Parameter updating method and device for article ownership change

Abstract

The invention discloses a parameter updating method and device for article ownership change. A specific embodiment of the method comprises the steps of determining a numerical value interval of ownership influence parameters of a target article according to sales data of the target article; determining the number of parameter updating times corresponding to the numerical interval; determining an estimated time interval for executing the ownership change process of the target article, wherein the estimated time interval corresponds to the numerical interval; in the process of updating the ownership influence parameter based on the numerical value interval, the estimated time interval and the number of parameter updating times, the estimated time interval is adjusted according to current behavior data of a user associated with the target article, an adjusted time interval is obtained, and the ownership influence parameter is in a descending trend in the updating process; and in the adjusted time interval, updating the ownership influence parameter according to the numerical value interval and the parameter updating frequency. The personalized parameter updating strategy in the application can improve the interactivity and activeness of the user in the parameter updating process, and is helpful to improve the ownership change efficiency of the target article.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, specifically to the field of e-commerce technology, and more particularly to a parameter updating method, device, computer-readable medium, and electronic device for changing the ownership of an item. Background Art

[0002] A Dutch auction is a reverse bidding auction involving one seller and multiple buyers. Once a round of bidding begins, the price of an item decreases gradually from the starting price. The price and duration of this price reduction process are simultaneously disclosed to all buyers. An auction round can terminate in two ways: 1) the round is "sold," meaning one buyer accepts the price and purchases the item; 2) the round fails, meaning the price remains unsold even after reaching the reserve price.

[0003] Although the existing online Dutch auction system platform can support the auction of a large number of items, the bidding strategy for all items is consistent, that is, the prices of items are evenly reduced throughout the auction process. Summary of the Invention

[0004] The embodiments of the present application provide a parameter updating method, apparatus, computer-readable medium, electronic device, and computer program product for changing the ownership of an item.

[0005] In a first aspect, an embodiment of the present application provides a parameter update method for changing the ownership of an item, comprising: determining a numerical interval of an ownership impact parameter of the target item based on the sales data of the target item; determining the number of parameter updates corresponding to the numerical interval; determining an estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; in the process of updating the ownership impact parameter based on the numerical interval, the estimated time interval and the number of parameter updates, adjusting the estimated time interval according to the current behavior data of the user associated with the target item to obtain an adjusted time interval, wherein the ownership impact parameter shows a downward trend during the update process; within the adjusted time interval, updating the ownership impact parameter according to the numerical interval and the number of parameter updates.

[0006] In some examples, in the process of updating the ownership influence parameter based on the numerical interval, the estimated time interval and the number of parameter updates, the estimated time interval is adjusted according to the current behavior data of the user associated with the target item to obtain the adjusted time interval, including: determining the update moments corresponding to the number of parameter updates and the parameter update operations within the estimated time interval; determining the numerical value corresponding to the parameter update operation within the numerical interval; in the process of updating the ownership influence parameter based on the update moment and the numerical value, the estimated time interval is adjusted according to the current behavior data of the user to obtain the adjusted time interval.

[0007] In some examples, the above-mentioned determination of the update time corresponding to each parameter update operation of the number of parameter updates within the estimated time interval includes: determining the update time corresponding to the parameter update operation based on the estimated time interval, the number of parameter updates and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influence parameter; and the above-mentioned determination of the numerical value corresponding to the parameter update operation within the numerical range includes: determining the numerical value corresponding to the parameter update operation based on the numerical range, the number of parameter updates and the constraint range.

[0008] In some examples, the above-mentioned adjustment of the estimated time interval based on the user's current behavior data to obtain the adjusted time interval includes: adjusting the adjustment ratio for the initial time point based on the user's current behavior data, wherein multiple estimated time intervals are obtained by dividing the time range based on the initial time point, and the multiple estimated time intervals correspond one-to-one to the multiple numerical intervals; adjusting the initial time point according to the adjustment ratio to obtain the adjusted time point; and dividing the time range into multiple adjusted time intervals according to the adjusted time point.

[0009] In some examples, the above-mentioned adjustment of the adjustment ratio for the initial time point based on the user's current behavior data includes: normalizing the behavior data of multiple dimensions in the user's current behavior data to obtain multiple normalized behavior features; obtaining a feature value based on the multiple normalized behavior features; and determining the adjustment ratio based on the comparison result of the feature value and the preset value.

[0010] In some examples, the above-mentioned determination of the update time corresponding to the parameter update operation based on the estimated time interval, the number of parameter updates and the constraint range includes: determining the sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determining the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the number of parameter updates and the parameter update operations; determining the update time corresponding to the parameter update operation based on the proportion and the estimated time interval.

[0011] In some examples, the above-mentioned determination of the numerical value corresponding to the parameter update operation based on the numerical interval, the number of parameter updates and the constraint range includes: determining the sampling moment corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determining the proportion of the sampling moment corresponding to the parameter update operation in the sum of the sampling moments corresponding to the number of parameter updates and the parameter update operations; and determining the numerical value corresponding to the parameter update operation based on the proportion and the numerical interval.

[0012] In some examples, the above-mentioned updating of ownership impact parameters within the adjusted time interval according to the numerical interval and the number of parameter updates includes: determining the adjusted update time corresponding to the parameter update operations that have not been executed within the estimated time interval according to the adjusted time interval, the number of parameter updates and the constraint range; for the parameter update operations that have not been executed, at the adjusted update time, updating the ownership impact parameters according to the numerical values ​​corresponding to the parameter update operations that have not been executed.

[0013] In some examples, the above-mentioned sales data is the correspondence data between the historical values ​​of the ownership impact parameters and the historical quantities of the target items that have undergone ownership changes, which are formed based on the user's ownership change behavior, and the above-mentioned sales data of the target items is used to determine the numerical range of the ownership impact parameters of the target items, including: dividing the numerical range of the ownership impact parameters into multiple numerical intervals according to the correspondence data.

[0014] In some examples, the above-mentioned method divides the numerical range of the ownership influence parameter into multiple numerical intervals based on the corresponding relationship data, including: deleting part of the corresponding relationship data related to abnormal historical values ​​to obtain the cleaned corresponding relationship data; based on the cleaned corresponding relationship data, counting the cumulative historical number of each historical value of the ownership influence parameter as of the cleaned corresponding relationship data; and dividing the numerical range into multiple numerical intervals based on the cumulative historical number.

[0015] In some examples, the above-mentioned determination of the number of parameter updates corresponding to the numerical interval includes: determining the update number range corresponding to the parameter update number based on the estimated time interval and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influence parameter; and determining the parameter update number based on uniformly distributed sampling within the update number range.

