); when value 4 and value 5 are selected as the two values of parameter 1 in set 2, the second loss corresponding to set 2 is 0.1 (less than the first loss 0.3 corresponding to set 1). Therefore, value 4 and value 5 can be selected as the two values of parameter 1 in set 2, which not only makes the second loss corresponding to set 2 less than the first loss corresponding to set 1, but also minimizes the second loss corresponding to set 2.
[0135] In another possible implementation, after the terminal device executes the above steps B1-B3 to optimize the first set determined by the above steps A1-A2, the difference in the sum of the prior probabilities corresponding to the values of all parameters of different elements of the first set may be too large. For example, the sum of the prior probabilities corresponding to the values of all parameters of the first element in set 1 is 0.8, and the sum of the prior probabilities corresponding to the values of all parameters of the first element in set 1 is 0.2. The probability that the user prefers the first element over the first element and the second element in set 1 is too large, resulting in low efficiency in collecting the user's preference data for the first element and the second element in set 1. Therefore, the terminal device may also execute the following steps C1-C3 to optimize the first set determined by the above steps B1-B3 to reduce the difference in the sum of the prior probabilities corresponding to the values of all parameters of different elements in the first set:
[0136] Step C1: performing a first update operation on N values of the fourth parameter in the third set to obtain a fourth set;
[0137] The step C1 can refer to the introduction of the above step B3, which will not be repeated here.
[0138] Step C2: Determine the first difference value corresponding to the fourth set.
[0139] The first difference is used to indicate the difference between the utilities corresponding to the N elements in the fourth set, and the utility corresponding to any one of the N elements is used to indicate the sum of the prior probabilities corresponding to the values of all parameters included in any one element.
[0140] For example, set 1 includes element 1 and element 2. Element 1 includes value 1 (prior probability is 0.1) of parameter 1, value 2 (prior probability is 0.2) of parameter 2, and value 3 (prior probability is 0.3) of parameter 3. Element 2 includes value 4 (prior probability is 0.2) of parameter 1, value 5 (prior probability is 0.1) of parameter 2, and value 6 (prior probability is 0.1) of parameter 3. The utility corresponding to element 1 is the sum of the prior probabilities of value 1, value 2, and value 3, which is 0.6. The utility corresponding to element 2 is the sum of the prior probabilities of value 4, value 5, and value 6, which is 0.4. Therefore, the first difference corresponding to set 1 is 0.2.
[0141] Step C3: Perform a second update operation on the N values of the fifth parameter in the fourth set to obtain a first set.
[0142] Among them, the fifth parameter is any parameter in the fourth set, the value of the fifth parameter of the first element in the first set is the value of the fifth parameter of the second element in the fourth set, the value of the fifth parameter of the second element in the first set is the value of the fifth parameter of the first element in the fourth set, the first set corresponds to the second difference, the second difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, and the second difference is smaller than the first difference.
[0143] For example, the value 2 of parameter 2 of element 1 in set 1 described in step C2 above is interacted with the value 5 of parameter 2 of element 2 in set 1 to obtain set 2, that is, the value of parameter 2 of element 1 in set 1 is 5, and the value of parameter 2 of element 2 in set 2 is 2. The utility corresponding to element 1 in set 2 is the sum of the prior probabilities of value 1, value 5 and value 3, which is 0.5, and the utility corresponding to element 2 in set 2 is the sum of the prior probabilities of value 4, value 2 and value 6, which is 0.5. Therefore, the second difference corresponding to set 2 is 0, which is less than the first difference corresponding to set 1, 0.2.
[0144] In another possible implementation, after the terminal device executes the above steps C1-C3 to optimize the first set determined by the above steps B1-B3, the number of times different values of any parameter in the first set appear in the questionnaire may not be balanced. For example, the value 1 of parameter 1 appears 8 times in the questionnaire, while the value 2 of parameter 2 appears only once in the questionnaire. Therefore, the terminal device may also execute the following steps D1-D3 to optimize the first set determined by the above steps C1-C3, so that the number of times different values of any parameter in the first set appear in the questionnaire is balanced:
[0145] Step D1: Perform a second update operation on the N values of the fifth parameter in the fourth set to obtain a fifth set.
