Material sequence adjustment method, device and computer program product

Abstract

The present disclosure provides a method, apparatus, and computer program product for adjusting a material sequence. The method includes: obtaining a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials having characteristic data at the multiple positions; obtaining a set of conditional judgment rules configured by a user; and, for at least a portion of the positions in the material sequence, sequentially judging, using each conditional judgment rule, the characteristic data in the characteristic data of at least one of the material at the current position and the material at a position associated with the current position, obtaining a comprehensive judgment result for each conditional judgment rule, wherein the current position associated with the current position is indicated by the conditional judgment rule being used; and determining whether to adjust the material at the current position based on the comprehensive judgment result for the current conditional judgment rule.

Description

Technical Field

[0001] The present disclosure relates to the field of computers, and more particularly, to a method, device, and computer program product for adjusting a material sequence. Background Art

[0002] In recent years, recommendation algorithms and solutions driven by big data have made tremendous progress, and society has been caught up in a big data frenzy—everything is data-driven. However, the judgments of industry experts or veterans are not necessarily less informed or more accurate than those derived from data mining. This is because data itself (at least with current technology) lacks prior knowledge. Even if a vast knowledge graph is built, providing a foundational worldview for the data and models, it still lags far behind the macro-level knowledge acquired through decades of human learning. For example, big data-driven image recognition technology may accurately identify cats from numerous images, even better than humans, but it likely has no idea what a cat actually is. Furthermore, the process of mining massive amounts of data using big data analysis tools and completing predictive analysis using algorithmic models takes considerable time to support decision-making. Consequently, the speed of response to many hot topics is limited by the time required for algorithmic models to learn.

[0003] Adjusting item sequences is common in item recommendation and search systems. Existing systems typically adjust item sequences based on user behavior preferences, item preferences, and profiles, combined with item and search information. While this achieves a degree of personalized presentation, it currently creates an "echo chamber effect."

[0004] Therefore, there is a need for a technology that can use the knowledge of industry experts or senior people to adjust the material sequences generated based on big data algorithms. Summary of the Invention

[0005] According to one aspect of the present disclosure, a method for adjusting a material sequence is provided. The method includes: obtaining a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials at the multiple positions, each material having feature data; obtaining a set of conditional judgment rules, wherein the set of conditional judgment rules is configured by a user; and for at least a portion of the positions in the material sequence, according to the order of the positions in the material sequence: using each conditional judgment rule in the set of conditional judgment rules, sequentially judging the feature data in the feature data of at least one of the material at the current position and the material at a position associated with the current position, obtaining a comprehensive judgment result for each conditional judgment rule, wherein each conditional judgment rule indicates a position associated with the current position, and determining whether to adjust the material at the current position based on the comprehensive judgment result for the current conditional judgment rule.

[0006] According to an embodiment of the present disclosure, the acquisition of the condition judgment rule set includes reading a profile combination from the first storage unit by sending a first read request, and the profile combination defines the condition judgment rule set. After the updated profile combination is written to the second storage unit and before the updated profile combination is written from the second storage unit to the first storage unit, the acquisition of the condition judgment rule set includes acquiring the updated profile combination from the second storage unit by sending a second read request. After the updated profile combination is written from the second storage unit to the first storage unit, the acquisition of the condition judgment rule set includes acquiring the updated profile combination from the first storage unit by sending a third read request.

[0007] According to an embodiment of the present disclosure, the adjustment method further includes: using the conditional judgment rules in the conditional judgment rule set of the user's historical configuration as historical conditional judgment rules; wherein, obtaining the conditional judgment rule set includes: for a specific scenario, selecting the conditional judgment rule set from the historical conditional judgment rules based on a random optimization algorithm.

[0008] According to one aspect of the present disclosure, a material sequence adjustment device is provided. The adjustment device may include a material sequence acquisition module, a rule acquisition module, and an adjustment module. The material sequence acquisition module is used to acquire a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials placed at the multiple positions respectively, and each material has feature data. The rule acquisition module is used to acquire a set of conditional judgment rules, wherein the set of conditional judgment rules is obtained by user configuration. The adjustment module is used to, for at least a portion of the positions of the material sequence, in accordance with the position order in the material sequence: using each conditional judgment rule in the conditional judgment rule set, sequentially judge the feature data in the feature data of at least one of the material at the current position and the material at the position associated with the current position, and obtain a comprehensive judgment result for each conditional judgment rule, wherein each conditional judgment rule indicates the position associated with the current position, and based on the comprehensive judgment result for the current conditional judgment rule, determine whether to adjust the material at the current position.

[0009] According to an embodiment of the present disclosure, the adjustment device may further include a first storage unit, a second storage unit, and a monitoring unit, or the first storage unit, the second storage unit, and the monitoring unit may exist independently of the adjustment device. The first storage unit and the second storage unit are used to store configuration file combinations, and the monitoring unit is used to monitor the status of the first storage unit and the second storage unit to determine whether there is an updated configuration file combination in the first storage unit and the second storage unit. The rule acquisition unit generally only acquires the configuration file combination from the first storage unit, for example, by sending a first read request to the monitoring unit, which then controls the first storage unit to return the configuration file combination to the rule acquisition unit, and the user only writes the configuration file combination to the second storage unit. When the monitoring unit detects an update in the status of the second storage unit (the configuration file combination is written to the second storage unit), upon receiving a second read request, the monitoring unit controls the second storage unit to return the updated configuration file combination to the rule acquisition unit, and triggers the second storage unit to write the updated configuration file combination to the first storage unit, thereby overwriting the original configuration file combination in the first storage unit. Thereafter, the monitoring unit can again detect an update in the status of the first storage unit and, upon receiving a third read request, can again control the first storage unit to return the updated configuration file combination to the rule acquisition unit.

