Information processing method and device, equipment and storage medium

Abstract

The invention provides an information processing method and device, equipment and a storage medium, which can be applied to the fields of computer technology and financial science and technology. The method comprises the steps of determining attribute information of a target object and a predetermined resource value corresponding to a preset periodic task in response to triggering of the preset periodic task, the attribute information including at least one attribute category; based on a preset evaluation rule corresponding to each attribute category, performing risk evaluation on the attribute information to obtain a risk value of the target object; for each target time period, determining a resource fluctuation value Ngt according to a resource transaction value corresponding to the target time period and acquired from a cache unit and N historical resource values of the product acquired from a product database; 2; determining a resource consumption proportion corresponding to the resource fluctuation value in the target time period based on the risk value and the attention of the target object to the product; and based on the resource consumption proportion and the predetermined resource value, determining a recommended resource value in the target time period.

Description

Technical Field

[0001] The present disclosure relates to the fields of computer technology and financial technology, and in particular to an information processing method, device, equipment and storage medium. Background Art

[0002] During the process of online transaction of products, data can be extracted regularly and quantitatively from the pre-stored resource data of the target object, and the extracted resource data can be used to obtain products to complete the online transaction of products.

[0003] In the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related art: in the process of periodically extracting resource data, it is necessary to determine the resource value extracted each time. Since the transaction environment will change, the quantitatively determined resource value is difficult to be adjusted intelligently based on the transaction environment, and in the adjustment process, a large amount of historical transaction data needs to be analyzed, which consumes a lot of system resources. Summary of the invention

[0004] In view of the above problems, the present disclosure provides an information processing method, apparatus, device, medium and program product.

[0005] According to the first aspect of the present disclosure, there is provided an information processing method, comprising: in response to a preset periodic task being triggered, determining attribute information of a target object and a predetermined resource value corresponding to the preset periodic task, wherein the attribute information includes at least one attribute category; based on preset evaluation rules corresponding to each of the attribute categories, performing risk assessment on the attribute information to obtain a risk value of the target object; for each target time period, determining a resource fluctuation value according to a resource transaction value corresponding to the target time period obtained from a cache unit and N historical resource values ​​of the product obtained from a product database, wherein the target time period is determined in a period corresponding to the preset periodic task, and N>2; determining a resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product; and determining a recommended resource value in the target time period based on the resource consumption ratio and the predetermined resource value.

[0006] According to an embodiment of the present disclosure, the above-mentioned attribute information is subjected to risk assessment based on preset assessment rules corresponding to each of the above-mentioned attribute categories to obtain a risk value of the above-mentioned target object, including: determining an assessment value of each of the above-mentioned attribute categories in the above-mentioned attribute information based on preset assessment rules corresponding to each of the above-mentioned attribute categories; summing up each of the above-mentioned assessment values ​​to obtain a total assessment value; dividing the above-mentioned total assessment value by a preset maximum risk value to obtain the above-mentioned risk value.

[0007] According to an embodiment of the present disclosure, the resource fluctuation value is determined based on the resource transaction value corresponding to the above-mentioned target time period obtained from the cache unit and N historical resource values ​​of the product obtained from the product database, including: determining an average resource value based on the N historical resource values; determining an intermediate value based on the above-mentioned resource transaction value and the above-mentioned average resource value; in the case that the above-mentioned intermediate value satisfies a preset interval, determining the above-mentioned intermediate value as the above-mentioned resource fluctuation value; in the case that the above-mentioned intermediate value does not satisfy the above-mentioned preset interval, determining the absolute value of the above-mentioned intermediate value as the above-mentioned resource fluctuation value.

[0008] According to an embodiment of the present disclosure, the method further includes: obtaining a first target fluctuation value and a second target fluctuation value within a first preset time period, wherein the first target fluctuation value is the maximum value among the resource fluctuation values ​​determined according to the intermediate value within the first preset time period, and the second target fluctuation value is the maximum value among the resource fluctuation values ​​determined according to the absolute value of the intermediate value within the first preset time period; determining a plurality of preset fluctuation intervals based on the first target fluctuation value and the second target fluctuation value, wherein the preset fluctuation intervals include a plurality of first fluctuation intervals determined based on the first target fluctuation value, and a plurality of second fluctuation intervals determined based on the second target fluctuation value.

[0009] According to an embodiment of the present disclosure, the resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined based on the risk value and the target object's attention to the product, including: based on a determination method for the resource fluctuation value, determining a plurality of fluctuation intervals corresponding to the determination method in the preset fluctuation interval; matching the resource fluctuation value with the plurality of fluctuation intervals to obtain a target fluctuation interval; determining a target weight corresponding to the target fluctuation interval; and determining the resource consumption ratio corresponding to the resource fluctuation value based on the target weight, the risk value and the attention.

[0010] According to an embodiment of the present disclosure, the above method also includes: when the above target fluctuation interval is greater than the interval in which the above first target fluctuation value is located, determining the resource consumption ratio corresponding to the above resource fluctuation value as a preset value; based on the above preset value and the above predetermined resource value, determining the recommended resource value in the above target time period.

[0011] According to an embodiment of the present disclosure, before determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product, it also includes: obtaining the historical cumulative clicks on the product-related page by the target object in the second preset time period, and the historical peak clicks on the product-related page by the target object in the third preset time period; taking the quotient of the historical cumulative clicks and the historical peak clicks to obtain the attention.

[0012] According to an embodiment of the present disclosure, the above method also includes: determining the remaining resource value of the above target object; subtracting the above remaining resource value from the above recommended resource value to obtain a new remaining resource value; and sending the above new remaining resource value and the above recommended resource value to the client corresponding to the above target object.