[0146] The step D1 can refer to the introduction of the above step C3, which will not be repeated here.
[0147] Step D2: Determine the number of times the value of the fifth parameter of the first element in the fifth set has appeared in the questionnaire.
[0148] Step D3: If the number of occurrences is greater than the third threshold, a third update operation is performed on the value of the fifth parameter of the first element in the fifth set to obtain the first set.
[0149] Among them, the value of the fifth parameter of the first element in the first set has appeared the number of times in the questionnaire is less than the third threshold value, the first set corresponds to the third difference, the third difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, the third difference is less than or equal to the second difference, the first set corresponds to the third loss, the third loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the first set, the fifth set corresponds to the fourth loss, the fourth loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the fifth set, and the difference between the third loss and the fourth loss is less than the fourth threshold value.
[0150] For example, if the values 2, 5, and 8 (with a prior probability of 0.2) of parameter 2 appear 3, 2, and 1 times in the questionnaire, respectively, then the fourth threshold value can be determined as the mean value 2 of 3, 2, and 1, and the value of parameter 2 of element 2 in set 2 described in step C3 is replaced from value 2 to value 8 to obtain set 3, that is, the value of parameter 2 of element 1 in set 3 is value 5, and the value of parameter 2 of element 2 in set 3 is value 8. The utility corresponding to element 1 in set 3 is the sum of the prior probabilities of value 1, value 5, and value 3, which is 0.5, and the utility corresponding to element 2 in set 3 is the sum of the prior probabilities of value 4, value 8, and value 6, which is 0.5. Therefore, the second difference corresponding to set 3 is 0, which is equal to the second difference corresponding to set 2, which is 0, the third loss corresponding to set 3 is 0.1, and the fourth loss corresponding to set 2 is 0.1. The difference between the third loss and the fourth loss is 0, which is less than the fourth threshold value 0.2.
[0151] S303: Obtain second information according to the questionnaire to complete data collection on the user.
[0152] In the embodiment of the present application, the second information is used to indicate the element selected by the user from the N elements in the first set. For example, set 1 includes element 1 and element 2, and in set 1, the user prefers element 1.
[0153] In a specific implementation, if the number of sets in the questionnaire determined in S303 is multiple, the terminal device may display the following on the display screen: Figure 4c An interface as shown in (1) may display a set 1. Set 1 includes two elements. For example, the values of the three parameters of brand, price, and resolution included in element 1 are brand 1, 3,000 yuan, and low resolution, respectively; the values of the three parameters of brand, price, and resolution included in element 2 are brand 2, 5,000 yuan, and high resolution, respectively. That is, the values of the same parameters in element 1 and element 2 are different. And the text for the user to select an element from the two elements in set 1, such as "Please select the element that you think is relatively important from the following elements." The user can select element 1 from element 1 and element 2. That is, the user prefers brand 1, 3,000 yuan, and low resolution.
[0154] When the terminal device detects the user's operation of selecting element 1, in response to the operation, the terminal device may display the following on the display screen: Figure 4c An interface as shown in (2) of FIG. 1 may display a set 2 in the interface. Set 2 includes two elements. For example, the values of the four parameters of brand, price, resolution, and display screen material included in element 3 are brand 1, RMB 3,000, low resolution, and material 1, respectively; the values of the four parameters of brand, price, resolution, blue light certification, and display screen material included in element 4 are brand 2, RMB 5,000, high resolution, and material 2, respectively. That is, the values of the same parameters in element 3 and element 4 are different, and element 3 has one more parameter value than element 1: material 1, and element 4 has one more parameter value than element 2: material 2, and text indicating that the user selects one element from the two elements of set 2, such as "Please select the element that you think is relatively important from the following elements". The user can select element 4 from elements 3 and 4. That is, the user prefers brand 2, RMB 5,000, high resolution, and material 2.