[0010] According to an embodiment of the present disclosure, the rule acquisition module can also use the conditional judgment rules in the conditional judgment rule set of the user's historical configuration as historical conditional judgment rules; and for specific scenarios, select the conditional judgment rule set from the historical conditional judgment rules based on a random optimization algorithm.

[0011] According to another aspect of the present disclosure, a computer device is provided. The computer device includes a processor and a memory. The memory stores a computer program that, when executed by the processor, implements the steps of the adjustment method described above.

[0012] According to another aspect of the present disclosure, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the processor executes the steps of the material sequence adjustment method as described above.

[0013] According to another aspect of the present disclosure, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the computer program implements the steps of the above-mentioned material sequence adjustment method.

[0014] Based on the above-mentioned aspects of the present disclosure, by configuring the sorting strategy on the user side, it is possible to use the wisdom and ideas of industry experts or senior people to sort materials in real time. In addition, the formatted configuration method is adopted to make the configuration on the user side more convenient. At the same time, according to the conditional judgment rule set configured on the user side, the sequence is adjusted based on the judgment result generated by each conditional judgment rule without human interference. The method of configuring various judgment processes based on material pairs is more convenient for computer implementation. By setting redundant storage means, the online hot update of the conditional judgment rule set can be realized, thereby saving time and cost. Finally, for different scenarios, the random optimization algorithm can be used to select the optimal conditional judgment rule set from the multiple conditional judgment rules that have been configured, thereby improving the performance of material sequence adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic flow chart of a method for adjusting a material sequence according to an embodiment of the present disclosure is shown.

[0016] Figure 2 Another schematic flow chart of a method for adjusting a material sequence according to an embodiment of the present disclosure is shown.

[0017] Figure 3 An example of a configuration file of a conditional judgment rule for judging whether there is a three-in-a-row situation according to an embodiment of the present disclosure and a corresponding flowchart are shown.

[0018] Figure 4 A schematic diagram of an online hot update solution for implementing a condition judgment rule set according to an embodiment of the present disclosure is shown.

[0019] Figures 5A-5C A structural block diagram of a device for adjusting a material sequence according to an embodiment of the present disclosure is shown.

[0020] Figures 6A-6BA structural block diagram of a computer device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the present disclosure more apparent, the following will describe in detail exemplary embodiments of the present disclosure with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure, and it should be understood that the present disclosure is not limited to the exemplary embodiments described herein.

[0022] In this specification and the accompanying drawings, substantially the same or similar steps and elements are denoted by the same or similar reference numerals, and repeated descriptions of these steps and elements will be omitted. At the same time, in the description of the present disclosure, the terms "first", "second", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance or ranking.

[0023] Big data refers to data sets that cannot be captured, managed, and processed within a specific timeframe using conventional software tools. These are massive, rapidly growing, and diverse information assets that require new processing models to enhance decision-making, insight discovery, and process optimization. Big data tends to be used for predictive analytics, user behavior analysis, or other advanced data analysis methods.

[0024] As mentioned earlier, current popular strategies for material sequencing rely heavily on big data. However, small and medium-sized enterprises (SMEs) often lack such big data resources and are far behind large platforms in terms of both product (material) volume and user volume. Therefore, they are unable to use big data to train algorithmic models to adjust the material sequence of their own products. Furthermore, even if these companies have accumulated a wealth of advanced and reliable industry experience, they struggle to apply it conveniently and in real time to adjust the material sequence.

[0025] A to-business (B2B) industry chain exists that provides capabilities to these B-side customers (hereinafter sometimes referred to as enterprise users or merchants). This B2B industry chain is centered around enterprise customers and includes various models, the most common of which involves selling these B-side customers' products to individual users through online trading platforms. When presenting these products to individual users, the online trading platforms use their own algorithms to rank the products (materials) (for example, based on individual user preferences determined through big data).

[0026] Existing material sequence adjustment technologies and methods have at least the following problems:

[0027] It is not friendly to B-side customers and cannot well support B-side customers to independently and customise the material sequence of the display page.

[0028] Sorting and adjustment plans designed by B-side clients cannot be directly implemented into the system. Instead, they must be submitted to the platform's R&D staff for development before being released. This significantly increases the B-side client's time and reduces their ability to quickly respond to environmental hotspots. While the analysis of historical user behavior in current popular platforms' recommendation systems can accurately grasp user preferences, they are unable to respond to sudden environmental hotspots due to a lack of relevant data. This necessitates manual intervention by frontline industry experts and operations personnel. If this requires a lengthy R&D process, opportunities will inevitably be missed.

[0029] Because B-side customers cannot customize the material sorting sequence, or even if they can customize it, the supported rules are limited and the editing capabilities are not high. This greatly limits the creativity and industry experience of B-side customer operations personnel or industry experts.