[0013] The second aspect of the present disclosure provides an information processing device, including: an information determination module, for determining the attribute information of a target object and a predetermined resource value corresponding to the preset periodic task in response to a preset periodic task being triggered, wherein the attribute information includes at least one attribute category; a risk assessment module, for performing a risk assessment on the attribute information based on preset evaluation rules corresponding to each of the attribute categories to obtain a risk value of the target object; a fluctuation determination module, for determining a resource fluctuation value for each target time period according to a resource transaction value corresponding to the target time period obtained from a cache unit and N historical resource values ​​of a product obtained from a product database, wherein the target time period is determined in the period corresponding to the preset periodic task, and N>2; a ratio determination module, for determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product; a recommendation determination module, for determining a recommended resource value in the target time period based on the resource consumption ratio and the predetermined resource value.

[0014] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above method.

[0015] The fourth aspect of the present disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above method.

[0016] The fifth aspect of the present disclosure also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0017] According to the information processing method, device, equipment, medium and program product provided by the present disclosure, the resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined based on the risk value and the target object's attention to the product. Since the risk value, attention and resource fluctuation value will change dynamically with the change of the trading environment. Therefore, the recommended resource value determined based on the resource consumption ratio and the predetermined resource value is more in line with the current trading environment, and the recommended resource value is intelligently adjusted based on the trading environment. And in the process of adjusting the recommended resource value, the resource fluctuation value is determined according to the resource transaction value obtained from the cache unit and the historical resource value obtained from the product database. Since the resource transaction value of the cache unit corresponds to the target time period, it is dynamically changing and has real-time, and does not need to be stored in the system database, which at least reduces the occupation of system resources to a certain extent. Therefore, the data is stored in the cache unit and the product database respectively, which effectively reduces the consumption of system resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above contents and other purposes, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0019] Figure 1 The application scenario diagram of the information processing method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown;

[0020] Figure 2 The flowchart of the information processing method according to the embodiment of the present disclosure is schematically shown;

[0021] Figure 3 A flowchart schematically shows an information processing method according to another embodiment of the present disclosure;

[0022] Figure 4 A block diagram schematically shows a structure of an information processing device according to an embodiment of the present disclosure; and

[0023] Figure 5 A block diagram of an electronic device suitable for implementing an information processing method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0024] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0025] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0026] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0027] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0028] In the technical solution of the present invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data comply with the relevant laws, regulations and standards of relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0029] In view of this, the embodiments of the present disclosure provide an information processing method, an information processing device, an electronic device, a computer-readable storage medium, and a computer program product. The method includes: in response to a preset periodic task being triggered, determining the attribute information of the target object and the predetermined resource value corresponding to the preset periodic task, wherein the attribute information includes at least one attribute category; based on the preset evaluation rules corresponding to each attribute category, performing risk assessment on the attribute information to obtain the risk value of the target object; for each target time period, determining the resource fluctuation value according to the resource transaction value corresponding to the target time period obtained from the cache unit and the N historical resource values ​​of the product obtained from the product database, wherein the target time period is determined in the period corresponding to the preset periodic task, and N>2; based on the risk value and the target object's attention to the product, determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period; based on the resource consumption ratio and the predetermined resource value, determining the recommended resource value in the target time period.

[0030] Figure 1 The application scenario diagram of the information processing method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0031] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104 and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0032] The user may use at least one of the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0033] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0034] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0035] It should be noted that the information processing method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the information processing device provided in the embodiment of the present disclosure can generally be set in the server 105. The information processing method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the information processing device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0036] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0037] The following will be based on Figure 1 The scene described by Figure 2 and Figure 3 The information processing method of the disclosed embodiment is described in detail.

[0038] Figure 2 The flowchart of the information processing method according to the embodiment of the present disclosure is schematically shown.

[0039] like Figure 2 As shown, the information processing method of this embodiment includes operations S210 to S250.

[0040] In operation S210, in response to a preset periodic task being triggered, attribute information of a target object and a predetermined resource value corresponding to the preset periodic task are determined, wherein the attribute information includes at least one attribute category.

[0041] In operation S220, based on preset evaluation rules corresponding to each attribute category, risk assessment is performed on the attribute information to obtain a risk value of the target object.

[0042] In operation S230, for each target time period, the resource fluctuation value is determined based on the resource transaction value corresponding to the target time period obtained from the cache unit and N historical resource values ​​of the product obtained from the product database, wherein the target time period is determined in the cycle corresponding to the preset periodic task, and N>2.

[0043] In operation S240 , based on the risk value and the target object's attention to the product, a resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined.

[0044] In operation S250, a recommended resource value in a target time period is determined based on the resource consumption ratio and the predetermined resource value.

[0045] According to an embodiment of the present disclosure, during the online transaction of a product, part of the resource data can be extracted from the pre-stored resource data of the target object periodically or based on the time set by the target object, and then the extracted part of the resource data can be used to obtain the product. Specifically, the product can be a precious metal such as gold. In the process of extracting part of the resource data, a preset periodic task can be set. By triggering the periodic task, the recommended resource value corresponding to each time period in the cycle is calculated, and then the corresponding part of the resource data is extracted from the pre-stored resource data based on the recommended resource value. Among them, the period of the preset periodic task can be set to one month, and each time period in the cycle can be set to one day.

