Automatic asset receiving method and system based on user asset evaluation model

Abstract

The invention discloses an automatic asset receiving method and system based on a user asset evaluation model, and relates to the technical field of asset receiving. Comprising the following steps: market value acquisition: setting a time threshold value, obtaining at least two time segment items, respectively obtaining market values of target game props in different time segment items, and obtaining at least two actual value items; and evaluation model establishment: predicting the subsequent value of the target game prop based on the change trend of the actual value item to obtain a predicted value item, and then obtaining an asset evaluation model. According to the method and the device, the emotion levels are divided, and the emotion values corresponding to the different emotion levels are matched according to the division result of the emotion levels, so that the value of the target game prop is re-evaluated according to the combination relationship between the emotion values and the actual value of the target game prop; and the target game prop is received according to the re-evaluation result, so that the asset receiving success rate can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of asset reception, and in particular to an automated asset reception method and system based on a user asset evaluation model. Background Art

[0002] Assets refer to resources formed by past transactions or events of an enterprise, owned or controlled by the enterprise, and expected to bring economic benefits to the enterprise. Assets can be divided into current assets, long-term investments, fixed assets, intangible assets and other assets according to liquidity. User assets usually refer to various digital assets owned by users on a certain platform or system. These assets may include but are not limited to virtual currency, points and rewards, digital goods, etc. The data generated by users on the platform, such as purchase history, browsing history, etc., are sometimes also regarded as user assets. When receiving user assets, it is necessary to first evaluate the value of the assets and receive them based on the value evaluation results to increase the success rate of receiving.

[0003] The digital asset value evaluation method, system and electronic device with patent publication number CN111160783A first obtains asset characteristic data and asset behavior data of the digital asset to be evaluated, as well as user data of the user who endorses the digital asset to be evaluated; then calculates the joint feature vector of the digital asset to be evaluated based on the asset characteristic data, the asset behavior data and the user data; then inputs the joint feature vector into a preset asset evaluation model to obtain the score of the label of the digital asset to be evaluated; the asset evaluation model takes the feature vector of the digital asset as input and the score of the label of the digital asset as output, and then determines the value of the digital asset to be evaluated based on the score of the label of the digital asset to be evaluated.

[0004] When the above-mentioned and similar technical solutions estimate the value of the user's game props assets based on the user asset evaluation model, the user asset evaluation model can only obtain the current market value and subsequent value trend of the game props. Different users' game props have different sources, such as gifts from friends, as tokens of trust, etc., which will give different emotional values ​​to the target game props. At this time, when the target game props are received based on the conventional asset evaluation model, the deviation between the value estimate of the target game props and the psychological value of the target user will cause twists and turns in the asset reception, affecting the asset reception rate. Summary of the invention

[0005] The purpose of the present invention is to provide an automated asset receiving method and system based on a user asset evaluation model to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: an automated asset receiving method and system based on a user asset evaluation model, comprising:

[0007] Market value acquisition: set a time threshold, obtain at least two time segment items, obtain the market value of the target game props in different time segment items, and obtain at least two actual value items;

[0008] Evaluation model establishment: predict the subsequent value of the target game props based on the change trend of the actual value item, obtain the predicted value item, and then obtain the asset evaluation model, and update and optimize the asset evaluation model based on the value information obtained in real time. According to the asset evaluation model, the market value of the target game props can be predicted, which is convenient for evaluating the value of the target game props. In addition, the asset evaluation model is optimized in combination with the value information obtained in real time to improve the evaluation accuracy;

[0009] Value evaluation update: Based on the update method, the target game props are first divided into emotional levels to obtain at least two emotional level items, and the assignment items are set to obtain at least two emotional value items. Based on the actual value items and the emotional value items, the value of the target game props is re-evaluated to obtain updated evaluation items. The target game props are received based on the updated evaluation items, thereby improving the acceptance rate of user assets;

[0010] The updating method includes:

[0011] The target game props are classified into emotional levels, influencing factors are set, the influencing factors include interaction time, at least two interaction time ranges are set, at least two interaction time items are obtained, and the levels are divided based on the interaction time items to obtain at least two emotional level items;

[0012] The actual interaction time of the target game prop is obtained to obtain an actual time item, and the actual emotion level item is obtained based on matching the actual time item with the interaction time item, thereby obtaining an actual emotion value item corresponding to the matching result;

[0013] Based on the combined results of the actual value item and the emotional actual value item, the value of the target game prop is updated and evaluated.