[0030] For example, for a merchant's various products, an online trading platform may use internal algorithms to sort these products according to buyer preferences and / or sales volume, launch time in descending order, and other factors to present them to buyers. However, the merchant may find that a certain type of product has been popular in the past week or two and may become a big hit in the future. Therefore, the current sorting scheme may not be what the merchant wants. The merchant may hope to put existing products of this type in the sequence or newly launched products of this type at the front of the sequence as soon as possible to increase exposure and thus grab market share. However, with current technology, the merchant may not be able to adjust the sequence quickly, or the sequence adjustment methods are limited and cannot meet current needs, or the merchant itself does not have the ability to adjust the sequence.

[0031] Therefore, a method for adjusting the material sequence is needed so that B-end customers can intervene and adjust the current material sequence independently and conveniently without the need for secondary research and development, thereby saving time and costs. At the same time, it also gives B-end customers the ability to independently update the material sequence and stimulate their subjective initiative and creativity.

[0032] Accordingly, the present disclosure proposes a method, device, and computer program product for adjusting a material sequence. By configuring a sorting strategy (a set of conditional judgment rules) on the user side (e.g., an enterprise user side), it is possible to utilize the wisdom and ideas of industry experts or senior people to sort materials in real time. In addition, a formatted configuration method (e.g., a formatted configuration language or a formatted configuration interface) is adopted to make the configuration on the user side more convenient. At the same time, according to the set of conditional judgment rules configured on the user side, the sequence is adjusted based on the judgment results generated by each conditional judgment rule, without the need for human intervention. In addition, as described later, in the embodiments of the present disclosure, the adjustment of the material sequence generally involves a comparison process, such as the comparison between the specific feature data of each material, the comparison between the specific feature data of the material and the threshold, etc. These comparisons can be implemented by configuring a pair of materials, and the method of configuring various judgment processes based on material pairs is more convenient for computer implementation. Therefore, in the scheme of the present disclosure, the configuration is based on the material pairs when configuring the conditional judgment rules. By setting up redundant storage means, the online hot update of the conditional judgment rule set can be achieved, thereby saving time and cost. Finally, for different scenarios, a random optimization algorithm can be used to select the appropriate optimal set of conditional judgment rules from the multiple configured conditional judgment rules, thereby improving the performance of material sequence adjustment.

[0033] According to one aspect of the present disclosure, a method for adjusting a material sequence is provided.

[0034] Figure 1 A material sequence adjustment method 100 according to an embodiment of the present disclosure is shown.

[0035] In step S110 , a material sequence to be adjusted is obtained, wherein the material sequence has multiple positions and includes multiple materials respectively at the multiple positions, and each material has characteristic data.

[0036] For example, a material sequence may refer to a product sequence in an e-commerce product list, an information retrieval item sequence in a search engine's information retrieval list, and a video sequence in a long and short video list on a video website. These material sequences are all ordered.

[0037] For example, the material sequence may be an ordered sequence determined by the platform based on big data (eg, based on personal user preferences, search history, etc.), so that the materials in the material sequence presented to each individual user may be different.

[0038] Optionally, materials generally have various attributes, such as product model, product launch time, product color, etc. for goods, video length, video creator, etc. for videos, information release time, information publisher type, etc. for information retrieval lists. In this disclosure, the feature data of a material can be understood as a feature data set, which is used to refer to each attribute and its corresponding attribute value.

[0039] In step S120 , a condition judgment rule set is obtained, wherein the condition judgment rule set is configured by the user.

[0040] Optionally, one or more conditional judgment rules can be configured as a conditional judgment rule set based on the ranking goals desired by B-side clients (businesses, search engines, video operators, and other enterprise users). For example, if a video website operator's ranking goal 1 is to prioritize videos of a certain type, and ranking goal 2 is to ensure that three consecutive videos do not come from the same creator, the video operator can configure two conditional judgment rules and adjust the video sequence based on these two conditional judgment rules.

[0041] In some implementations, the configuration process is offline, and the newly configured conditional judgment rules and the previously configured conditional judgment rules serve as a resource pool of rules. The optimal conditional judgment rule set is selected from the resource pool based on, for example, a random optimization algorithm.

[0042] Optionally, each conditional judgment rule is defined by a configuration file configured by an enterprise user on the user side using a formatted configuration method. The formatted configuration method can be a formatted configuration language or a formatted configuration interface. For example, the formatted configuration language can be in the form of a YAML file, or other formats such as an XML file or HDFS. For example, the formatted configuration method can include configuration fields for material pair configuration (for example, material pair judgment conditions, the number of material pair judgment conditions, the relationship between different material pair judgment conditions, etc. as described later). For example, the formatted configuration interface can include an interface box for specifying configuration fields for material pair configuration (for example, material pair judgment conditions, the number of material pair judgment conditions, the relationship between different material pair judgment conditions).

[0043] Furthermore, as previously mentioned, configuring material pairs facilitates computer-implemented adjustments to material sequences. Therefore, in the configuration file, conditional judgment rules are configured based on material pairs. Each configuration file defines a conditional judgment rule, which is described below.

[0044] Each conditional judgment rule may include a specific number of material pair judgment conditions and a method for generating a comprehensive judgment result of the conditional judgment rule based on the judgment results of each material pair judgment condition.

[0045] The specific number of material pair conditions included in each conditional judgment rule can be selected based on the sorting goal. For example, if the sorting goal is to prevent three consecutive items of the same color in the product sequence (i.e., to avoid color triplets), then the color of the item at the current position can be compared with the color of the item at the previous position and the color of the items at the previous two positions. If they are equal, the item at the current position needs to be adjusted. In this case, the conditional judgment rule includes two item pairs (material pairs): the item at the current position and the item at the previous position are considered one item pair, and the item at the current position and the items at the previous two positions are considered one item pair.