[0016] In a second aspect, an embodiment of the present application provides a parameter updating device for changing the ownership of an item, comprising: a numerical interval determining unit, configured to determine the numerical interval of the ownership influencing parameter of the target item based on the sales data of the target item; a number determining unit, configured to determine the number of parameter updates corresponding to the numerical interval; a time interval determining unit, configured to determine the estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; a time interval adjusting unit, configured to adjust the estimated time interval according to the current behavior data of the user associated with the target item in the process of updating the ownership influencing parameter based on the numerical interval, the estimated time interval and the number of parameter updates, to obtain an adjusted time interval, wherein the ownership influencing parameter shows a downward trend during the updating process; and a parameter updating unit, configured to update the ownership influencing parameter according to the numerical interval and the number of parameter updates within the adjusted time interval.

[0017] In some examples, the time interval adjustment unit is further configured to: determine the update times corresponding to the number of parameter update operations and the parameter update operations within the estimated time interval; determine the numerical values ​​corresponding to the parameter update operations within the numerical range; and in the process of updating the ownership influence parameter based on the update time and the numerical value, adjust the estimated time interval according to the user's current behavior data to obtain the adjusted time interval.

[0018] In some examples, the above-mentioned time interval adjustment unit is further configured to: determine the update time corresponding to the parameter update operation based on the estimated time interval, the number of parameter updates and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership impact parameter; determine the numerical value corresponding to the parameter update operation based on the numerical interval, the number of parameter updates and the constraint range.

[0019] In some examples, the above-mentioned time interval adjustment unit is further configured to: adjust the adjustment ratio for the initial time point based on the user's current behavior data, wherein multiple estimated time intervals are obtained by dividing the time range based on the initial time point, and the multiple estimated time intervals correspond one-to-one to multiple numerical intervals; adjust the initial time point according to the adjustment ratio to obtain the adjusted time point; and divide the time range into multiple adjusted time intervals according to the adjusted time point.

[0020] In some examples, the above-mentioned time interval adjustment unit is further configured to: normalize the behavioral data of multiple dimensions in the user's current behavioral data to obtain multiple normalized behavioral features; obtain a feature value based on the multiple normalized behavioral features; and determine the adjustment ratio based on the comparison result of the feature value and the preset value.

[0021] In some examples, the above-mentioned time interval adjustment unit is further configured to: determine the sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations; and determine the update time corresponding to the parameter update operation based on the proportion and the estimated time interval.

[0022] In some examples, the above-mentioned time interval adjustment unit is further configured to: determine the sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations; and determine the numerical value corresponding to the parameter update operation based on the proportion and the numerical interval.

[0023] In some examples, the above-mentioned parameter update unit is further configured to: determine the adjusted update time corresponding to the parameter update operation that was not executed within the estimated time interval based on the adjusted time interval, the number of parameter updates and the constraint range; for the parameter update operation that was not executed, at the adjusted update time, update the ownership impact parameter according to the numerical value corresponding to the parameter update operation that was not executed.

[0024] In some examples, the above-mentioned sales data is correspondence data between the historical values ​​of the ownership impact parameters and the historical quantities of the target items that have undergone ownership changes, which are formed based on the user's ownership change behavior, and the above-mentioned numerical interval determination unit is further configured to: divide the numerical range of the ownership impact parameters into multiple numerical intervals according to the correspondence data.

[0025] In some examples, the above-mentioned numerical interval determination unit is further configured to: delete part of the corresponding relationship data related to abnormal historical values ​​in the corresponding relationship data to obtain the cleaned corresponding relationship data; based on the cleaned corresponding relationship data, count the cumulative historical number of each historical value up to the ownership influence parameter; and divide the numerical range into multiple numerical intervals based on the cumulative historical number.

[0026] In some examples, the above-mentioned number determination unit is further configured to determine the update number range corresponding to the parameter update number based on the estimated time interval and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influence parameter; and determine the parameter update number based on uniformly distributed sampling within the update number range.

[0027] In a third aspect, an embodiment of the present application provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

[0028] In a fourth aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect.

[0029] The parameter updating method and device for item ownership change provided in the embodiments of the present application determine the numerical range of the ownership impact parameter of the target item based on the sales data of the target item; determine the number of parameter updates corresponding to the numerical range; determine the estimated time range for executing the ownership change process of the target item, wherein the estimated time range corresponds to the numerical range; in the process of updating the ownership impact parameter based on the numerical range, the estimated time range and the number of parameter updates, the estimated time range is adjusted according to the current behavior data of the user associated with the target item to obtain the adjusted time range, and the ownership impact parameter shows a downward trend during the update process; within the adjusted time range, the ownership impact parameter is updated according to the numerical range and the number of parameter updates, thereby providing a method for updating the ownership impact parameter of the target item in combination with the sales data related to the target item and the current behavior data of the user, and the personalized parameter update strategy can improve the interactivity and activity of the user during the parameter update process, and help improve the efficiency of the ownership change of the target item. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Other features, objects and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0031] Figure 1 is an exemplary system architecture diagram in which an embodiment of the present application may be applied;

[0032] Figure 2 is a flowchart of an embodiment of a parameter updating method for changing item ownership according to the present application;

[0033] Figure 3 is a schematic diagram of an application scenario of the parameter updating method for changing item ownership according to this embodiment;

[0034] Figure 4 is a flow chart of another embodiment of a parameter updating method for item ownership change according to the present application;

[0035] Figure 5 This is a structural diagram of an embodiment of a parameter updating device for changing item ownership according to the present application;

[0036] Figure 6 It is a structural diagram of a computer system suitable for implementing the embodiments of the present application. DETAILED DESCRIPTION

[0037] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0038] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0039] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, and storage of user personal information involved in the technical solutions disclosed herein all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken with respect to user personal information to prevent unauthorized access to user personal information data and to safeguard the security of user personal information, network security, and national security.

[0040] Figure 1 An exemplary architecture 100 is shown to which the parameter updating method and apparatus for item ownership change of the present application can be applied.

[0041] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. The communication connections between terminal devices 101, 102, and 103 constitute a topological network, and network 104 is used to provide a medium for communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0042] The terminal devices 101, 102, 103 can interact with the server 105 via the network 104 to receive or send data, etc. The terminal devices 101, 102, 103 can be hardware devices or software that support network connection for data interaction and data processing. When the terminal devices 101, 102, 103 are hardware, they can be various electronic devices that support network connection, information acquisition, interaction, display, processing and other functions, including but not limited to smart phones, car computers, tablet computers, e-book readers, laptop computers and desktop computers, etc. When the terminal devices 101, 102, 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software or software modules for providing distributed services, for example, or they can be implemented as a single software or software module. No specific limitation is made here.