[0046] According to an embodiment of the present disclosure, in response to a preset periodic task being triggered, the attribute information of the target object and the predetermined resource value corresponding to the preset periodic task are determined. The attribute information includes at least one attribute category, such as: personal information category, resource information category and transaction information category of the target object. Specifically, it may include the age, net asset amount, types of assets held and gold investment experience of the target object. It should be noted that the acquisition of the attribute information of the target object complies with the provisions of relevant laws and regulations, and necessary confidentiality measures are taken. And before the acquisition, the user's authorization or consent is obtained.

[0047] According to an embodiment of the present disclosure, the predetermined resource value corresponding to the preset periodic task can be set based on the resource data corresponding to each period and the number of time periods in the period. For example: assuming that the resource data corresponding to each period is 10,000 yuan, assuming that the number of time periods in the period is 20, the predetermined resource value for each time period is determined to be N=M / d=10000 / 20=500. Among them, M represents the resource data corresponding to each period, d represents the number of time periods in the period, and N represents the predetermined resource value.

[0048] According to an embodiment of the present disclosure, each attribute category has a corresponding preset evaluation rule. The preset evaluation rule includes a rule for comparing with a divided interval and a rule for comparing with a preset fixed value. The risk value of the target object is obtained by evaluating the attribute information. As the risk value increases, it indicates that the target object is more sensitive to the recommended resource value. When the resource fluctuation value is large, the greater the fluctuation of the recommended resource value, the more accurately the recommended resource value is determined.

[0049] According to an embodiment of the present disclosure, in the cycle corresponding to the preset periodic task, each time period has a corresponding recommended resource value. For each target time period determined in the cycle corresponding to the preset periodic task, the resource transaction value corresponding to the target time period is obtained from the cache unit, wherein the cache unit can be connected to an external interface, specifically, the external interface can be a third-party network interface. The resource transaction value for each target time period may be different. Specifically, the resource transaction value can be the opening price of the product in each target time period. N historical resource values ​​of the product are obtained from the product database, wherein the historical resource value can be the opening price corresponding to each time period in the historical transaction time.

[0050] According to the embodiment of the present disclosure, the resource fluctuation value is determined according to the resource transaction value and N historical resource values. Specifically, the resource transaction value and the average value of the N historical resource values ​​can be compared to obtain the resource fluctuation value. Then, the recommended resource value for the target time period is determined based on the resource fluctuation value, so that the recommended resource value is more accurate and reasonable.

[0051] According to the embodiment of the present disclosure, the attention degree of the target object to the product is determined. The higher the attention degree, the more sensitive the target object is to the recommended resource value. When the resource fluctuation value is large, the fluctuation of the recommended resource value is also large. Based on the risk value and the attention degree, the resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined, and the resource consumption ratio is multiplied by the predetermined resource value to determine the recommended resource value in the target time period.

[0052] According to an embodiment of the present disclosure, the resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined based on the risk value and the target object's attention to the product. Since the risk value, attention and resource fluctuation value will change dynamically with the change of the trading environment. Therefore, the recommended resource value determined based on the resource consumption ratio and the predetermined resource value is more in line with the current trading environment, and the recommended resource value is intelligently adjusted based on the trading environment. In the process of adjusting the recommended resource value, the resource fluctuation value is determined according to the resource transaction value obtained from the cache unit and the historical resource value obtained from the product database. Since the resource transaction value of the cache unit corresponds to the target time period, it is dynamically changing and real-time, and does not need to be stored in the system database, which at least reduces the occupation of system resources to a certain extent. Therefore, storing the data in the cache unit and the product database respectively effectively reduces the consumption of system resources.

[0053] According to an embodiment of the present disclosure, based on preset evaluation rules corresponding to each attribute category, risk assessment is performed on attribute information to obtain a risk value of the target object, which may include the following operations:

[0054] Based on the preset evaluation rules corresponding to each attribute category, the evaluation value of each attribute category in the attribute information is determined; each evaluation value is summed to obtain a total evaluation value; the total evaluation value is divided by the preset maximum risk value to obtain a risk value.

[0055] According to the embodiments of the present disclosure, each attribute category has a corresponding preset evaluation rule. Specifically, the personal information category in the attribute category includes the age of the target object, the resource information category includes the net asset amount, and the transaction information category includes the types of assets held and gold investment experience.

[0056] According to the embodiments of the present disclosure, the target object's age can be divided into the following categories: A. Under 18 years old; B. 18-30 years old; C. 31-50 years old; D. 51-65 years old; E. Over 65 years old. Thus, the personal information is evaluated based on the age range. It should be noted that if the age is selected as a target under 18 years old, it is not allowed to purchase the accumulation fund, so the target of the accumulation fund fixed investment must be over 18 years old.

[0057] According to the embodiments of the present disclosure, the net asset amount, that is, the amount of assets minus liabilities, can be divided into the following categories: A. less than 500,000 yuan; B. 500,000-1 million; C. 1 million-5 million; D. 5 million-10 million; E. more than 10 million. Thus, the resource information is evaluated based on the amount range. Among them, assets include deposits, wealth management, funds, bonds, precious metals, account transactions (such as account foreign exchange, account agricultural products, account basic metals, account energy, foreign exchange trading, etc.), provident funds, pensions and branch wealth management, insurance. Liabilities include credit cards and loans.

[0058] According to the embodiments of the present disclosure, the types of assets held can be divided into the following categories: A. Apart from bank savings, there is basically no other investment experience (judgment basis: the target object's assets are only deposits); B. Purchased financial products such as bank wealth management, bonds, and insurance (judgment basis: the target object's asset classification includes wealth management, bonds, and insurance); C. Participated in the transaction of products such as stocks and funds (judgment basis: the target object's asset classification includes funds or the target object has opened a securities fund account). Thus, the types of assets held in the resource information category are evaluated based on the amount range.