[0046] In addition, the method for generating the comprehensive judgment result based on the judgment results of the judgment conditions of each material pair included in each conditional judgment rule can be a logical operation, such as an "AND operation" or an "OR operation", or other generation methods configured according to the actual sorting target. For example, in the case of avoiding color trifectas of the above-mentioned products, a color trifecta is determined to exist only when the colors of the two products in the two product pairs are the same. Assuming that the judgment result of the product pair judgment condition is 1 when the colors of the two products in the two product pairs are the same, it is necessary to perform an "AND operation" on the judgment results of the two product pairs, and if the result of the "AND operation" is 1, it is considered that a color trifecta exists.

[0047] More specifically, each material pair judgment condition may include: indication information of a current position associated with a position, data information of feature data for judgment, and a judgment method for the material pair used to generate a judgment result.

[0048] Alternatively, the indication information of the current position-related position in the material pair judgment condition can be two numerical values of the offset relative to the current position. For example, the indication information of 1 and 2 can indicate that the position of one material in the material pair is one position after the current position and the position of the other material is two positions after the current position. Alternatively, the indication information can be a combination of a numerical value of the offset relative to the current position and a numerical value of the offset between the two positions in the material pair. For example, the indication information of -2 and -1 can indicate that the position of one material in the material pair is one position before the current position and the position of the other material is two positions forward of the position before the current position, that is, three positions before the current position. In addition, the indication information of the material pair can also only indicate the current position, that is, the current position-related position can be the current position itself. For example, the indication information can be 0 and 0. This situation often exists in the case of judging the characteristic data of the material itself at the current position (for example, attributes and attribute values such as color, model, etc.). Of course, the indication information can have other forms, as long as it can clearly indicate the current position-related position involved in the material pair judgment condition.

[0049] Optionally, the data information for the characteristic data used for judgment in the material pair judgment condition may include a characteristic field. For example, if the judgment is based on the characteristic data of the product's color, the characteristic field may be "color." Furthermore, the data information may also include a reference value for the characteristic field. For example, if the judgment is based on whether the color of the product is red, the reference value may be "red." That is, the value of the characteristic field for the color of the product at the current location may be compared with the reference value red. If they are equal, the color of the product at the current location is determined to be red.

[0050] Optionally, the judgment method for material pairs in the material pair judgment condition may include one of the following methods: method A, judging whether the materials in the material pair exist in the preset data source; method B, judging whether the judgment feature data of the two materials in the material pair are equal to the threshold or whether the judgment feature data of the two materials in the material pair are equal; method C, judging whether the judgment feature data of the two materials in the material pair is less than or greater than the threshold; and method D, judging whether the absolute value of the difference between the judgment feature data of the two materials in the material pair is less than or greater than the threshold.

[0051] Among them, the preset data source can be an external data source, which is used to provide additional data required to complete the judgment conditions, and these additional data can be written in the configuration file in the form of a list. For example, still taking the product sequence as an example, if the merchant has a large number of products, the merchant wants to determine whether the products in the product sequence exist in a series of products that it wants to put on the shelves (in the form of a list as the preset data source), so the products at each position in the product sequence can be compared with the preset data source to determine whether one or more products that want to be put on the shelves already exist in the current product sequence. At this time, the current position associated position in the material pair is the current position itself, that is, it is determined whether the material at the current position exists in the preset data source. Of course, other judgment methods can also be configured according to the actual sorting target or combined with other judgment methods.

[0052] Optionally, the feature data used for each material pair judgment condition in the same conditional judgment rule can be different. For example, to determine whether the product at the current location is a "red coat," a conditional judgment rule can be set up that includes two material pair judgment conditions, one of which is based on the color feature data, and the other on the clothing type feature data. The judgment results of the two material pair judgment conditions are then logically operated (e.g., an "AND operation") to determine whether the product at the current location is a red coat.

[0053] In addition, each conditional judgment rule also includes an adjustment method for the material at the current position and a subsequent operation mode, which is used to indicate how to adjust the material at the current position when it needs to be adjusted and what operation to perform after the adjustment.

[0054] In step S130, for at least a part of the positions in the material sequence, according to the position order in the material sequence, execute: I. use each condition judgment rule in the condition judgment rule set to judge the judgment feature data in the feature data of at least one of the material at the current position and the material at the position associated with the current position in turn, and obtain a comprehensive judgment result for each condition judgment rule, wherein each condition judgment rule indicates the current position associated position, and II. for each condition judgment rule, determine whether to adjust the material at the current position based on the comprehensive judgment result for the current condition judgment rule.

[0055] For example, in some scenarios, it may be necessary to adjust materials at some positions in the material sequence. For example, for a video sequence, it may be necessary to adjust only the videos presented in the first twenty positions on the homepage of the video sequence in order to present videos with the highest possible click-through rates. For another example, when it is necessary to compare a feature data of the product at the current position with the previous N (N is an integer greater than or equal to 1) products in order to determine whether the product at the current position needs to be adjusted, step S130 is executed starting from the N+1th position in the product sequence.

[0056] The following combination Figure 2 The material sequence adjustment method will be further described, especially with respect to step S130.

[0057] Figure 2 Another schematic diagram of a material sequence adjustment method according to an embodiment of the present disclosure is shown.