[0014] Furthermore, the interaction duration also includes the interaction frequency, and the method of dividing the emotion level includes:

[0015] Step 1: Divide the proportion range, set the proportion frequency, obtain two frequency ranges based on the proportion frequency, obtain frequency range items, and set the influence values ​​based on the frequency range items to obtain two influence data;

[0016] Step 2: Determine the actual proportion, obtain the actual interaction frequency of the target user to the target game prop, obtain the actual frequency item, and obtain the actual proportion frequency of the target game prop based on the actual duration item;

[0017] Step 3: Based on the comparison relationship between the actual proportion frequency and the frequency range item, the actual impact data is obtained, and based on the product relationship between the actual impact data and the actual duration item, the update duration item is obtained, and based on the matching of the update duration item and the interaction duration item, the emotional update level item is obtained.

[0018] Furthermore, the influencing factors also include source channels, and the method of emotional level classification includes:

[0019] S1: source classification, setting source mode, setting added values ​​based on the source mode, and then obtaining at least two added items according to the source mode;

[0020] S2: Source acquisition, obtaining the actual source of the target game props, and matching the corresponding added value to obtain the actual added item;

[0021] S3: Level determination, based on the combination result of the actual increase item and the actual duration item, the combination result is matched with the interaction duration item, and then the emotion secondary update level item is obtained.

[0022] Furthermore, the updating method also includes: obtaining an updated emotional value item based on the emotional secondary update level item, updating the evaluation of the value of the target game prop based on the combination result of the actual value item and the updated emotional value item, and re-evaluating the value of the target game prop when there are different ways to obtain the target game prop to obtain a more accurate emotional level of the target user for the target game prop.

[0023] Furthermore, the method of obtaining the emotional value item includes:

[0024] M1: Determine the value item, based on the emotion level item, set at least two value items, corresponding to the emotion level items respectively;

[0025] M2: Value determination, based on the multiplication of the added value item and the actual value item, obtain at least two emotional value items.

[0026] Furthermore, the method for obtaining the asset evaluation model includes:

[0027] N1: Ratio determination, based on the ratio relationship of the actual value items, the value ratio items are obtained;

[0028] N2: Ratio comparison, with years as the unit. There are multiple time segment items in a year. The ratio relationship between adjacent time segment items is obtained to get a ratio set. The ratio item of the time segment item corresponding to the value ratio item is selected from the ratio set as the comparison item to be compared with the value ratio item to get the comparison difference. The comparison threshold is set. When the comparison difference is less than the comparison threshold, the comparison item is used as the target item, and the asset valuation model is created with the remaining ratios in the ratio set. When the comparison difference is greater than the comparison threshold, the value ratio item is used as the target item, and the asset valuation model is created with the remaining ratios in the ratio set.

[0029] Furthermore, the updating and optimization method of the asset evaluation model includes: obtaining a real-time comparison item based on the comparison of the value information obtained in real time with the market value of the target game props in the previous time segment item, and selecting a ratio item of the time segment item corresponding to the real-time comparison item from the ratio set as a comparison item to compare with the real-time comparison item to obtain a real-time difference. When the real-time difference is greater than the comparison threshold, the real-time comparison item is used as a replacement item to optimize the asset evaluation model.

[0030] Furthermore, an automated asset receiving system based on a user asset evaluation model is used to implement the above-mentioned automated asset receiving party based on a user asset evaluation model.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The automated asset receiving method and system based on the user asset evaluation model first obtains the market value of the target game props and creates an asset evaluation model. Since different users have different emotions towards the target game props, the emotional levels are first divided, and according to the results of the emotional level division, the emotional values ​​corresponding to the different emotional levels are matched respectively. Then, according to the combined relationship between the emotional value and the actual value of the target game props, the value of the target game props is re-evaluated, and the target game props are received according to the results of the re-evaluation, thereby greatly improving the success rate of asset reception.