[0043] Server 105 may be a server that provides various services, such as a backend processing server that updates the ownership impact parameters of the target item based on the sales data of the target item and the user's current behavior data provided by terminal devices 101, 102, and 103. As an example, server 105 may be a cloud server.

[0044] It should be noted that the server can be either hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software or software modules (e.g., software or software modules for providing distributed services), or as a single software or software module. No specific limitations are given here.

[0045] It should also be noted that the parameter updating method for item ownership change provided in the embodiments of this application is generally executed by a server, but this does not rule out the possibility of execution by a terminal device, or of a server and a terminal device cooperating with each other. Accordingly, the various components (e.g., various units) included in the parameter updating device for item ownership change can be entirely located in the server, entirely located in the terminal device, or separately located in the server and the terminal device.

[0046] It should be understood that Figure 1 The number of terminal devices, networks, and servers in the system is merely illustrative. Any number of terminal devices, networks, and servers may be provided as needed. When the electronic device on which the parameter update method for changing item ownership is running does not need to transmit data with other electronic devices, the system architecture may only include the electronic device (e.g., a server or terminal device) on which the parameter update method for changing item ownership is running.

[0047] Continue to refer Figure 2 , shows a process 200 of an embodiment of a parameter update method for item ownership change, including the following steps:

[0048] Step 201: Determine the numerical range of the ownership influencing parameter of the target item based on the sales data of the target item.

[0049] In this embodiment, the execution subject of the parameter update method for changing the ownership of an item (for example Figure 1 The server in the example embodiment can obtain sales data associated with the target item remotely or locally through a wired network connection or a wireless network connection, and determine the numerical range of the ownership influencing parameter of the target item based on the sales data of the target item.

[0050] The ownership influencing parameters of the target item are parameters that can affect the ownership of the target item when the owner of the target item allows the ownership of the target item to be changed.

[0051] For example, a process allowing for a change in ownership of a target item is an auction process for the target item, where the ownership-affecting parameters include, for example, the price, quantity, and volume of the target item. During the auction process, if a bidder approves the owner's bid for the target item, the bidder can proceed with the target item's ownership change, transferring the rights corresponding to the target item from the original owner to the bidder.

[0052] The sales data associated with the target item may be data generated by the user's purchasing behavior during the target item's historical ownership changes, for example, data such as the user's historical transaction volume during the update of the target item's ownership influencing parameters.

[0053] In this embodiment, based on the sales data of the target item, the execution entity can analyze the numerical range of the ownership influencing parameter of the target item with a higher transaction success rate. In this embodiment, the execution entity can determine one or more continuous data intervals.

[0054] In some implementations of this embodiment, the sales data is correspondence data between historical values ​​of ownership influencing parameters and historical quantities of target items that have undergone ownership changes, which are generated based on the user's ownership change behavior.

[0055] Taking the ownership influencing parameter as the price parameter as an example, the above-mentioned execution entity can extract the order data of the historical time period related to the target item (for example, within the past year), clean up the final price and sales quantity of each order, and add up the sales quantity of the same final price to obtain the historical "price-sales volume" data of the target item, that is, the commodity quantity-price relationship model, to represent the corresponding relationship data between the historical values ​​of the ownership influencing parameter and the historical quantity of the target item that has undergone ownership changes.

[0056] In this implementation, the execution subject may perform step 201 in the following manner: dividing the numerical range of the ownership influence parameter into a plurality of numerical intervals according to the corresponding relationship data.

[0057] As an example, the execution entity may determine the change rate of the historical quantity according to the corresponding relationship data, and then divide adjacent historical values ​​with similar change rates into a numerical interval to obtain multiple numerical intervals.

[0058] In this implementation, multiple numerical ranges are determined based on the correspondence data between the historical numerical values ​​representing the ownership influencing parameters and the historical quantities of the target items that have undergone ownership changes, which helps to improve the rationality of the numerical ranges.

[0059] In some optional implementations of this embodiment, the execution entity may determine multiple numerical intervals in the following manner:

[0060] First, part of the corresponding relationship data related to abnormal historical values ​​is deleted to obtain cleaned corresponding relationship data.

[0061] As an example, the above execution entity can determine the abnormal history value p by the following formula: abnormal :

[0062]

[0063] Among them, p i Indicates historical values.

[0064] Then, based on the cleaned corresponding relationship data, the cumulative historical quantity of each historical value up to the ownership influence parameter is counted.

[0065] As an example, the execution entity may determine the cumulative historical quantity of each historical value of the ownership impact parameter by the following formula:

[0066]

[0067] Among them, sale i is the historical value p i The historical quantity sold at the time.

[0068] The proportion of the cumulative historical quantity corresponding to each historical value is determined by the following formula:

[0069]

[0070] Finally, the numerical range is divided into multiple numerical intervals based on the accumulated historical quantity.

[0071] As an example, you can use a high sales price (p b ), low sales price (p c ) divides the value range into multiple value intervals. Continuing with the example of the ownership influencing parameter being the price parameter, the maximum price in the price set with a cumulative sales volume of less than 60% is taken as the high-movement sales price (p b The maximum price in the price set with cumulative sales volume less than 90% is taken as the low moving price (p c ).

[0072] High sales price p b =max({p i ,cumratio i <60%})(Formula 6)

[0073] Low sales price c =max({p i ,cumratio i <90%})(Formula 7)

[0074] Among them, based on the high dynamic selling price (p b ), low sales price (p c )'s numerical interval division logic is as follows: the historical transaction volume within the price range of "reserve price to high moving price" accounts for 60% of the total sales volume, the historical transaction volume within the price range of "high moving price to low moving price" accounts for 30% of the total sales volume, and the historical transaction volume within the price range of "low moving price to starting price" accounts for 10% of the total order volume.

[0075] In this implementation, a specific implementation method for determining a numerical interval based on corresponding relationship data is provided, which improves the rationality of the numerical interval and helps to improve the interactivity and activity of users during the parameter update process.

[0076] Step 202: Determine the number of parameter updates corresponding to the numerical interval.

[0077] In this embodiment, the execution entity may determine the number of parameter updates corresponding to the numerical interval.

[0078] Within the numerical range of the ownership impact parameter, the ownership impact parameter can be updated through multiple parameter update operations.

[0079] As an example, the execution entity may determine the number of parameter updates corresponding to the numerical interval in a random manner.