[0058] like Figure 2 As shown, Figure 1 Operation I in step S130 may include the following sub-steps.

[0059] In operation 1, for at least a portion of the positions in the material list, for example, starting from the first position, each conditional judgment rule in the conditional judgment rule set (one or more conditional judgment rules) is used to sequentially determine whether the material placed at the current position is suitable. If a conditional judgment rule determines that the material at the current position is unsuitable, the material at the current position needs to be adjusted. The following sub-steps can be, for example, operations performed when determining the material placed at the Nth position, where the material at the previous position (N-1) has already been adjusted or does not need to be adjusted.

[0060] In sub-step S1301, for the current condition judgment rule, based on the various indication information and various data information included, characteristic data for judging the materials of each material pair included in the current condition judgment rule is obtained.

[0061] For example, if the indication information included in the current condition judgment rule (actually the indication information in the judgment conditions of each material pair) indicates that the position related to the current position is the previous and previous two adjacent positions of the current position, and the data information indicates to obtain the color data of the material (actually the data information in the judgment conditions of each material pair), then the color data of the material at the current position, the previous adjacent position, and the previous two adjacent positions are first obtained as feature data for judgment.

[0062] In step S1302, according to the judgment methods included in the judgment conditions of each material pair included in the current condition judgment rule, the respective judgment feature data are judged to obtain the respective judgment results of the judgment conditions of each material pair.

[0063] For example, assuming that the current condition judgment rule includes two material pairs, the characteristic data of the materials in the corresponding material pairs obtained in sub-step S1301 are judged based on the judgment method in each material pair, such as whether the colors of the two materials in each material pair are equal, and two judgment results are obtained.

[0064] In step S1303, according to the generation method included in the current condition judgment rule, a comprehensive judgment result for the current condition judgment rule is obtained based on the various judgment results.

[0065] For example, if the generation method is "AND operation," then if the two judgment results obtained in step S1302 are both equal (e.g., represented by 1), the comprehensive judgment result can be determined to be 1, i.e., there are three consecutive materials with the same color. Of course, the generation method can be other logical operations, and 0 can be used to represent the judgment result of each material indicating "equal" to the judgment condition. It only needs to reasonably design the logical relationship between them to meet the sorting goal.

[0066] like Figure 2 As shown, Figure 1 Operation II in step S130 may include the following sub-steps.

[0067] In operation II, when determining whether the material at the current position is suitable (for example, the current position is the Nth position, and the first N-1 positions have been adjusted or all meet the sorting target), if the comprehensive judgment result of the current condition judgment rule is valid, the material placed at the current position is adjusted based on the current condition judgment rule. The validity here can be indicated by 0 or 1, which is specifically determined according to the sorting target and the material pair judgment conditions and generation method included in the condition judgment rule. As mentioned above, for the current condition judgment rule, the comprehensive judgment result can be generated based on the judgment results of each material pair judgment condition through "OR operation" or "AND operation", and the judgment result of each material pair judgment condition is "yes" or "no" (which can be represented by binary 1 and 0).

[0068] Optionally, if the comprehensive judgment result of the current conditional judgment rule is valid, it indicates that the material at the current location needs to be adjusted. For example, if the comprehensive judgment result of the conditional judgment rule for judging the three-color combination of products is valid (e.g., 1), it means that the product at the current location has the same color as the products at the previous two locations, so they need to be broken up, that is, the product at the current location needs to be adjusted (generally, only the material at the current location is adjusted to simplify the process).

[0069] In sub-step S1304, the material placed at the current position is adjusted using the adjustment method included in the current condition judgment rule.

[0070] For example, the adjustment method of the material at the current position includes one of the following: exchanging the position of the material placed at the current position with the material placed at other positions in the material sequence; inserting another material at the current position, where the other material is a new material from an external data source to be added to the material list or a material at another position; and deleting the material placed at the current position.

[0071] In sub-step S1305, after adjusting the material placed at the current position once, the condition judgment rule set is used to further adjust the material at the current position or stop adjusting the material at the current position based on the subsequent operation mode included in the current condition judgment rule.

[0072] For example, after adjusting the material placed at the current position once, further adjustment of the material at the current position can be immediately stopped, or it can be determined whether the adjusted material at the current position meets the current condition judgment rule. If the condition judgment rule set includes multiple condition judgment rules, it can also be determined whether the adjusted material at the current position meets all condition judgment rules. How to perform the next operation after an adjustment can be determined by the subsequent operation mode included in the current condition judgment rule. For example, different subsequent operation modes can be included in the condition judgment rule according to different sorting goals. The subsequent operation mode can include: a stop operation mode (after the adjustment of the current position is completed, jump directly to the next position and continue to execute all condition judgments from the beginning, for example, if the sorting goal is to swap positions); a continue execution mode (after the adjustment of the current position is completed, all condition judgment rules are used again to determine whether the material at the current position meets all condition judgment rules); a repeat execution mode (after the adjustment of the current position is completed, only the current condition judgment rule is repeated to determine whether the material at the current position meets the current condition judgment rule. For example, the current condition judgment rule has a higher priority and only the condition judgment rule needs to be met).