[0033] At the same time, the target game props are divided into emotional levels based on interaction frequency, source path, etc. The acquisition and combination of comprehensive data from multiple aspects can further improve the target users' emotional level towards the target game props, and then more accurately evaluate the value of the target game props to ensure successful asset reception. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 A schematic diagram of the relationship between market value acquisition, evaluation model establishment and value assessment update of the present invention;

[0035] Figure 2 It is a schematic diagram of the updating method flow of the present invention;

[0036] Figure 3 A schematic diagram of the interaction duration range of the present invention;

[0037] Figure 4 It is a schematic diagram of the frequency position of the present invention;

[0038] Figure 5 This is a schematic diagram showing that the contrast difference of the present invention is less than the contrast threshold;

[0039] Figure 6 This is a schematic diagram of the contrast difference being greater than the contrast threshold value of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Different game props assets of different users may have different emotional attachments to game props assets due to factors such as different sources and different usage times. For example, a game prop of a user is given by a friend. When it is time to sell it, the asset evaluation model can only give a value equal to the market price. However, since the game prop is given by a friend and has special meaning, the user will most likely not sell it when the same value as the market value is given, resulting in a failure to receive the game prop asset and a lower acceptance rate. The technical solution provided by the present application first obtains the market value of the target game prop and creates an asset evaluation model. However, since different users assign a certain value to the target game prop, the asset evaluation model will generate an asset evaluation model. The emotions given to game props are different, so the emotion levels are first divided, and according to the division results of the emotion levels, the emotion values ​​corresponding to different emotion levels are matched respectively, so as to re-evaluate the value of the target game props according to the combination relationship between the emotion value and the actual value of the target game props, and receive the target game props according to the results of the re-evaluation, which can greatly improve the success rate of asset reception, and comprehensively divide the emotion levels of target game props from multiple aspects such as interaction frequency and source channel. The comprehensive data acquisition and combination from multiple aspects can further improve the target users' emotion level for the target game props, and then more accurately evaluate the value of the target game props to ensure the successful reception of assets.

[0042] like Figure 1-Figure 2As shown, the present invention provides a technical solution: an automated asset receiving method and system based on a user asset evaluation model, comprising: market value acquisition: setting a time threshold to obtain at least two time segment items, respectively obtaining the market value of the target game props in different time segment items, and obtaining at least two actual value items; evaluation model establishment: predicting the subsequent value of the target game props based on the change trend of the actual value item, obtaining the predicted value item, and then obtaining the asset evaluation model, and updating and optimizing the asset evaluation model based on the value information obtained in real time, according to the asset evaluation model, the market value of the target game props can be predicted, which is convenient for evaluating the value of the target game props, and combined with the value information obtained in real time, the asset evaluation model is optimized to improve the evaluation accuracy; value evaluation update: based on the update method, firstly, the target game props are divided into emotional levels, and at least two actual value items are obtained. The invention discloses a method for obtaining a target game item by reducing two emotion level items, setting an assignment item, obtaining at least two emotion value items, re-evaluating the value of the target game item based on the actual value item and the emotion value item, obtaining an updated evaluation item, receiving the target game item based on the updated evaluation item, thereby improving the reception rate of user assets; the updating method comprises: classifying the emotion level of the target game item, setting influencing factors, the influencing factors comprising interaction time, setting at least two interaction time ranges, obtaining at least two interaction time items, classifying the levels based on the interaction time items, obtaining at least two emotion level items; obtaining the actual interaction time of the target game item, obtaining the actual time item, matching the actual time item with the interaction time item, obtaining the emotion actual level item, thereby obtaining the emotion actual value item corresponding to the matching result; and updating the evaluation of the value of the target game item based on the combination result of the actual value item and the emotion actual value item.

[0043] like Figure 3As shown, due to the influence of the frequency of value fluctuations of game props, the time threshold is set to one month, so that two time segment items can be obtained, such as 0-1 month and 1-2 months, and the market value of the target game props in these two time segment items is obtained respectively, and two actual value items are obtained. According to the change trend of the actual value items, an asset evaluation model is established to predict the market value of the target game props. Since different users have different emotions for the target game props, the emotional level is first divided into three levels, and three emotional level items are obtained, namely, favorite, normal and general. Since the influencing factors include interaction time, three interaction time ranges are set from the time the target user receives the target game props, namely, 0-100h, 100-500h and more than 500h, corresponding to general, normal and favorite respectively. Three interaction time items are obtained, and the target user's actual emotion level item for the target game prop is obtained by matching the actual interaction time with the set interaction range, thereby obtaining the emotion actual value item corresponding to the emotion actual level item, wherein the emotion actual value item is determined by the set assignment item. First, the market value of the target game prop is obtained, and an asset evaluation model is created. Since different users have different emotions for the target game prop, the emotion level is first divided, and according to the division results of the emotion level, the emotion values ​​corresponding to different emotion levels are matched respectively, so that according to the combination relationship between the emotion value and the actual value of the target game prop, the value of the target game prop is re-evaluated, and the target game prop is received according to the result of the re-evaluation, which can greatly improve the success rate of asset reception.