[0080] As another example, the execution entity may determine a range of optional parameter update times based on the length of the numerical interval, and then randomly determine the number of parameter updates corresponding to the numerical interval within the optional range. The numerical length is the difference between the starting and ending values ​​of the numerical interval.

[0081] In some implementations of this embodiment, the execution entity may perform step 202 as follows:

[0082] First, based on the estimated time interval and constraint range, determine the update number range corresponding to the number of parameter updates.

[0083] The constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership impact parameter.

[0084] In this implementation, the execution subject can determine the update frequency range by the following formula [f min ,f max ].

[0085]

[0086] Among them, ceil means rounding up, floor means rounding down, (cmin ,c max ) indicates the constraint range.

[0087] Second, the number of parameter updates is determined based on uniformly distributed sampling within the range of update times.

[0088] As an example, the execution entity may determine the number of parameter updates in the following manner:

[0089] Uniform distribution sampler:

[0090] Probability density function

[0091] In this implementation, a specific method for determining the number of parameter updates is provided, which improves the rationality and accuracy of the number of parameter updates and helps to further improve the interactivity and activity of users during the parameter update process.

[0092] Step 203: Determine an estimated time interval for executing the ownership change process of the target item.

[0093] In this embodiment, the execution entity may determine an estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to a numerical value interval.

[0094] During the estimated time interval, the ownership impact parameter of the target item can be updated within a numerical range. That is, each parameter update operation occurs within the estimated time interval, and the updated ownership impact parameter value is within the numerical range. If step 201 determines multiple numerical ranges, step 203 also determines multiple estimated time intervals corresponding to the multiple numerical ranges.

[0095] As an example, the execution entity may analyze the sales data of the target item to determine an estimated time interval with a higher transaction success rate.

[0096] As another example, the execution entity may determine, based on the numerical length of the numerical interval, an estimated time interval of a time length that matches the numerical length.

[0097] Step 204 , in the process of updating the ownership influence parameter based on the numerical interval, the estimated time interval and the parameter update times, the estimated time interval is adjusted according to the current behavior data of the user associated with the target item to obtain an adjusted time interval.

[0098] In this embodiment, the execution entity may adjust the estimated time interval based on the user's current behavior data associated with the target item during the process of updating the ownership impact parameter based on the value interval, estimated time interval, and parameter update count to obtain an adjusted time interval. The ownership impact parameter exhibits a downward trend during the update process.

[0099] In this embodiment, first, for each parameter update operation in the parameter update number parameter update operations, the execution entity may randomly determine an updated value for the ownership impact parameter of this parameter update operation within a value range, and randomly determine an update time for the ownership impact parameter of this parameter update operation within an estimated time range. Then, in the process of updating the ownership impact parameter based on the determined update value and update time, the execution entity may collect current user behavior data associated with the target item, and adjust the estimated time range based on the current user behavior data to obtain an adjusted time range.

[0100] The user's current behavior data refers to the behavior data exhibited by the user during the change of ownership influencing parameters within the estimated time interval, including but not limited to the number of auction reservations, the number of real-time buyers watching, the number of buyer interactions (comments, likes, follows, reposts), the average length of stay of buyers, etc.

[0101] For example, when the user's current behavior data indicates that the user is highly active and is more interested in the current explanation process of the target item, the length of the estimated time interval can be appropriately increased to obtain an adjusted time interval.

[0102] The operation of obtaining an adjusted time interval based on the estimated time interval can be performed once or multiple times. In the case of multiple times, the execution subject can collect the user's current behavior data within the preset time interval at each preset time interval, and adjust the estimated time interval based on the user's current behavior data to obtain the adjusted time interval.

[0103] In some optional implementations of this embodiment, the execution mechanism may perform step 204 as follows:

[0104] The first step is to determine the update times corresponding to the parameter update times and parameter update operations within the estimated time interval.

[0105] As an example, for each parameter update operation in the parameter update number parameter update operations, its corresponding update time is randomly determined between the update time corresponding to the previous parameter update operation and the end of the estimated time interval. For the first parameter update operation in the estimated time interval, its update time can be randomly determined within the estimated time interval.

[0106] As another example, the time intervals between adjacent parameter update operations are consistent. Based on the estimated time length of the time interval and the number of parameter updates, the time intervals between adjacent parameter update operations are determined to determine the update time corresponding to each parameter update operation.

[0107] The second step is to determine the value corresponding to the parameter update operation within the value range.

[0108] As an example, for each parameter update operation in the parameter update number parameter update operations, its corresponding value is randomly determined between the value corresponding to the previous parameter update operation and the end of the value interval. For the first parameter update operation within the estimated time interval, its value can be randomly determined within the value interval.

[0109] As another example, the numerical differences between adjacent parameter update operations are consistent, and the numerical differences between adjacent parameter update operations are determined based on the numerical range of the numerical interval and the number of parameter updates to determine the numerical value corresponding to each parameter update operation.

[0110] The third step is to adjust the estimated time interval according to the user's current behavior data during the process of updating the ownership influence parameters based on the update time and value to obtain the adjusted time interval.

[0111] For each parameter update operation, in response to the current time being the update time of this parameter update operation, the ownership influence parameter is updated according to the value of this parameter update operation.

[0112] In this implementation, the execution entity may determine the adjusted time interval by referring to the determination method in step 204, which will not be described in detail here.

[0113] In this implementation, the updating process of the ownership impact parameters and the determination process of the adjusted time interval are clarified, which further improves the flexibility of the updating process and the accuracy of the adjusted time interval.

[0114] In some optional implementations of this embodiment, the execution entity may perform the first step as follows: determining the update time corresponding to the parameter update operation within the estimated time interval based on the estimated time interval, the number of parameter updates, and the constraint range. The constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership impact parameter.

[0115] As an example, for each non-first parameter update operation in the parameter update number, the execution entity may randomly determine the update time of the current parameter update operation based on the update time of the previous parameter update operation, subject to the constraint range. Furthermore, it is necessary to ensure that the update time of all parameter update operations is within the estimated time interval.

[0116] The update time of the first parameter update operation within the estimated time interval may be determined based on the starting time point of the estimated time interval and within the constraints of the constraint range.

[0117] In this implementation, the execution subject may perform the second step in the following manner: determining a value corresponding to the parameter update operation according to a value interval, the number of parameter updates, and a constraint range.

[0118] As an example, for an update time corresponding to a parameter update operation determined according to the parameter update times and the constraint range, a value corresponding to the parameter update operation is randomly determined within a value interval.