[0059] According to the embodiments of the present disclosure, the gold investment experience, that is, the account opening time of the target object's Jicunjin (and Ruyijin) account can be divided into the following categories: A. No experience (corresponding to no account opening); B. Less than 2 years (account opening time is less than 2 years ago); C. 2-5 years (account opening time is 2-5 years ago); D. 5-10 years (account opening time is 5-10 years ago); E. More than 10 years (account opening time is more than 10 years ago). Thus, the gold investment experience in the resource information category is evaluated based on the amount range.

[0060] According to an embodiment of the present disclosure, for the above four types of information, different objects may correspond to different options, and different options correspond to certain evaluation plus component values. The corresponding relationship of the evaluation plus component values ​​is shown in Table 1.

[0061] Table 1

[0062]

[0063] According to an embodiment of the present disclosure, the risk value λ depends on the total evaluation value of the completed evaluation values ​​of each attribute category. The total evaluation value is divided by the preset maximum risk value to obtain the risk value. As shown in Table 2, the preset maximum risk value is 12. The total evaluation value is represented by A, and the preset maximum risk value is 12, and the risk value λ can be obtained. Specifically, λ=A / 12. By determining the risk value, the recommended resource value determined is more accurate. The higher the risk value, the more sensitive the target object is to the recommended resource value. Furthermore, when the resource fluctuation value is large, the fluctuation of the recommended resource value will be greater.

[0064] Table 2

[0065]

[0066] According to an embodiment of the present disclosure, determining a resource fluctuation value according to a resource transaction value corresponding to a target time period obtained from a cache unit and N historical resource values ​​of a product obtained from a product database may include the following operations:

[0067] Based on N historical resource values, the average resource value is determined; based on the resource transaction value and the average resource value, the intermediate value is determined; when the intermediate value meets the preset interval, the intermediate value is determined as the resource fluctuation value; when the intermediate value does not meet the preset interval, the absolute value of the intermediate value is determined as the resource fluctuation value.

[0068] According to an embodiment of the present disclosure, the opening price of the gold price in the last 30 days can be obtained from the product database, and the opening price is used as the historical resource value. The average resource value is calculated based on the number of historical trading days and the historical resource value. The average resource value only retains 2 decimal places, and the third decimal place is not rounded. Based on the resource transaction value and the average resource value, the intermediate value is determined, where the resource transaction value is the opening price of the product in the target time period. The calculation formula is as follows: intermediate value = P OP / P μ30 -1, where P μ30 represents the average resource value, P OP Represents the transaction value of a resource.

[0069] According to an embodiment of the present disclosure, it is determined whether the intermediate value satisfies a preset interval. The preset interval may be set to an interval greater than 0. Specifically, if POP / P μ30 -1 is greater than 0, then it is included in the α value. If P OP / P μ30 -1 is less than 0, and the absolute value is included in the β value. Positive resource fluctuation value is represented by α, and negative resource fluctuation value is represented by β. The calculation formula is as follows: When P OP / P μ30 -1>0,α=P OP / P μ30 -1; when P OP / P μ30 -1<0,β=|P OP / P μ30 By distinguishing between positive resource fluctuation values ​​and negative resource fluctuation values, the fluctuation range is made more intuitive.

[0070] According to an embodiment of the present disclosure, the information processing method may further include the following operations:

[0071] Obtain a first target fluctuation value and a second target fluctuation value within a first preset time period, wherein the first target fluctuation value is the maximum value among the resource fluctuation values ​​determined according to the intermediate value within the first preset time period, and the second target fluctuation value is the maximum value among the resource fluctuation values ​​determined according to the absolute value of the intermediate value within the first preset time period; determine multiple preset fluctuation intervals based on the first target fluctuation value and the second target fluctuation value, wherein the preset fluctuation intervals include multiple first fluctuation intervals determined based on the first target fluctuation value, and multiple second fluctuation intervals determined based on the second target fluctuation value.

[0072] According to an embodiment of the present disclosure, a first target fluctuation value and a second target fluctuation value within a first preset time period are obtained, wherein the first preset time period can be set to three years. The first target fluctuation value is the maximum value of the resource fluctuation values ​​determined according to the intermediate values ​​within the first preset time period, that is, the maximum value of α within three years, expressed as α MAX The second target fluctuation value is the maximum value of the resource fluctuation value determined according to the absolute value of the intermediate value in the first preset time period, that is, the maximum value of β within three years, expressed as β MAX .

[0073] According to an embodiment of the present disclosure, a plurality of preset fluctuation intervals are determined based on the first target fluctuation value and the second target fluctuation value, and the plurality of preset fluctuation intervals include a plurality of first fluctuation intervals and a plurality of second fluctuation intervals. Specifically, the first fluctuation interval includes α∈(0, α MAX / 2], α∈(α MAX / 2,α MAX ] and α∈(α MAX , +∞]. The second fluctuation interval includes β∈(0, β MAX / 2], β∈(βMAX / 2, β MAX ] and β∈(β MAX , 100%). By setting a preset fluctuation range, it is convenient to determine the resource consumption ratio, and the resource consumption ratio can be determined more accurately.

[0074] According to an embodiment of the present disclosure, determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product may include the following operations:

[0075] Based on a method for determining resource fluctuation values, multiple fluctuation intervals corresponding to the determination method are determined in a preset fluctuation interval; the resource fluctuation values ​​are matched with the multiple fluctuation intervals to obtain a target fluctuation interval; a target weight corresponding to the target fluctuation interval is determined; based on the target weight, risk value and attention level, a resource consumption ratio corresponding to the resource fluctuation value is determined.