[0044] The interaction duration also includes the interaction frequency. The method of emotional level division includes: step 1: proportion range division, setting the proportion frequency, obtaining two frequency ranges based on the proportion frequency, obtaining frequency range items, and setting influence values ​​based on the frequency range items to obtain two influence data; step 2: actual proportion determination, obtaining the actual interaction frequency of the target user to the target game props, obtaining the actual frequency item, and obtaining the actual proportion frequency of the target game props based on the actual duration item; step 3: obtaining the actual influence data based on the comparison relationship between the actual proportion frequency and the frequency range item, and obtaining the update duration item based on the product relationship between the actual influence data and the actual duration item, and obtaining the emotional update level item based on matching the update duration item with the interaction duration item.

[0045] like Figure 4As shown, it should be noted that the interaction frequency is the frequency of users using the target game props, and the set percentage frequency is 50%. Based on the percentage frequency, two frequency ranges are obtained, namely 0-50% and 50%-100%. At this time, the set influence values ​​are 0.5 and 1.5, corresponding to 0-50% and 50%, respectively. According to the actual frequency of use of the target game props by the target user, the specific influence value is obtained, and the update duration is obtained according to the product relationship between the influence value and the actual duration item, and then the emotion update level item is obtained by matching.

[0046] In the specific implementation process, a user obtains a game prop 150 hours later. After data acquisition, it is found that the user actually uses the game prop for 50 hours, with a frequency of 33.33%. At this time, the impact value is 0.5, and the update time of the user is 75 hours. After matching, it is found that the user's emotional update level is general. At the same time, there is another user who obtains a game prop 90 hours later. After data acquisition, it is found that the user actually uses the game prop for 80 hours, with a frequency of 88.88%. At this time, the impact value is 1.5, and the update time of the user is 135 hours. After matching, it is found that the user's emotional update level is normal.

[0047] The influencing factors also include the source path. The method of emotional level division includes: S1: source classification, setting the source method, setting the added value based on the source method, and then obtaining at least two added items according to the source method; S2: source acquisition, obtaining the actual source of the target game props, and matching the corresponding added value, and then obtaining the actual added item; S3: level determination, based on the combination result of the actual added item and the actual duration item, matching the combination result with the interaction duration item, and then obtaining the emotional secondary update level item.

[0048] It should be noted that there are two sources, one is self-purchase and the other is gift from others. The added value is set based on the source method. The added values ​​are 1.0 and 1.5, corresponding to self-purchase and gift from others respectively. The corresponding added value is matched according to the actual source of the target game props to obtain the actual added item, and the interaction time is matched to the combination result in combination with the actual time item.

[0049] In the specific implementation process, it is 80 hours since a user obtained a certain game prop. After data acquisition, it is found that the user's target game prop is a gift from others. At this time, the matching increase value is 1.5, and the combination result is 80*1.5=120, and the emotional secondary update level item is normal; at the same time, it is 88 hours since a user obtained a certain game prop. After data acquisition, it is found that the user's target game prop is purchased by himself. At this time, the matching increase value is 1.0, and the combination result is 88*1.0=88, and the emotional secondary update level item is average.

[0050] The updating method also includes: obtaining an updated emotional value item based on the emotional secondary update level item, updating the evaluation of the value of the target game props based on the combination of the actual value item and the updated emotional value item, and re-evaluating the value of the target game props when there are different ways to obtain the target game props to obtain a more accurate emotional level of the target user for the target game props.

[0051] The methods for obtaining emotional value items include: M1: determining the value items, based on the emotional level items, setting at least two value items, which correspond to the emotional level items respectively; M2: determining the value, based on the product relationship between the value items and the actual value items, obtaining at least two emotional value items.