[0119] In this embodiment, a method for determining the numerical value and update time corresponding to the parameter update operation is provided, which improves the rationality of the parameter update operation and helps to further improve the interactivity and activity of users during the parameter update process.

[0120] In some optional implementations of this embodiment, the execution entity may perform the update time determination process in the following manner:

[0121] First, based on uniformly distributed sampling within the constraint range, the sampling time corresponding to the parameter update operation is determined.

[0122] As an example, the execution entity may determine the sampling time corresponding to the parameter update operation by the following formula.

[0123] Uniform distribution sampler: Probability density function

[0124] Among them, (c min ,c max ) indicates the constraint range.

[0125] Then, the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling time corresponding to the parameter update number and the parameter update operations is determined.

[0126] Finally, the update time corresponding to the parameter update operation is determined based on the ratio and the estimated time interval.

[0127] As an example, the execution entity can determine the update time corresponding to the parameter update operation by the following formula:

[0128]

[0129] Among them, wn i represents the sampling time corresponding to the i-th parameter update operation, Indicates the number of parameter updates (freq) and the sum of the sampling times corresponding to the parameter update operations, amount t Indicates the length of the estimated time interval.

[0130] In this implementation, a specific method for determining the update time corresponding to the parameter update operation is provided. Based on uniformly distributed sampling within the constraint range, the rationality of the determined update time is further improved, which helps to further improve the interactivity and activity of users during the parameter update process.

[0131] In some optional implementations of this embodiment, the execution entity may perform the process of determining the above-mentioned value in the following manner:

[0132] First, based on uniformly distributed sampling within the constraint range, the sampling time corresponding to the parameter update operation is determined.

[0133] As an example, the execution entity may determine the sampling time corresponding to the parameter update operation by the following formula.

[0134] Uniform distribution sampler: Probability density function

[0135] Among them, (c min ,c max ) indicates the constraint range.

[0136] Then, the ratio of the sampling time corresponding to the parameter update operation to the total sampling time corresponding to the parameter update number and parameter update operations is determined. Finally, the value corresponding to the parameter update operation is determined based on the ratio and the value interval.

[0137] As an example, the execution entity can determine the value corresponding to the parameter update operation through the following formula:

[0138]

[0139] Among them, wn i represents the sampling time corresponding to the i-th parameter update operation, Indicates the number of parameter updates (freq) and the sum of the sampling times corresponding to the parameter update operations, amount m Indicates the length of the numeric range.

[0140] In this implementation, a specific method for determining the numerical value corresponding to the parameter update operation is provided. Based on uniformly distributed sampling within the constraint range, the rationality of the determined numerical value is further improved, which helps to further improve the interactivity and activity of users during the parameter update process.

[0141] In some optional implementations of this embodiment, the execution entity may perform the third step in the following manner:

[0142] First, adjust the adjustment ratio for the initial time point based on the user's current behavior data.

[0143] The multiple estimated time intervals are obtained by dividing the time range based on the initial time point, and the multiple estimated time intervals correspond to the multiple value intervals one by one.

[0144] The time range is a predetermined time range within which the ownership change process of the target item can be executed, for example, a time range specified by the owner of the target item (auctioneer).

[0145] Taking the Dutch auction as an example, the total duration (t total ) is based on the real-time buyer user behavior data and calculates the time point of high selling price (t b ), low selling price time point (t c ), and finally join the auction start time (t a =0) and auction end time (t d =t total Thus, a key interval is formed between each adjacent time point, and the four key time points divide the time range into three key time intervals, namely, the popularity interval (auction start time point → low sales time point, [t d ,t c ]), emotional adjustment interval (low sales time point → high sales time point, [t c ,t b ]), breakthrough range (high sales time point → auction end time point, [t b ,t a ]).

[0146] As an example, the execution subject can determine the initial time point by the following initial time point calculation model. The input of the initial time point calculation model is the total duration t of the time range. total , the output is the initial value of the high moving selling price time point (t b ), the initial value of the low moving price time point (t c ).

[0147]

[0148] For example:

[0149] t c =0.2*t total , making the popularity gathering period account for 20% of the total duration, which is relatively short;

[0150] tb =0.8*t total , which makes the mood adjustment interval account for 60% of the total time (60%=80%-20%), which is relatively long; the final breakthrough period accounts for 20% of the total time (20%=1-80%), which is relatively short.

[0151] In the parameter update process of multiple estimated time intervals determined by the initial time point, when the user's current behavior data indicates that the user is highly active and is more interested in the explanation process of the target item, the length of the estimated time interval can be increased according to a preset adjustment ratio to obtain an adjusted time interval; when the user's current behavior data indicates that the user is less active and is not interested in the explanation process of the target item, the length of the estimated time interval can be reduced according to a preset adjustment ratio to obtain an adjusted time interval.

[0152] Then, the initial time point is adjusted according to the adjustment ratio to obtain the adjusted time point.

[0153] Finally, the time range is divided into multiple adjusted time intervals according to the adjusted time points.

[0154] Taking the adjustment ratio f(x) as an example, the above execution entity can adjust the initial time point using the following formula:

[0155] t b =t b *(1+f(x))

[0156] t c =t c *(1+f(x))

[0157] After obtaining the adjusted time point, the time range can be divided into multiple adjusted time intervals according to the adjusted time point.

[0158] In this implementation, the length of the time interval is adjusted based on the user's current behavior data during the update process of the ownership impact parameters, which improves the adaptability of the ownership change process to the user's real-time behavior data and helps to further improve the user's interactivity and activity during the parameter update process.

[0159] In some optional implementations of this embodiment, the execution entity may determine the adjustment ratio in the following manner:

[0160] First, the behavioral data of multiple dimensions in the user's current behavioral data are normalized to obtain multiple normalized behavioral features; then, characteristic values ​​are obtained based on the multiple normalized behavioral features; finally, the adjustment ratio is determined based on the comparison result between the characteristic values ​​and the preset values.

[0161] The preset value can be set according to the actual situation and is not limited here.

[0162] As an example, first, the behavioral data of multiple dimensions are normalized using the following formula:

[0163] z=tanh(xc),z∈[-1,1],c=activation threshold

[0164] Then, the eigenvalue is obtained using the following formula:

[0165] U=β1*z(UB)+β2*z(UC)+β3*z(UA)+β4*z(UT)

[0166] Among them, UA, UB, UC, and UD are behavioral data of different dimensions, and β1, β2, β3, and β4 are weight parameters corresponding to behavioral data of different dimensions.

[0167] Finally, the adjustment ratio is determined using the following formula:

[0168]

[0169] In this embodiment, a specific implementation method for determining the adjustment ratio based on the user's current behavior data is provided, which improves the accuracy and rationality of the adjustment ratio.