[0073] Therefore, correspondingly, sub-step S1305 may specifically include: 1) stopping further adjustment of the adjusted material placed at the current position, and performing judgment and adjustment operations on the material at the next position, that is, using each conditional judgment rule in the conditional judgment rule set to judge the feature data in the feature data of the material placed at the next position and at least one of the materials at the position associated with the next position to determine whether to adjust the material at the next position, that is, obtaining a comprehensive judgment result for each conditional judgment rule, and determining whether to adjust the material placed at the next position based on the comprehensive judgment result for each conditional judgment rule; or 2) re-performing the same operation on the adjusted material placed at the current position, that is, using each conditional judgment rule in the conditional judgment rule set to judge the material placed at the current position, and at least one of the materials at the position associated with the next position. The characteristic data of at least one of the materials at the current position and the associated position are judged using the characteristic data to obtain a comprehensive judgment result for each condition judgment rule to determine whether to further adjust the adjusted material at the current position, that is, to determine whether to further adjust the adjusted material placed at the current position based on the comprehensive judgment result for each condition judgment rule; or 3) the characteristic data of the material placed at the current position and at least one of the materials at the position associated with the current position are judged using the characteristic data to determine whether to further adjust the adjusted material at the current position, that is, to obtain an updated comprehensive judgment result for the current condition judgment rule, to determine whether to further adjust the adjusted material placed at the current position based on the updated comprehensive judgment result for the current condition judgment rule.

[0074] In addition, in operation II, in the process of judging whether the material at the current position is suitable (for example, the current position is the Nth position, and the first N-1 positions have been adjusted or all meet the sorting target), if the comprehensive judgment result of the current condition judgment rule is invalid, operation II can also include the following sub-steps.

[0075] In sub-step S1306, no adjustment is made to the material placed at the current position.

[0076] That is, according to the current condition judgment rules, the material at the current position is suitable, so no adjustment is required at this time.

[0077] In step S1307, based on the next conditional judgment rule in the conditional judgment rule set, the selected feature data to be used for judgment in the feature data of at least one of the material at the current position and the material at the position associated with the current position indicated in the next conditional judgment rule is judged to determine whether to adjust the adjusted material at the current position, until all conditional judgment rules have been used to make judgments or it is determined that the material at the current position needs to be adjusted for a certain conditional judgment rule.

[0078] That is, a comprehensive judgment result for the next condition judgment rule is first obtained, and then based on the comprehensive judgment result for the next condition judgment rule, it is determined whether to adjust the material placed at the current position.

[0079] For example, based on the current condition judgment rule, it is judged that the material at the current position is suitable, so the next condition judgment rule is used to continue to judge the material at the current position to determine whether the material at the current position is still suitable for the next condition judgment rule.

[0080] Similarly, the comprehensive judgment result for the next conditional judgment rule (which becomes the current conditional judgment rule) may also be valid or invalid. If the comprehensive judgment result is invalid, it means that the material at the current position is also suitable for the next conditional judgment rule, so there is no need to adjust it. Then continue to use the next conditional judgment rule to judge the material at the current position, and so on. If the comprehensive judgment result for the last conditional judgment rule is still invalid until the last conditional judgment rule, it is determined that the current position no longer needs to be adjusted, and then the same judgment and adjustment process is started for the material at the next position using the conditional judgment rule set. Alternatively, if the comprehensive judgment result for the next conditional judgment rule is valid, the material at the current position is adjusted based on the next conditional judgment rule, for example, the operations of sub-steps S1304-1305 are executed.

[0081] By using reference Figure 1-2 The described material sequence adjustment method enables enterprise users to automatically sort materials in real time. Simultaneously, based on a set of user-configured conditional judgment rules, sequence adjustments are performed based on the judgment results generated by each conditional judgment rule, eliminating the need for human intervention. Furthermore, configuring conditional judgment rules based on material pairs facilitates computer implementation.

[0082] Reference above Figure 1-2The described material sequence adjustment method can be implemented by a computer executing (e.g., parsing) a combination of configuration files (each configuration file corresponds to a conditional judgment rule). To more clearly explain the configuration method of the conditional judgment rules disclosed herein, the specific content of a configuration file is used as an example below.

[0083] Figure 3 An example of a configuration file for a conditional judgment rule for judging whether there is a three-in-a-row situation and a corresponding flowchart are shown.

[0084] like Figure 3 As shown on the right, the quantity (num) indicates the number of material pairs that make up the entire conditional judgment rule. As previously analyzed, the three-in-a-row judgment requires two material pairs, so num is 2 here.

[0085] A logical relationship (relation) represents how the combined judgment result of a conditional judgment rule is generated based on the results of each material's judgment of the condition. As previously analyzed, when judging a three-in-a-row situation, the result of the "AND" operation of each material's judgment of the condition is used. Therefore, the corresponding relation here should be "and."

[0086] Next, for each item pair in the two item pairs, configure the item pair judgment conditions as follows: First, each item pair needs to be named. For example, for simplicity and convenience, the item pair names can be generated using the format "name" + index, as shown in the figure. However, this is merely exemplary and other naming methods are possible. A and B correspond to the current position, with B being the offset relative to the current item position and A being the offset relative to B. That is, the item at position A and the item at position B together constitute an item pair. When judging the three-in-a-row situation, as previously analyzed, the item at the current position and the items one or two positions before it (their characteristic data, such as color) need to be combined into two item pairs for comparison. Therefore, in one item pair judgment condition, B should be 0 to indicate the current position, while A should be -1 to indicate the position before B (the current position). In the other item pair judgment condition, B should be 0 to indicate the current position, while A should be -2 to indicate the position two positions before B (the current position). C and D can be considered as data information for the judgment feature data. C represents the feature field whose characteristic data should be selected for the material pair's judgment. For example, it can be "color" to indicate that the color characteristic data of each material should be extracted for judgment. D indicates the reference value corresponding to the feature field, which is used for comparison with the corresponding feature data. However, when judging a three-in-a-row situation, D can be left blank, as only the feature data of the same type for each material needs to be compared, so a reference value is not required. The data source (data_source) is additional data required to complete the judgment condition and can be directly specified in the configuration file as a list (list[String]). For example, some judgment methods may require checking whether the material at the current location exists in this data source. However, when judging a three-in-a-row situation, this data source is not required, so data_source can also be left blank. In other words, C, D, and data_source together determine all the data used for the material pair judgment process.