[0052] It should be noted that since there are three emotion level items, namely, like, normal and general, the number of set assignment items is also three, and the set assignment items are 0.2, 0.1 and 0.05, corresponding to like, normal and general respectively, and according to the product relationship between the assignment item and the actual value item, the three emotion value items are obtained.

[0053] In the specific implementation process, in the specific implementation process, a user needs to sell a game prop in his account in March. Through the asset evaluation model, the value of the game prop is 100 in January, 99 in February, and 98 in March. The data also shows that the user has obtained the target game prop for 200 hours, and the emotional level item is normal. Therefore, according to the actual value item of the normal level of emotion plus the actual value, the final value of the game prop is determined to be 98+98*0.1=107.8.

[0054] The method for obtaining an asset evaluation model includes: N1: ratio determination, based on the ratio relationship of actual value items, a value ratio item is obtained; N2: ratio comparison, with years as units, there are multiple time segment items in a year, the ratio relationship of adjacent time segment items is obtained, a ratio set is obtained, and the ratio item of the time segment item corresponding to the value ratio item is selected from the ratio set as a comparison item to be compared with the value ratio item to obtain a comparison difference, and a comparison threshold is set. When the comparison difference is less than the comparison threshold, the comparison item is used as the target item, and the asset evaluation model is created with the remaining ratios in the ratio set. When the comparison difference is greater than the comparison threshold, the value ratio item is used as the target item, and the asset evaluation model is created with the remaining ratios in the ratio set.

[0055] It should be noted that since there are two time segment items, the ratio of the actual value item is one at this time, and the ratios of multiple time segment items in the past data in units of years are obtained to obtain a ratio set. The ratio of the time segment item corresponding to the ratio of the actual value item is selected from the ratio set to compare the difference with the ratio of the actual value item, and the comparison threshold is set to ±5%.

[0056] like Figure 5-Figure 6 As shown in the figure, in the specific implementation process, the value of a game prop in 0-1 month and 1-2 month is 100 and 95 respectively. At this time, the ratio of the actual value item is 0.95, and the ratio of the game prop in multiple time segment items in the previous data with years as the unit is obtained. The ratio of 0-1 month and 1-2 month is 0.93. At this time, the comparison difference is -0.02, which does not exceed the comparison threshold. This means that the value change of the game prop last year and this year is small. Therefore, 0.93 is used as the target item, and the remaining ratios in the ratio set are used to create Asset valuation model; there is a game prop whose values ​​in 0-1 and 1-2 are 100 and 95 respectively. At this time, the ratio of the actual value item is 0.95. The ratio of multiple time segment items in the previous data with years as the unit is obtained, and the ratio of 0-1 and 1-2 is 1.02. At this time, the comparison difference is 0.07, which exceeds the comparison threshold. This means that the value change of the game prop last year and this year is quite different. Therefore, 0.95 is used as the target item, and the asset valuation model is created with the remaining ratios in the ratio set.

[0057] The updating and optimization method of the asset evaluation model includes: obtaining a real-time comparison item based on the comparison of the value information obtained in real time with the market value of the target game props in the previous time segment item, and selecting a ratio item of the time segment item corresponding to the real-time comparison item from the ratio set as a comparison item to compare with the real-time comparison item to obtain a real-time difference. When the real-time difference is greater than the comparison threshold, the real-time comparison item is used as a replacement item to optimize the asset evaluation model.

[0058] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. An automated asset receiving method based on a user asset evaluation model, characterized in that: include: Market value acquisition: set a time threshold, obtain at least two time segment items, obtain the market value of the target game props in different time segment items, and obtain at least two actual value items; Evaluation model establishment: predict the subsequent value of the target game props based on the change trend of the actual value item, obtain the predicted value item, and then obtain the asset evaluation model, and update and optimize the asset evaluation model based on the value information obtained in real time. According to the asset evaluation model, the market value of the target game props can be predicted, which is convenient for evaluating the value of the target game props. In addition, the asset evaluation model is optimized in combination with the value information obtained in real time to improve the evaluation accuracy; Value evaluation update: Based on the update method, the target game props are first divided into emotional levels to obtain at least two emotional level items, and the assignment items are set to obtain at least two emotional value items. Based on the actual value items and the emotional value items, the value of the target game props is re-evaluated to obtain updated evaluation items. The target game props are received based on the updated evaluation items, thereby improving the acceptance rate of user assets; The updating method includes: Duration confirmation: emotional level classification of target game props, setting influencing factors, the influencing factors include interaction duration, setting at least two interaction duration ranges, obtaining at least two interaction duration items, and performing level classification based on the interaction duration items to obtain at least two emotional level items; Information acquisition: obtaining the actual interaction time of the target game props, obtaining the actual time item, matching the actual time item with the interaction time item, obtaining the actual emotional level item, and thus obtaining the actual emotional value item corresponding to the matching result; Evaluation update: Based on the combined results of the actual value item and the emotional actual value item, the value of the target game prop is updated and evaluated.