[0170] Step 205: Update the ownership impact parameter according to the value interval and the number of parameter updates within the adjusted time interval.

[0171] In this embodiment, the execution entity may update the ownership impact parameter according to the value interval and the number of parameter updates within the adjusted time interval.

[0172] As an example, for parameter update operations that have not yet been executed within the estimated time interval, the execution entity may randomly determine the updated value of the ownership impact parameter for this parameter update operation within the value interval, and randomly determine the update time of the ownership impact parameter for this parameter update operation within the adjusted time interval. For each parameter update operation, in response to reaching the update time of this parameter update operation, the value of the ownership impact parameter is updated to the update value corresponding to this parameter update operation.

[0173] In some optional implementations of this embodiment, the execution entity may perform step 205 as follows:

[0174] First, based on the adjusted time interval, the number of parameter updates, and the constraint range, the adjusted update time corresponding to the parameter update operations that were not executed within the estimated time interval is determined; then, for the unexecuted parameter update operations, at the adjusted update time, the ownership impact parameters are updated according to the values ​​corresponding to the unexecuted parameter update operations.

[0175] As an example, for each parameter update operation not executed within the estimated time interval, the adjusted update time corresponding to the parameter update operation can be determined by referring to the above-described method for determining the update time. Specifically, the sampling time corresponding to the parameter update operation is determined based on uniformly distributed sampling within the constraint range; the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the number of parameter updates and parameter update operations is determined; and based on the proportion and the estimated time interval, the adjusted update time corresponding to the parameter update operation is determined.

[0176] In this implementation, for parameter update operations that are not executed within the estimated time interval, in response to reaching the adjusted update time corresponding to this parameter update operation, the ownership impact parameters are updated according to the numerical values ​​corresponding to this parameter update operation, providing users with a parameter update process that is more suitable for the current user, which helps to further improve the efficiency of ownership changes of target items.

[0177] Continue to see Figure 3 , Figure 3 FIG3 is a schematic diagram 300 of an application scenario of the parameter updating method for changing the ownership of an item according to this embodiment. Figure 3 In the application scenario, the server 301 needs to obtain the sales data associated with the target item 303 from the database 302. After obtaining the sales data, the server 301 first determines the numerical range of the target item's ownership impact parameter based on the sales data of the target item; then, determines the number of parameter updates corresponding to the numerical range; then, determines the estimated time range for executing the target item's ownership change process, where the estimated time range corresponds to the numerical range; then, in the process of updating the ownership impact parameter based on the numerical range, the estimated time range and the number of parameter updates, the current behavior data of the user associated with the target item is collected in real time, and the estimated time range is adjusted according to the current behavior data of the user associated with the target item to obtain the adjusted time range; finally, within the adjusted time range, the ownership impact parameter is updated according to the numerical range and the number of parameter updates.

[0178] The method provided by the above-mentioned embodiment of the present application determines the numerical interval of the ownership impact parameter of the target item based on the sales data of the target item; determines the number of parameter updates corresponding to the numerical interval; determines the estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; in the process of updating the ownership impact parameter based on the numerical interval, the estimated time interval and the number of parameter updates, adjusts the estimated time interval according to the current behavior data of the user associated with the target item to obtain the adjusted time interval; within the adjusted time interval, updates the ownership impact parameter according to the numerical interval and the number of parameter updates, thereby providing a method for updating the ownership impact parameter of the target item in combination with the sales data related to the target item and the current behavior data of the user. The personalized parameter update strategy can improve the interactivity and activity of the user in the parameter update process, and help improve the efficiency of the ownership change of the target item.

[0179] Continue to refer Figure 4 , shows a schematic process 400 of another embodiment of a parameter update method for item ownership change according to the present application, comprising the following steps:

[0180] Step 401 : deleting part of the corresponding relationship data related to abnormal historical values ​​in the corresponding relationship data to obtain cleaned corresponding relationship data.

[0181] The corresponding relationship data represents the corresponding relationship between the historical values ​​of the ownership influencing parameters of the target items and the historical quantity of the target items that have undergone ownership changes.

[0182] Step 402: Based on the cleaned correspondence data, the accumulated historical quantity of each historical value up to the ownership influence parameter is counted.

[0183] Step 403: Divide the numerical range into multiple numerical intervals according to the accumulated historical quantity.

[0184] Step 404 : Divide the time range based on the initial time point to obtain multiple estimated time intervals for executing the ownership change process of the target item.

[0185] The multiple estimated time intervals correspond to the multiple value intervals one by one.

[0186] Step 405: Determine the update number range corresponding to the parameter update number according to the estimated time interval and the constraint range.

[0187] The constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership impact parameter.

[0188] Step 406: Determine the parameter update times based on uniformly distributed sampling within the update times range.

[0189] Step 407 : Determine the sampling time corresponding to the parameter update operation based on the uniformly distributed sampling within the constraint range.

[0190] Step 408: Determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling time corresponding to the parameter update number and parameter update operations.

[0191] Step 409 : Determine the update time corresponding to the parameter update operation according to the ratio and the estimated time interval.

[0192] Step 410: Determine the value corresponding to the parameter update operation according to the ratio and the value range.

[0193] Step 411: In response to the current time being the update time, update the ownership influence parameter according to the value.

[0194] Step 412: During the updating process of the ownership influence parameters, the user's current behavior data is obtained.

[0195] Step 413: Adjust the adjustment ratio for the initial time point according to the user's current behavior data.

[0196] Step 414: Adjust the initial time point according to the adjustment ratio to obtain an adjusted time point.

[0197] Step 415 : Divide the time range into a plurality of adjusted time intervals according to the adjusted time points.

[0198] Step 416 : Determine the adjusted update time corresponding to the parameter update operations not executed within the estimated time interval according to the adjusted time interval, the number of parameter updates, and the constraint range.

[0199] Step 417: For the parameter update operations that have not been executed, at the adjusted update time, the ownership influence parameters are updated according to the values ​​corresponding to the parameter update operations that have not been executed.

[0200] It can be seen from this embodiment that Figure 2 Compared with the corresponding embodiments, the process 400 of the parameter update method for changing the ownership of an item in this embodiment specifically illustrates the process of determining the estimated time interval, the process of updating the number of parameter updates, the process of determining the adjusted time interval based on the user's current behavior data, and the process of determining the parameter update operation. The personalized parameter update strategy can improve the user's interactivity and activity during the parameter update process, and help improve the efficiency of changing the ownership of the target item.