[0155] Alternatively, the terminal device may display the following on the display: Figure 4d An interface as shown in (1) may display a set 1. Set 1 includes two elements. For example, the values of the two parameters of brand and price included in element 1 are brand 1 and 4,000 yuan respectively, and the values of the two parameters of brand and price included in element 2 are brand 2 and 4,000 yuan respectively. That is, only one parameter in element 1 and element 2 has a different value. And text for the user to select an element from the two elements in set 1, such as "Please select the element that you think is relatively important from the following elements". The user can select element 2 from element 1 and element 2. That is, the user prefers brand 2.
[0156] When the terminal device detects the user's operation of selecting element 2, in response to the operation, the terminal device may display the following on the display screen: Figure 4d An interface as shown in (2) may display a set 2. Set 2 includes two elements. For example, the values of the two parameters of brand, price and display screen material included in element 3 are brand 2 and material 1 respectively, and the values of the two parameters of brand and display screen material included in element 4 are brand 2 and material 2 respectively. That is, only one of the same parameters in element 3 and element 4 has a different value, and the number of parameter values included in element 3 and element 4 is the same as the number of parameter values included in element 1 and element 2. And text for the user to select an element from the two elements of set 2, such as "Please select the element that you think is relatively important among the following elements". The user can select element 3 from element 3 and element 4. That is, the user prefers material 1.
[0157] The above scheme can obtain the user's preferences for multiple parameters of an object and multiple values of each parameter through the first information, so the set of questionnaires displayed to the user can be obtained based on the user's preferred parameters and / or preferred values, so that the questionnaire meets the user's personalized needs, which is conducive to improving the user's patience and thus improving the efficiency of data collection. In addition, the user's preferences for multiple parameters of an object and multiple values of each parameter can be further obtained through the questionnaire, so that the collected user data is more targeted, which is conducive to setting more personalized content for the user to improve the user experience.
[0158] Based on the above embodiments, the present application also provides a computing device, such as Figure 5 As shown, it is a schematic diagram of the structure of a computing device provided in an embodiment of the present application, and the computing device 500 includes: a bus 502, a processor 504, a memory 506, and a communication interface 508. The processor 504, the memory 506, and the communication interface 508 communicate with each other through the bus 502. The computing device 500 can be a terminal device or a server. It should be understood that the present application does not limit the number of processors and memories in the computing device 500.
[0159] The bus 502 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 The bus 502 is represented by only one line, but it does not mean that there is only one bus or one type of bus. The bus 502 may include a path for transmitting information between various components of the computing device 500 (eg, the memory 506, the processor 504, and the communication interface 508).
[0160] The processor 504 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).
[0161] The memory 506 may include a volatile memory, such as a random access memory (RAM). The memory 506 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).
[0162] The memory 506 stores executable program codes, and the processor 504 executes the executable program codes to respectively implement the functions of the communication module and the processing module, thereby implementing the data acquisition method in the above method embodiment. That is, the memory 506 stores instructions for executing the data acquisition method in the above method embodiment.
[0163] The communication interface 508 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 500 and other devices or a communication network.
[0164] Based on the above embodiments, the embodiments of the present application further provide a computing device cluster. The computing device cluster includes at least one computing device. The computing device may be an electronic device.
[0165] like Figure 6 As shown, the computing device cluster includes at least one computing device 500. The memory 506 in one or more computing devices 500 in the computing device cluster may store the same instructions for executing the data collection method in the above method embodiment.
[0166] In some possible implementations, the memory 506 of one or more computing devices 500 in the computing device cluster may also store partial instructions for executing the data collection method in the above method embodiment. In other words, the combination of one or more computing devices 500 can jointly execute instructions for executing the data collection method in the above method embodiment.
[0167] It is understandable that the memory 506 in different computing devices 500 in the computing device cluster can store different instructions, which are respectively used to execute part of the functions of the electronic device. That is, the instructions stored in the memory 506 in different computing devices 500 can implement the functions of one or more modules in the communication module and the processing module.