[0087] The material pair judgment condition may further include a reverse information (reverse) field, the value of the reverse field indicating whether the logical value of the judgment result of the corresponding material pair judgment condition in the judgment method described below is reversed (i.e., if reverse is 1, then reverse, and if reverse is 0, then no inversion is required).

[0088] The material pair judgment condition may further include a judgment method. As previously mentioned, according to the specific sorting target, the embodiment of the present disclosure may adopt one of the following four methods:

[0089] a. Determine whether the material in the material pair exists in the data source (data_source). This is achieved by calling the exist_func function. In this case, A=0 is required. In combination with the reverse field, it can be used to determine whether the material does not exist.

[0090] b. Determine whether the feature data used for judgment of both materials in the material pair is equal to the threshold or whether the feature data used for judgment of both materials in the material pair is equal. This is achieved by calling the equal_func function. When D is not empty, it is determined whether the feature data used for judgment of both materials in the material pair is equal to D. When D is empty, it is determined whether the feature data used for judgment of both materials in the material pair is equal. In addition, the reverse field can also be used to achieve inequality judgment;

[0091] c. Determine whether the characteristic data used for judgment of the two materials in the material pair is less than or greater than the threshold. This is achieved by calling the comp_func function. This is for the case where A is equal to 0, that is, the two materials in the material pair are the same material. If the comp_func function defaults to executing the judgment on whether the value of the characteristic data used for judgment of the material is greater than the threshold, the reverse field can be used to determine whether it is less than or equal to the threshold. The threshold is still indicated by D. In addition, if it is necessary to perform a judgment on whether it is less than the threshold, it can be achieved by subtracting a minimum value from the threshold. For example, to determine whether it is less than 100, the threshold can be set to 100-1e -7 , by calling the comp_func function to determine whether it is greater than (100-e -7 ), the reverse field can be used to determine whether it is less than or equal to (100-e -7 ), if it is less than or equal to (100-e -7 ), it must be less than 100; In addition, for interval judgment, the threshold can be bucketed and converted into a judgment based on calling the equal_func function;

[0092] d. Determine whether the absolute value of the difference between the judgment feature data of the two materials in the material pair is less than or greater than the threshold. This is also implemented based on calling the comp_func function, where this is for the case where A is not equal to 0, that is, the two materials in the material pair are two different materials. If the default judgment is to perform the judgment of whether it is greater than the threshold, that is, to determine whether the value of the judgment feature data of one material is greater than the value of the judgment feature data of the other material plus the threshold, the reverse field can be used to achieve the judgment of the opposite size relationship, and the threshold is still indicated by D.

[0093] When judging the situation of three consecutive beads, it is only necessary to perform the judgment of whether they are equal, that is, to select the judgment method b. Therefore, the content specified in the judge field shows that the equal_func function is called, and D is empty.

[0094] The configuration file for a conditional judgment rule can also include an implementation. This implementation involves adjusting the material at the current location when the combined judgment result generated based on the judgment condition is valid (three consecutive items are present). As mentioned above, there are three types of implementations: a. Insert (implemented by calling the insert_func function); b. Delete (implemented by calling the del_func function); and c. Move (implemented by the move_func function, essentially swapping the positions of two materials at different locations).

[0095] When adjusting for the three-in-a-row situation, you can choose adjustment method c, which is to swap the material at the current position with the material at other positions. For example, in the move_func function, you can design the material at the current position to move down N units when moving, and do a position swap with the material at the corresponding position. If the material at the current position after the swap still does not meet the conditional judgment rule set (for example, starting from the first conditional judgment rule, use the conditional judgment rule set to judge the material at the current position after the swap), then restore the material before the swap, and then move the material at the current position down N+1 units, and continue the same operation. However, this part of the adjustment details is only an example, and functions with other adjustment methods can also be designed.

[0096] The configuration file of the conditional judgment rule can also include a subsequent operation mode (next_step), which refers to the mode of the operation that needs to be performed next after the adjustment. As mentioned above, there are three types of subsequent operation modes: a. Abort the operation (implemented by calling the break function, the material adjustment at the current position is completed, and it jumps directly to the next position to continue to judge and adjust based on all the conditional judgment rules); b. Continue execution (implemented by calling the move_on function, which means that after adjusting based on the current conditional judgment rule, the judgment and adjustment are re-based on all the conditional judgment rules); c. Repeat execution (implemented by calling the repeat function, which means only repeating the current conditional judgment rule).

[0097] When judging the situation of three consecutive balls, you can choose mode B, which adjusts the material at the current position based on the current condition judgment rules, and then re-judges and adjusts based on all condition judgment rules. Of course, you can also choose the other two modes.