[0076] According to an embodiment of the present disclosure, the first fluctuation interval or the second fluctuation interval is selected based on the determination method of the resource fluctuation value. The determination method includes determination based on the intermediate value and determination based on the absolute value of the intermediate value. If the resource fluctuation value is determined based on the intermediate value, the first fluctuation interval is selected. If the resource fluctuation value is determined based on the absolute value of the intermediate value, the second fluctuation interval is selected.

[0077] According to an embodiment of the present disclosure, the resource fluctuation value is matched with multiple fluctuation intervals to obtain a target fluctuation interval. Each fluctuation interval has a corresponding weight. The target weight corresponding to the target fluctuation interval is determined, and the resource consumption ratio corresponding to the resource fluctuation value is determined based on the target weight, risk value and attention. Different weights are set for different fluctuation intervals, so that the calculated resource consumption ratio is more accurate. Specifically, the calculation method of the resource consumption ratio is shown in Table 3.

[0078] Table 3

[0079] Fluctuation range Resource consumption ratio <![CDATA[α∈(0,α MAX / 2]]]> 1-20% (1+λ*0.5+γ*0.5) <![CDATA[α∈(α MAX / 2,a MAX ]]> 1-40% (1+λ*0.5+γ*0.5) <![CDATA[α∈(α MAX ,+∞]]]> 0 <![CDATA[β∈(0,β MAX / 2]]]> 1+20%(1+λ*0.5+γ*0.5) <![CDATA[β∈(β MAX / 2,b MAX ]]> 1+40%(1+λ*0.5+γ*0.5) <![CDATA[β∈(β MAX ,100%)]]> 1+50%(1+λ*0.5+γ*0.5)

[0080] Among them, α∈(0, α MAX / 2] corresponds to a weight of -20%, α∈(α MAX / 2,α MAX ] corresponds to a weight of -40%, α∈(α MAX , +∞] corresponds to a weight of 0, β∈(0, β MAX / 2] corresponds to a weight of 20%, β∈(β MAX / 2, β MAX ] corresponds to a weight of 40%, β∈(β MAX, 100%) has a corresponding weight of 50%, λ represents the risk value, γ represents the attention degree, and the risk value and attention degree each account for 50% of the influence.

[0081] According to an embodiment of the present disclosure, the information processing method may further include the following operations:

[0082] When the target fluctuation interval is greater than the interval where the first target fluctuation value is located, the resource consumption ratio corresponding to the resource fluctuation value is determined as a preset value; based on the preset value and the predetermined resource value, the recommended resource value in the target time period is determined.

[0083] According to an embodiment of the present disclosure, when the target fluctuation range is α∈(α MAX , +∞], the resource consumption ratio corresponding to the resource fluctuation value is determined as the preset value. The preset value is 0. The product of the preset value and the predetermined resource value is obtained, and the recommended resource value is also 0, indicating that it is necessary to suspend the deduction and stop obtaining the product, so as to make the recommended resource value more reasonable and reduce the waste of resources.

[0084] According to an embodiment of the present disclosure, before determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product, the following operations may also be included:

[0085] Obtain the historical cumulative clicks of the target object on the product-related page within the second preset time period and the historical peak clicks of the target object on the product-related page within the third preset time period; take the historical cumulative clicks and the historical peak clicks as the quotient to obtain the attention degree.

[0086] According to an embodiment of the present disclosure, the historical cumulative click volume Q of the target object on the product-related page within the second preset time period is obtained, wherein the second preset time period can be set to one month. Specifically, the product-related page can be a page related to product market conditions in mobile banking. The more frequently the target object browses the market conditions page of the mobile banking product, the more the target object pays attention to the product and is more sensitive to the recommended resource value.

[0087] According to an embodiment of the present disclosure, the historical peak click volume Q of the target object on the product-related page within the third preset time period is obtained. MAX , where the third preset time can be set to one year. The historical cumulative click volume and the historical peak click volume are divided to obtain the attention degree. The attention degree γ takes a value of 0-1, and the γ value is calculated monthly. The calculation formula is as follows: γ = Q / Q MAX If Q=0, it means there is no click volume in the last month, then γ=0. By determining the attention, the recommended resource value is more accurate. The higher the attention, the more sensitive the target object is to the recommended resource value. When the resource fluctuation value is large, the fluctuation of the recommended resource value is also greater.

[0088] According to an embodiment of the present disclosure, for example, in response to a preset periodic task being triggered, the attribute information of the target object is determined as:

[0089] (1) Age: C. 31-50 years old;

[0090] (2) Net assets (i.e. assets minus liabilities): B. 500,000-1,000,000;

[0091] (3) Investment behavior: C. Participated in the trading of stocks, funds and other products;

[0092] (4) Gold investment experience: B. Less than 2 years.

[0093] Compare the attribute information with Table 1 in sequence, and obtain the total evaluation value A=2+1+2+1=6, and then determine the risk value λ=A / 12=0.5.

[0094] Get the target object's historical cumulative click volume Q=10 on the product-related page within one month, and the target object's historical peak click volume Q on the product-related page within one year MAX＝ 20, get attention γ = Q / Q MAX =10 / 20=0.5.

[0095] The 17 historical resource values ​​of the product are obtained, as shown in Table 5. The average resource value is determined to be 415.71. The target time period is determined to be **** year * month * day, and the resource transaction value corresponding to the target time period is 421.2. Based on the resource transaction value and the average resource value, the median value is determined. Median value = P OP / P μ30 -1=resource transaction value / average resource value-1=1.32%. If the middle value of the determined value meets the preset interval, the middle value is determined as the resource fluctuation value, and the resource fluctuation value α is 1.32%.