[0168] In some possible implementations, one or more computing devices in the computing device cluster may be connected via a network, which may be a wide area network or a local area network. Figure 7 A possible implementation is shown. Figure 7 As shown, two computing devices 500A and 500B are connected via a network. Specifically, the network is connected via a communication interface in each computing device. In this type of possible implementation, the memory 506 in the computing device 500A stores instructions for executing the functions of the communication module. At the same time, the memory 506 in the computing device 500B stores instructions for executing the functions of the processing module.
[0169] It should be understood that Figure 7 The functions of the computing device 500A shown in FIG. 5A may also be completed by multiple computing devices 500. Similarly, the functions of the computing device 500B may also be completed by multiple computing devices 500.
[0170] Based on the above embodiments, the embodiments of the present application further provide a computer-readable storage medium, which may be any available medium that can be stored by a computing device or a data storage device such as a data center containing one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc. The computer-readable storage medium includes instructions that instruct the computing device to execute the data acquisition method in the above method embodiment.
[0171] Based on the above embodiments, the embodiments of the present application further provide a computer program product including instructions, which may be software or a program product including instructions that can be run on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, the at least one computing device executes the data collection method in the above method embodiment.
[0172] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.
[0173] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data acquisition device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data acquisition device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0174] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data acquisition device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0175] These computer program instructions may also be loaded onto a computer or other programmable data acquisition device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0176] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.
Claims
1. A data collection method, characterized in that: include: Acquire first information, where the first information is used to indicate M parameters selected by a user and at least one value of each of the M parameters, where the M parameters correspond to one object, and M is a positive integer; Determine a questionnaire according to the first information, the questionnaire includes a first set, the first set includes N elements, each of the N elements includes a value of at least one parameter, the at least one parameter belongs to the M parameters, the parameters included in the N elements are the same, and at least one of the same parameters in the N elements has a different value, and N is a positive integer; Second information is obtained according to the questionnaire to complete data collection of the user, wherein the second information is used to indicate an element selected by the user from the N elements.
2. The method according to claim 1, characterized in that Determining a questionnaire according to the first information includes: determining that a first parameter of the M parameters is a first parameter in the first set, and determining that N values of the first parameter are N values of the first parameter in the first set, the N values of the first parameter belonging to at least one value of the first parameter of the M parameters; Determine that a second parameter among the M parameters that satisfies the first condition is the i-th parameter in the first set, and determine that the N values of the second parameter are the N values of the i-th parameter in the first set, the N values of the second parameter belong to at least one value of the second parameter among the M parameters, and i is an integer greater than 1.
3. The method according to claim 2, characterized in that The first condition includes: The difference between the first weight and the second weight is less than a first threshold, the first weight is the weight corresponding to any one of the first parameter to the i-1th parameter in the first set, and the second weight is the weight corresponding to the second parameter; The remaining number of occurrences in the questionnaire is greater than a second threshold, and the remaining number of occurrences is related to a preset total number of occurrences; and, Different from the first parameter to the (i-1)th parameter in the first set.
4. The method according to claim 2, characterized in that The first condition includes: The remaining number of occurrences in the questionnaire is greater than a second threshold, and the remaining number of occurrences is related to a preset total number of occurrences; and, Different from the first parameter to the (i-1)th parameter in the first set.
5. The method according to claim 4, characterized in that Determining that a second parameter among the M parameters that satisfies a first condition is an i-th parameter in the first set includes: When the number of parameters satisfying the first condition among the M parameters is greater than 1, a parameter satisfying the first condition is determined as the second parameter, wherein the second parameter corresponds to a first distance, the first distance is the minimum value of the distances corresponding to the M parameters, and the first distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set.
6. The method according to claim 5, characterized in that The distance between the second parameter and the first parameter to the i-1th parameter in the first set is the minimum value of the difference between the weight of the second parameter and the weight of the first parameter to the i-1th parameter in the first set.
7. The method according to claim 2, characterized in that The questionnaire further includes a second set, where the second set is a set determined before the first set is determined, and the first condition includes: The second parameter is included in the second set; and, Different from the first parameter to the (i-1)th parameter in the first set.