[0201] Continue to refer Figure 5 As an implementation of the methods shown in the above figures, the present application provides an embodiment of a parameter updating device for changing the ownership of an item. Figure 2Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0202] like Figure 5 As shown, the parameter updating device 500 for changing the ownership of an item includes: a numerical interval determining unit 501, configured to determine the numerical interval of the ownership influencing parameter of the target item based on the sales data of the target item; a number determining unit 502, configured to determine the number of parameter updates corresponding to the numerical interval; a time interval determining unit 503, configured to determine the estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; a time interval adjusting unit 504, configured to adjust the estimated time interval according to the current behavior data of the user associated with the target item in the process of updating the ownership influencing parameter based on the numerical interval, the estimated time interval and the number of parameter updates, to obtain an adjusted time interval, wherein the ownership influencing parameter shows a downward trend during the updating process; a parameter updating unit 505, configured to update the ownership influencing parameter according to the numerical interval and the number of parameter updates within the adjusted time interval.

[0203] In some implementations of this embodiment, the time interval adjustment unit 504 is further configured to: determine the update moments corresponding to the number of parameter update operations and the parameter update operations within the estimated time interval; determine the numerical values ​​corresponding to the parameter update operations within the numerical range; and in the process of updating the ownership influence parameters based on the update moments and the numerical values, adjust the estimated time interval according to the user's current behavior data to obtain the adjusted time interval.

[0204] In some implementations of this embodiment, the above-mentioned time interval adjustment unit 504 is further configured to: determine the update time corresponding to the parameter update operation based on the estimated time interval, the number of parameter updates and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influence parameter; determine the numerical value corresponding to the parameter update operation based on the numerical interval, the number of parameter updates and the constraint range.

[0205] In some implementations of this embodiment, the above-mentioned time interval adjustment unit 504 is further configured to: adjust the adjustment ratio for the initial time point based on the user's current behavior data, wherein multiple estimated time intervals are obtained by dividing the time range based on the initial time point, and the multiple estimated time intervals correspond one-to-one to multiple numerical intervals; adjust the initial time point according to the adjustment ratio to obtain the adjusted time point; and divide the time range into multiple adjusted time intervals according to the adjusted time point.

[0206] In some implementations of this embodiment, the above-mentioned time interval adjustment unit 504 is further configured to: normalize the behavioral data of multiple dimensions in the user's current behavioral data to obtain multiple normalized behavioral features; obtain a feature value based on the multiple normalized behavioral features; and determine the adjustment ratio based on the comparison result of the feature value and the preset value.

[0207] In some implementations of this embodiment, the above-mentioned time interval adjustment unit 504 is further configured to: determine the sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations of the number of parameter updates; and determine the update time corresponding to the parameter update operation based on the proportion and the estimated time interval.

[0208] In some implementations of this embodiment, the above-mentioned time interval adjustment unit 504 is further configured to: determine the sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations of the number of parameter updates; and determine the value corresponding to the parameter update operation based on the proportion and the value interval.

[0209] In some implementations of this embodiment, the above-mentioned parameter update unit 505 is further configured to: determine the adjusted update time corresponding to the parameter update operation that was not executed within the estimated time interval based on the adjusted time interval, the number of parameter updates and the constraint range; for the parameter update operation that was not executed, at the adjusted update time, update the ownership influence parameter according to the numerical value corresponding to the parameter update operation that was not executed.

[0210] In some implementations of this embodiment, the above-mentioned sales data is correspondence data between the historical values ​​of the ownership influence parameters and the historical quantities of the target items that have undergone ownership changes, which are formed based on the user's ownership change behavior, and the above-mentioned numerical interval determination unit 501 is further configured to: divide the numerical range of the ownership influence parameter into multiple numerical intervals according to the correspondence data.

[0211] In some implementations of this embodiment, the above-mentioned numerical interval determination unit 501 is further configured to: delete part of the corresponding relationship data related to the abnormal historical values ​​in the corresponding relationship data to obtain the cleaned corresponding relationship data; based on the cleaned corresponding relationship data, count the cumulative historical number of each historical value up to the ownership influence parameter; and divide the numerical range into multiple numerical intervals based on the cumulative historical number.

[0212] In some implementations of this embodiment, the above-mentioned number determination unit 502 is further configured to determine the update number range corresponding to the parameter update number based on the estimated time interval and the constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influence parameter; and determine the parameter update number based on uniformly distributed sampling within the update number range.

[0213] In this embodiment, a parameter updating device for item ownership change includes a numerical interval determination unit that determines a numerical interval for the target item's ownership-affecting parameter based on the target item's sales data; a frequency determination unit that determines the number of parameter updates corresponding to the numerical interval; a time interval determination unit that determines an estimated time interval for executing the target item's ownership change process, where the estimated time interval corresponds to the numerical interval; a time interval adjustment unit that adjusts the estimated time interval based on the user's current behavior data associated with the target item during the update of the ownership-affecting parameter based on the numerical interval, the estimated time interval, and the number of parameter updates, to obtain an adjusted time interval; and a parameter updating unit that updates the ownership-affecting parameter based on the numerical interval and the number of parameter updates within the adjusted time interval. This provides a device for updating the target item's ownership-affecting parameter based on both the user's historical behavior data and the user's current behavior data related to the target item. This personalized parameter update strategy can enhance user interactivity and activity during the parameter update process, thereby improving the efficiency of the target item's ownership change.

[0214] Reference below Figure 6 , which shows a device suitable for implementing the embodiments of the present application (eg Figure 1 Schematic diagram of the structure of the computer system 600 of the devices 101, 102, 103, 105 shown. Figure 6 The device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application.

[0215] like Figure 6 As shown, the computer system 600 includes a processor (e.g., CPU, central processing unit) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the system 600 are also stored in the RAM 603. The processor 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0216] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, and the like; an output section 607 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed into the storage section 608 as needed.

[0217] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609 and / or installed from a removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the method of the present application are performed.

[0218] It should be noted that the computer-readable medium of the present application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0219] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the client computer, partially on the client computer, as a stand-alone software package, partially on the client computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the client computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0220] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of 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 than that 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 and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0221] The units involved in the embodiments described in the present application can be implemented by software or by hardware. The described units can also be set in a processor. For example, they can be described as: a processor comprising a numerical interval determination unit, a number determination unit, a time interval determination unit, a time interval adjustment unit, and a parameter update unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the time interval adjustment unit can also be described as "a unit that adjusts the estimated time interval according to the current behavior data of the user associated with the target item in the process of updating the ownership influencing parameters based on the numerical interval, the estimated time interval, and the number of parameter updates to obtain the adjusted time interval."