[0096] Get α within three years MAX and β MAX , 30% and 2% (rounded to integers), respectively, and then determine multiple preset fluctuation ranges, as shown in Table 4. Based on the resource fluctuation value α=1.32%, the target fluctuation range is determined to be α∈(0, 15%], and then the target weight is determined to be -20%. Based on the target weight, risk value and attention, the resource consumption ratio corresponding to the resource fluctuation value is determined to be 0.7.

[0097] Table 4

[0098] Fluctuation range Resource consumption ratio α∈(0，15％] 1-20％(1+0.5*0.5+0.5*0.5)＝0.70 α∈(15％，30％] 1-40％(1+0.5*0.5+0.5*0.5)＝0.4 α greater than 30% 0 β∈(0，1％] 1+20％(1+0.5*0.5+0.5*0.5)＝1.30 β∈(1％，2％] 1+40％(1+0.5*0.5+0.5*0.5)＝1.60 β∈(2％，100％) 1+50％(1+0.5*0.5+0.5*0.5)＝1.75

[0099] Table 5

[0100]

[0101]

[0102]

[0103] According to the embodiment of the present disclosure, the recommended resource value obtained according to the information processing method is compared with the quantitative resource value in the related art. Each recommended resource value and quantitative resource value has a corresponding handling fee. The handling fee is calculated as follows: the recommended resource value and the quantitative resource value are multiplied by the handling fee rate respectively. Specifically, the handling fee rate can be set to 0.5%. The shares corresponding to the recommended resource value and the quantitative resource value are determined based on the handling fee. The share is calculated as follows: (DD*0.5%) / P OP , where D represents the recommended resource value or quantitative resource value, P OP Indicates the resource transaction value. Based on the total recommended resource value and the total share, the average cost is calculated.

[0104] According to the embodiments of the present disclosure, as shown in Table 6, the average cost obtained according to the recommended resource value is 13300 / 32.0294=415.24 yuan / gram. As shown in Table 7, the average cost obtained according to the quantitative resource value is 10000 / 24.0426=415.93 yuan / gram. After comparing the two, it is determined that the recommended resource value determined by the information processing method saves an average cost of 415.93-415.24=0.69 yuan / gram. Therefore, it is shown that the recommended resource value determined by using the information processing method is more reasonable and can save costs to a certain extent.

[0105] Table 6

[0106]

[0107]

[0108] Table 7

[0109] Resource transaction value Quantitative resource value Fees Share 421.2 500 2.5 1.1811 424.59 500 2.5 1.1717 418.52 500 2.5 1.1887 413.5 500 2.5 1.2031 412.7 500 2.5 1.2054 412.68 500 2.5 1.2055 412.61 500 2.5 1.2057 411 500 2.5 1.2104 412.3 500 2.5 1.2066 411.6 500 2.5 1.2086 413.2 500 2.5 1.2040 411.2 500 2.5 1.2098 411.12 500 2.5 1.2101 412.78 500 2.5 1.2052 412.78 500 2.5 1.2052 413.2 500 2.5 1.2040 412.3 500 2.5 1.2066 413.14 500 2.5 1.2041 413.22 500 2.5 1.2039 413.6 500 2.5 1.2028 Total 10000 Total 24.0425

[0110] Figure 3 The flowchart of an information processing method according to another embodiment of the present disclosure is schematically shown.

[0111] like Figure 3 As shown, the information processing method of this embodiment includes operations S310 to S330.

[0112] In operation S310, a remaining resource value of a target object is determined.

[0113] In operation S320, the remaining resource value is subtracted from the recommended resource value to obtain a new remaining resource value.

[0114] In operation S330, the new remaining resource value and the recommended resource value are sent to the client corresponding to the target object.

[0115] According to an embodiment of the present disclosure, starting from the fifth-to-last natural day of each month, the remaining resource value of the target object is determined on the server side, and the resource data required for the current cycle is frozen from the remaining resource value. After determining the recommended resource value for the target time period in the cycle, the remaining resource value and the recommended resource value are subtracted to obtain a new remaining resource value. The new remaining resource value and the recommended resource value are sent to the client corresponding to the target object. This allows the client to purchase the product based on the recommended resource value, and the new remaining resource value is visually displayed, so that the client can complete the acquisition of the product on time, effectively improving the user experience.

[0116] Based on the above information processing method, the present disclosure also provides an information processing device. Figure 4 The device is described in detail.

[0117] Figure 4 The structure block diagram of the information processing device according to the embodiment of the present disclosure is schematically shown.

[0118] like Figure 4 As shown, the information processing device 400 of this embodiment includes an information determination module 410 , a risk assessment module 420 , a fluctuation determination module 430 , a ratio determination module 440 and a recommendation determination module 450 .

[0119] The information determination module 410 is used to determine the attribute information of the target object and the predetermined resource value corresponding to the preset periodic task in response to the preset periodic task being triggered, wherein the attribute information includes at least one attribute category. In one embodiment, the information determination module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0120] The risk assessment module 420 is used to perform risk assessment on the attribute information based on the preset assessment rules corresponding to each attribute category to obtain the risk value of the target object. In one embodiment, the risk assessment module 420 can be used to perform the operation S220 described above, which will not be described in detail here.