8. The method according to claim 7, characterized in that Determining that a second parameter among the M parameters that satisfies a first condition is an i-th parameter in the first set includes: When the number of parameters satisfying the first condition among the M parameters is greater than 1, determining one parameter from the parameters satisfying the first condition as the second parameter; Among them, the second parameter corresponds to a second distance, the M parameters also include a third parameter that satisfies the second condition, the third parameter corresponds to a third distance, the sum of the second distance and the third distance is the smallest, the second distance is the distance between the second parameter and the first parameter to the i-1th parameter in the first set, and the third distance is the distance between the third parameter and all parameters in the second set except the second parameter.
9. The method according to claim 8, characterized in that The second condition includes: The remaining number of occurrences in the questionnaire is greater than a second threshold; and, Different from all parameters in the second set except the second parameter.
10. The method according to claim 8 or 9, characterized in that After determining a parameter from the parameters satisfying the first condition as the second parameter, the method further includes: The second parameter in the second set is replaced with the third parameter.
11. The method according to any one of claims 1 to 10, characterized in that: The method further comprises: Determine a third set according to the first information; Determine a first loss corresponding to the third set, where the first loss is used to indicate a difference between prior probabilities corresponding to N values of a fourth parameter in the third set, where the fourth parameter is any one parameter in the third set; A first update operation is performed on the N values of the fourth parameter in the third set to obtain the first set, wherein the N values of the fourth parameter in the first set are different from at least one value of the N values of the fourth parameter in the third set, the first set corresponds to a second loss, the second loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fourth parameter in the first set, and the second loss is less than the first loss.
12. The method according to claim 11, characterized in that Performing a first update operation on the N values of the fourth parameter in the third set to obtain the first set includes: Performing a first update operation on the N values of the fourth parameter in the third set to obtain a fourth set; Determine a first difference corresponding to the fourth set, the first difference being used to indicate a difference between utilities corresponding to N elements in the fourth set, the utility corresponding to any one of the N elements being used to indicate a sum of prior probabilities corresponding to values of all parameters included in the any one element; A second update operation is performed on the N values of the fifth parameter in the fourth set to obtain the first set, wherein the fifth parameter is any parameter in the fourth set, the value of the fifth parameter of the first element in the first set is the value of the fifth parameter of the second element in the fourth set, the value of the fifth parameter of the second element in the first set is the value of the fifth parameter of the first element in the fourth set, the first set corresponds to a second difference, the second difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, and the second difference is smaller than the first difference.
13. The method according to claim 11, characterized in that Performing a second update operation on the N values of the fifth parameter in the fourth set to obtain the first set includes: Performing a second update operation on the N values of the fifth parameter in the fourth set to obtain a fifth set; determining the number of times the value of the fifth parameter of the first element in the fifth set has appeared in the questionnaire; If the number of occurrences is greater than a third threshold, performing a third update operation on the value of the fifth parameter of the first element in the fifth set to obtain the first set; Among them, the value of the fifth parameter of the first element in the first set has appeared the number of times in the questionnaire is less than the third threshold value, the first set corresponds to a third difference, the third difference is used to indicate the difference between the utilities corresponding to the N elements in the first set, the third difference is less than or equal to the second difference, the first set corresponds to a third loss, the third loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the first set, the fifth set corresponds to a fourth loss, the fourth loss is used to indicate the difference between the prior probabilities corresponding to the N values of the fifth parameter in the fifth set, and the difference between the third loss and the fourth loss is less than the fourth threshold value.
14. A computing device cluster, characterized in that: The computing device cluster includes at least one computing device, each computing device in the at least one computing device includes a processor and a memory; the memory is used to store computer program instructions; The processor calls the computer program instructions stored in the memory to execute the method according to any one of claims 1 to 13.
15. A computer-readable storage medium, characterized in that: The method comprises computer program instructions, and when the computer program instructions are executed by a computing device, the computing device performs the method according to any one of claims 1 to 13.
16. A computer program product comprising instructions, characterized in that When the instructions are executed by a computing device, the computing device is caused to perform the method as claimed in any one of claims 1 to 13.
Citation Information
Cited By
Data acquisition method and computing device cluster
EP4718361A1