[0222] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by the device, the computer device: determines the numerical interval of the ownership impact parameter of the target item based on the sales data of the target item; determines the number of parameter updates corresponding to the numerical interval; determines the estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; in the process of updating the ownership impact parameter based on the numerical interval, the estimated time interval and the number of parameter updates, adjusts the estimated time interval according to the current behavior data of the user associated with the target item to obtain an adjusted time interval, wherein the ownership impact parameter shows a downward trend during the update process; within the adjusted time interval, updates the ownership impact parameter according to the numerical interval and the number of parameter updates.

[0223] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A parameter updating method for changing the ownership of an item, comprising: Determining a numerical range of an ownership influencing parameter of the target item based on sales data of the target item; Determine the number of parameter updates corresponding to the numerical interval; Determining an estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; In the process of updating the ownership influence parameter based on the value interval, the estimated time interval and the parameter update number, adjusting the estimated time interval according to the current behavior data of the user associated with the target item to obtain an adjusted time interval, wherein the ownership influence parameter shows a downward trend during the updating process; In the adjusted time interval, the ownership influence parameter is updated according to the numerical interval and the parameter update times.

2. The method according to claim 1, wherein: In the process of updating the ownership influence parameter based on the value interval, the estimated time interval and the parameter update number, adjusting the estimated time interval according to the current behavior data of the user associated with the target item to obtain the adjusted time interval includes: Determine the update time corresponding to each of the parameter update times and parameter update operations within the estimated time interval; Determine a value corresponding to the parameter update operation within the value interval; In the process of updating the ownership influence parameter based on the update time and the value, the estimated time interval is adjusted according to the user's current behavior data to obtain the adjusted time interval.

3. The method according to claim 2, wherein: The determining of the update times corresponding to the parameter update times and the parameter update operations within the estimated time interval includes: Determining an update time corresponding to the parameter update operation according to the estimated time interval, the number of parameter updates and a constraint range, wherein the constraint range is used to constrain the length of the time interval between adjacent parameter update operations corresponding to the ownership influencing parameter; and The determining of a value corresponding to the parameter update operation within the value interval includes: A value corresponding to the parameter update operation is determined according to the value interval, the number of parameter updates and the constraint range.

4. The method according to claim 2, wherein: The step of adjusting the estimated time interval according to the current user behavior data to obtain the adjusted time interval includes: According to the user's current behavior data, adjusting the adjustment ratio for the initial time point, wherein the multiple estimated time intervals are obtained by dividing the time range based on the initial time point, and the multiple estimated time intervals correspond to the multiple value intervals one by one; Adjust the initial time point according to the adjustment ratio to obtain an adjusted time point; The time range is divided into a plurality of adjusted time intervals according to the adjusted time points.

5. The method according to claim 4, wherein: The adjusting the adjustment ratio for the initial time point according to the current behavior data of the user includes: Normalizing the behavior data of multiple dimensions in the current behavior data of the user to obtain multiple normalized behavior features; Obtaining a feature value according to the plurality of normalized behavior features; The adjustment ratio is determined according to a comparison result between the characteristic value and a preset value.

6. The method according to claim 3, wherein: The determining, according to the estimated time interval, the number of parameter updates and the constraint range, an update time corresponding to the parameter update operation includes: Determining a sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; Determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations of the parameter update number; An update time corresponding to the parameter update operation is determined according to the ratio and the estimated time interval.

7. The method according to claim 3, wherein: The determining, according to the numerical value interval, the number of parameter updates and the constraint range, a numerical value corresponding to the parameter update operation includes: Determining a sampling time corresponding to the parameter update operation based on uniformly distributed sampling within the constraint range; Determine the proportion of the sampling time corresponding to the parameter update operation in the sum of the sampling times corresponding to the parameter update operations of the parameter update number; A value corresponding to the parameter update operation is determined according to the ratio and the value range.

8. The method according to any one of claims 2 to 7, wherein: The updating of the ownership influence parameter according to the value interval and the parameter update times within the adjusted time interval includes: Determining, according to the adjusted time interval, the number of parameter updates and the constraint range, an adjusted update time corresponding to the parameter update operation not executed within the estimated time interval; For the parameter update operation that has not been executed, at the post-adjustment update time, the ownership influence parameter is updated according to the value corresponding to the parameter update operation that has not been executed.

9. The method according to claim 1, wherein: The sales data is the corresponding relationship data between the historical values ​​of the ownership influencing parameters and the historical quantities of the target items that have undergone ownership changes, which are formed based on the ownership change behavior of the user, and The step of determining the numerical range of the ownership influencing parameter of the target item according to the sales data of the target item includes: According to the corresponding relationship data, the numerical range of the ownership influence parameter is divided into a plurality of numerical intervals.

10. The method according to claim 9, wherein: The dividing the value range of the ownership influence parameter into a plurality of value intervals according to the corresponding relationship data includes: Deleting part of the corresponding relationship data related to the abnormal historical values ​​in the corresponding relationship data to obtain cleaned corresponding relationship data; According to the cleaned corresponding relationship data, the accumulated historical quantity of each historical value of the ownership influencing parameter up to the date is counted; According to the accumulated historical quantity, the numerical range is divided into a plurality of numerical intervals.

11. The method according to claim 1, wherein: The determining the number of parameter updates corresponding to the numerical interval includes: Determine, according to the estimated time interval and the constraint range, the update number range corresponding to the parameter update number, wherein the constraint range is used to constrain the time interval length between adjacent parameter update operations corresponding to the ownership influencing parameter; The parameter update times are determined based on uniformly distributed sampling within the update times range.

12. A parameter updating device for changing the ownership of an item, comprising: a numerical range determination unit configured to determine a numerical range of an ownership influencing parameter of the target item according to sales data of the target item; A number determination unit, configured to determine the number of parameter updates corresponding to the numerical interval; a time interval determination unit configured to determine an estimated time interval for executing the ownership change process of the target item, wherein the estimated time interval corresponds to the numerical interval; a time interval adjustment unit configured to adjust the estimated time interval according to the current behavior data of the user associated with the target item during the process of updating the ownership influence parameter based on the numerical interval, the estimated time interval and the parameter update number, to obtain an adjusted time interval, wherein the ownership influence parameter shows a downward trend during the updating process; The parameter updating unit is configured to update the ownership influence parameter according to the value interval and the parameter update times within the adjusted time interval.

13. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

14. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 11.

15. A computer program product comprising: A computer program which, when executed by a processor, implements the method according to any one of claims 1 to 11.

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