[0121] The fluctuation determination module 430 is used to determine the resource fluctuation value for each target time period according to the resource transaction value corresponding to the target time period obtained from the cache unit and the N historical resource values ​​of the product obtained from the product database, wherein the target time period is determined in the cycle corresponding to the preset periodic task, and N>2. In one embodiment, the fluctuation determination module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0122] The ratio determination module 440 is used to determine the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product. In one embodiment, the ratio determination module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0123] The recommendation determination module 450 is used to determine the recommended resource value in the target time period based on the resource consumption ratio and the predetermined resource value. In one embodiment, the recommendation determination module 450 can be used to perform the operation S250 described above, which will not be described in detail here.

[0124] According to an embodiment of the present disclosure, the resource consumption ratio corresponding to the resource fluctuation value in the target time period is determined based on the risk value and the target object's attention to the product. Since the risk value, attention and resource fluctuation value will change dynamically with the change of the trading environment. Therefore, the recommended resource value determined based on the resource consumption ratio and the predetermined resource value is more in line with the current trading environment, and the recommended resource value is intelligently adjusted based on the trading environment. In the process of adjusting the recommended resource value, the resource fluctuation value is determined according to the resource transaction value obtained from the cache unit and the historical resource value obtained from the product database. Since the resource transaction value of the cache unit corresponds to the target time period, it is dynamically changing and real-time, and does not need to be stored in the system database, which at least reduces the occupation of system resources to a certain extent. Therefore, storing the data in the cache unit and the product database respectively effectively reduces the consumption of system resources.

[0125] According to an embodiment of the present disclosure, the risk assessment module 420 includes an assessment determination submodule, a total value determination submodule and a risk determination submodule.

[0126] The evaluation determination submodule is used to determine the evaluation value of each attribute category in the attribute information based on the preset evaluation rules corresponding to each attribute category.

[0127] The total value determination submodule is used to sum up each evaluation value to obtain the total evaluation value.

[0128] The risk determination submodule is used to calculate the quotient of the total assessment value and the preset maximum risk value to obtain the risk value.

[0129] According to an embodiment of the present disclosure, the fluctuation determination module 430 includes an average determination submodule, a middle determination submodule, a first resource determination submodule, and a second resource determination submodule.

[0130] The average determination submodule is used to determine the average resource value according to N historical resource values.

[0131] The intermediate determination submodule is used to determine the intermediate value based on the resource transaction value and the average resource value.

[0132] The first resource determination submodule is used to determine the intermediate value as the resource fluctuation value when the intermediate value meets a preset interval.

[0133] The second resource determination submodule is used to determine the absolute value of the intermediate value as the resource fluctuation value when the intermediate value does not satisfy the preset interval.

[0134] According to an embodiment of the present disclosure, the information processing device 400 further includes a fluctuation acquisition module and an interval determination module.

[0135] A fluctuation acquisition module is used to obtain a first target fluctuation value and a second target fluctuation value within a first preset time period, wherein the first target fluctuation value is the maximum value of the resource fluctuation values ​​determined according to the intermediate value within the first preset time period, and the second target fluctuation value is the maximum value of the resource fluctuation values ​​determined according to the absolute value of the intermediate value within the first preset time period.

[0136] The interval determination module is used to determine multiple preset fluctuation intervals based on the first target fluctuation value and the second target fluctuation value, wherein the preset fluctuation intervals include multiple first fluctuation intervals determined based on the first target fluctuation value, and multiple second fluctuation intervals determined based on the second target fluctuation value.

[0137] According to an embodiment of the present disclosure, the ratio determination module 440 includes an interval determination submodule, a target determination submodule, a weight determination submodule and a ratio determination submodule.

[0138] The interval determination submodule is used to determine a plurality of fluctuation intervals corresponding to the determination method in the preset fluctuation interval based on the determination method of the resource fluctuation value.

[0139] The target determination submodule is used to match the resource fluctuation value with multiple fluctuation intervals to obtain the target fluctuation interval.

[0140] The weight determination submodule is used to determine the target weight corresponding to the target fluctuation range.

[0141] The ratio determination submodule is used to determine the resource consumption ratio corresponding to the resource fluctuation value based on the target weight, risk value and attention degree.

[0142] According to an embodiment of the present disclosure, the information processing device 400 further includes a consumption determination module and a resource determination module.

[0143] The consumption determination module is used to determine that the resource consumption ratio corresponding to the resource fluctuation value is a preset value when the target fluctuation interval is greater than the interval where the first target fluctuation value is located.

[0144] The resource determination module is used to determine the recommended resource value in the target time period based on the preset value and the predetermined resource value.

[0145] According to an embodiment of the present disclosure, the information processing device 400 further includes a click acquisition module and an attention determination module.

[0146] The click acquisition module is used to acquire the historical cumulative clicks of the target object on the product-related page within the second preset time period and the historical peak clicks of the target object on the product-related page within the third preset time period.

[0147] The attention determination module is used to calculate the quotient of the historical cumulative click volume and the historical peak click volume to obtain the attention degree.

[0148] According to an embodiment of the present disclosure, the information processing device 400 further includes a remainder determination module, a remainder difference module and an information sending module.

[0149] The remaining determination module is used to determine the remaining resource value of the target object.

[0150] The remaining subtraction module is used to subtract the remaining resource value from the recommended resource value to obtain a new remaining resource value.

[0151] The information sending module is used to send the new remaining resource value and the recommended resource value to the client corresponding to the target object.

[0152] According to an embodiment of the present disclosure, any multiple modules of the information determination module 410, the risk assessment module 420, the fluctuation determination module 430, the ratio determination module 440 and the recommendation determination module 450 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the information determination module 410, the risk assessment module 420, the fluctuation determination module 430, the ratio determination module 440 and the recommendation determination module 450 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the information determination module 410, the risk assessment module 420, the fluctuation determination module 430, the ratio determination module 440 and the recommendation determination module 450 may be at least partially implemented as a computer program module, which may perform a corresponding function when executed.