2. The method for automatically receiving assets based on a user asset evaluation model according to claim 1, characterized in that: The interaction duration also includes the interaction frequency, and the method of emotional level division includes: Step 1: Divide the proportion range, set the proportion frequency, obtain two frequency ranges based on the proportion frequency, obtain frequency range items, and set the influence values ​​based on the frequency range items to obtain two influence data; Step 2: Determine the actual proportion, obtain the actual interaction frequency of the target user to the target game prop, obtain the actual frequency item, and obtain the actual proportion frequency of the target game prop based on the actual duration item; Step 3: Based on the comparison relationship between the actual proportion frequency and the frequency range item, the actual impact data is obtained, and based on the product relationship between the actual impact data and the actual duration item, the update duration item is obtained, and based on the matching of the update duration item and the interaction duration item, the emotional update level item is obtained.

3. The method for automatically receiving assets based on a user asset evaluation model according to claim 1, characterized in that: The influencing factors also include source channels, and the methods for dividing the emotional levels include: S1: source classification, setting source mode, setting added values ​​based on the source mode, and then obtaining at least two added items according to the source mode; S2: Source acquisition, obtaining the actual source of the target game props, and matching the corresponding added value to obtain the actual added item; S3: Level determination, based on the combination result of the actual increase item and the actual duration item, the combination result is matched with the interaction duration item, and then the emotion secondary update level item is obtained.

4. The method for automatically receiving assets based on a user asset evaluation model according to claim 3, characterized in that: The updating method also includes: obtaining an updated emotional value item based on the emotional secondary update level item, updating and evaluating the value of the target game prop based on the combination result of the actual value item and the updated emotional value item, and re-evaluating the value of the target game prop when there are different ways to obtain the target game prop to obtain a more accurate emotional level of the target user for the target game prop.

5. The method for automatically receiving assets based on a user asset evaluation model according to claim 1, characterized in that: The method of obtaining the emotional value item includes: M1: Determine the value item, based on the emotion level item, set at least two value items, corresponding to the emotion level items respectively; M2: Value determination, based on the multiplication of the added value item and the actual value item, obtain at least two emotional value items.

6. The method for automatically receiving assets based on a user asset evaluation model according to claim 1, characterized in that: The method for obtaining the asset evaluation model includes: N1: Ratio determination, based on the ratio relationship of the actual value items, the value ratio items are obtained; N2: Ratio comparison, with years as the unit. There are multiple time segment items in a year. The ratio relationship between adjacent time segment items is obtained to get a ratio set. The ratio item of the time segment item corresponding to the value ratio item is selected from the ratio set as the comparison item to be compared with the value ratio item to get the comparison difference. The comparison threshold is set. When the comparison difference is less than the comparison threshold, the comparison item is used as the target item, and the asset valuation model is created with the remaining ratios in the ratio set. When the comparison difference is greater than the comparison threshold, the value ratio item is used as the target item, and the asset valuation model is created with the remaining ratios in the ratio set.

7. The method for automatically receiving assets based on a user asset evaluation model according to claim 6, characterized in that: The updating and optimization method of the asset evaluation model includes: obtaining a real-time comparison item based on the comparison of the value information obtained in real time with the market value of the target game props in the previous time segment item, and selecting a ratio item of the time segment item corresponding to the real-time comparison item from the ratio set as a comparison item to compare with the real-time comparison item to obtain a real-time difference. When the real-time difference is greater than the comparison threshold, the real-time comparison item is used as a replacement item to optimize the asset evaluation model.

8. An automated asset receiving system based on a user asset evaluation model, characterized in that: Used to implement an automated asset receiving method based on a user asset evaluation model as described in any one of claims 1-7.

Images