[0153] Figure 5A block diagram of an electronic device suitable for implementing an information processing method according to an embodiment of the present disclosure is schematically shown.

[0154] like Figure 5 As shown, the electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include an onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0155] In RAM 503, various programs and data required for the operation of electronic device 500 are stored. Processor 501, ROM 502 and RAM 503 are connected to each other via bus 504. Processor 501 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 502 and / or RAM 503. It should be noted that the program can also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0156] According to an embodiment of the present disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to the bus 504. The electronic device 500 may further include one or more of the following components connected to the input / output (I / O) interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage portion 508 as needed.

[0157] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0158] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0159] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the information processing method provided by the embodiment of the present disclosure.

[0160] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 501. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0161] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 509, and / or installed from the removable medium 511. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0162] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the processor 501, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0163] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0164] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0165] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0166] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. An information processing method, comprising: In response to a preset periodic task being triggered, determining attribute information of a target object and a predetermined resource value corresponding to the preset periodic task, wherein the attribute information includes at least one attribute category; Based on the preset evaluation rules corresponding to each of the attribute categories, the attribute information is subjected to risk assessment to obtain a risk value of the target object; For each target time period, determine the resource fluctuation value according to the resource transaction value corresponding to the target time period obtained from the cache unit and N historical resource values ​​of the product obtained from the product database, wherein the target time period is determined in the period corresponding to the preset periodic task, and N>2; Determining a resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product; Based on the resource consumption ratio and the predetermined resource value, a recommended resource value in the target time period is determined.

2. The method according to claim 1, wherein: The step of performing risk assessment on the attribute information based on preset assessment rules corresponding to each attribute category to obtain a risk value of the target object includes: Determining the evaluation value of each of the attribute categories in the attribute information based on the preset evaluation rules corresponding to each of the attribute categories; Sum up the evaluation values ​​to obtain a total evaluation value; The risk value is obtained by dividing the total assessment value by the preset maximum risk value.

3. The method according to claim 1, wherein: The determining of the resource fluctuation value according to the resource transaction value corresponding to the target time period obtained from the cache unit and the N historical resource values ​​of the product obtained from the product database includes: Determine the average resource value based on N historical resource values; Determining a median value based on the resource transaction value and the average resource value; In the case where the intermediate value satisfies a preset interval, determining the intermediate value as the resource fluctuation value; When the intermediate value does not satisfy the preset interval, the absolute value of the intermediate value is determined as the resource fluctuation value.

4. The method according to claim 3, further comprising: Obtaining a first target fluctuation value and a second target fluctuation value within a first preset time period, wherein the first target fluctuation value is a maximum value among resource fluctuation values ​​determined according to intermediate values ​​within the first preset time period, and the second target fluctuation value is a maximum value among resource fluctuation values ​​determined according to absolute values ​​of intermediate values ​​within the first preset time period; A plurality of preset fluctuation intervals are determined based on the first target fluctuation value and the second target fluctuation value, wherein the preset fluctuation intervals include a plurality of first fluctuation intervals determined based on the first target fluctuation value, and a plurality of second fluctuation intervals determined based on the second target fluctuation value.

5. The method according to claim 4, wherein: The determining, based on the risk value and the target object's attention to the product, a resource consumption ratio corresponding to the resource fluctuation value in the target time period includes: Based on a determination method of the resource fluctuation value, determining a plurality of fluctuation intervals corresponding to the determination method in the preset fluctuation interval; Matching the resource fluctuation value with the plurality of fluctuation intervals to obtain a target fluctuation interval; Determining a target weight corresponding to the target fluctuation range; Based on the target weight, the risk value and the attention level, a resource consumption ratio corresponding to the resource fluctuation value is determined.

6. The method according to claim 5, further comprising: In a case where the target fluctuation interval is greater than the interval where the first target fluctuation value is located, determining the resource consumption ratio corresponding to the resource fluctuation value as a preset value; Based on the preset value and the predetermined resource value, a recommended resource value in the target time period is determined.

7. The method according to claim 1, wherein: Before determining the resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product, the method further includes: Obtaining the historical cumulative number of clicks on the product-related page by the target object within a second preset time period, and the historical peak number of clicks on the product-related page by the target object within a third preset time period; The historical cumulative click volume and the historical peak click volume are divided to obtain the attention degree.

8. The method according to claim 1, further comprising: Determining the remaining resource value of the target object; Subtract the remaining resource value from the recommended resource value to obtain a new remaining resource value; The new remaining resource value and the recommended resource value are sent to a client corresponding to the target object.

9. An information processing device, comprising: An information determination module, configured to determine, in response to a preset periodic task being triggered, attribute information of a target object and a predetermined resource value corresponding to the preset periodic task, wherein the attribute information includes at least one attribute category; A risk assessment module, configured to perform risk assessment on the attribute information based on preset assessment rules corresponding to each of the attribute categories to obtain a risk value of the target object; A fluctuation determination module, for determining a resource fluctuation value for each target time period according to a resource transaction value corresponding to the target time period obtained from a cache unit and N historical resource values ​​of a product obtained from a product database, wherein the target time period is determined in a period corresponding to the preset periodic task, and N>2; A ratio determination module, configured to determine a resource consumption ratio corresponding to the resource fluctuation value in the target time period based on the risk value and the target object's attention to the product; The recommendation determination module is used to determine the recommended resource value in the target time period based on the resource consumption ratio and the predetermined resource value.

10. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 8.

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