[0098] The above content is Figure 3 A detailed description of the configuration file example in is given below. The following briefly introduces the flowchart corresponding to the operations implemented when executing this configuration file (a conditional judgment rule).

[0099] like Figure 3 As shown in the left part, the operations shown in the first area (Z1) correspond to determining the number (num) of material pairs of judgment conditions and a generation method (relation) of generating a comprehensive judgment result based on the judgment results of each material pair of judgment conditions.

[0100] The operations shown in the second area (Z2) correspond to executing the judgment conditions of each material pair in the condition judgment rule to obtain corresponding judgment results.

[0101] The operation shown in the third area (Z3) corresponds to generating a comprehensive judgment result based on the judgment results of the judgment conditions for each material, and performing an adjustment operation on the material at the current position based on the comprehensive judgment result.

[0102] The operations shown in the fourth area (Z4) correspond to executing subsequent operations after the adjustment operation on the material at the current position according to the conditional judgment rule configured for the configuration file.

[0103] From the above, we can see that through Figure 3 The configuration file shown can use a formatted configuration language to configure each condition judgment rule, making the configuration on the user side more convenient.

[0104] The above embodiments of the present disclosure are exemplarily described below using three specific scenarios to help facilitate understanding thereof.

[0105] The first scenario is the situation of adjusting the sequence of goods. The adjustment goal designed for this scenario is to break up the colors of the goods. Specifically, goods of the same color (for example, red) will not appear in a row of three. This scenario has been explained as an example before. For example, you can first determine whether the color of the goods at the current position is equal to that of the goods at the previous position, and whether the color of the goods at the current position is equal to that of the goods at the previous two positions. If both results are equal, it means that there are three consecutive cases, so it is necessary to adjust the sequence of the goods placed at these three positions (for simple processing, generally the goods placed at the current position are adjusted). The specific condition judgment rules and the corresponding judgment and adjustment process have been described above, so further description of the sequence adjustment in this scenario is omitted here.

[0106] The second scenario is the situation of video sequence adjustment, for example, the operator of the website finds that a video of Chinese natural landscape is quite popular, so the operator of the video website may wish to put the video sequence (for example, possibly according to the ordered sequence of play duration) in the natural landscape of existing various languages in the video sequence that relates to the natural landscape of Chinese in the front row as far as possible thereby improving click-through rate.In this case, the adjustment target designed for this scenario is that the natural landscape of Chinese is arranged in the front of the video sequence. Can start from the first position, determine whether the video placed at each position is the video of Chinese natural landscape, if so, then do not need to adjust the video at this position, otherwise, then adjust the video at this position.In addition, if for a position of the video that is not the natural landscape of Chinese at its place, after the adjustment of preset number of times, still can't the natural landscape of Chinese be placed at its place, can think that all the natural landscape videos of Chinese in this video sequence have all been arranged in the position in front of this position, thereby can terminate the adjustment to video sequence. Alternatively, considering the diversity of video websites and different audiences, it may be desirable to place only Chinese natural landscape videos in the first twenty positions, so adjustments can be made only to the videos in the first twenty positions. This can all be achieved through a program, and the present disclosure does not impose any restrictions on this.

[0107] According to the above video sequence adjustment method, a conditional judgment rule can be set as follows: set two video pairs (expressed as name1, name2), both of which are (video at the current position, video at the current position), one is used to judge whether the video at the current position is a Chinese video, and the other is used to judge whether the video at the current position is a natural landscape-related video, and both are used to make judgments on the video at the same current position; the conditional judgment rule of the first video pair includes the following contents: the position offset of the video in the video pair relative to the current position (expressed as (A, B), in this scenario, the specific feature data of the video at the current position is judged, so the video position in the video pair can be expressed as (X, X), X is the current position; data information of the feature data for judgment (expressed as C, for example, the feature field of the video language, used to indicate that the feature data of the video in the video pair to be used for judgment is the feature data of the video language); threshold Value (expressed as D, used to indicate that the reference language to be used for judgment is Chinese); judgment method (expressed as judge, in this scenario, it is to judge whether the language of the video at the current position is equal to the reference language, so the judgment method in the video pair can be "whether they are equal"); similarly, the conditional judgment of the second video pair includes the following: the position offset of the video in the video pair relative to the current position (can also be expressed as (0, 0)); data information of the feature data for judgment (expressed as C, for example, the feature field of the landscape type, used to indicate that the feature data of the feature data of the video in the video pair is to be used for judgment. The landscape type is the feature data); the threshold value (expressed as D, used to indicate that the reference landscape type to be used for judgment is the natural landscape); judgment method (expressed as judge, in this scenario, it is to judge whether the landscape type of the video at the current position is equal to the reference landscape type, so the judgment method in the video pair can be "whether they are equal").

[0108] Furthermore, only when the judgment results for both video pairs are "equal" is the video at the current location considered to be a natural landscape video in Chinese, and no adjustment is required. Otherwise, adjustment is required. Therefore, the conditional judgment rule also needs to include a method for generating a comprehensive judgment result based on the judgment results of the video pairs, which in this scenario is an "AND operation."

[0109] Furthermore, if the video at the current position is a natural landscape video in Chinese, the judgment results of the two video pairs are both "equal", and then the same judgment and possible adjustment process will be started for the video at the next position (adjustment will be performed if one of the judgment results of the two video pairs is not "equal").

[0110] If the video at the current position is not a natural landscape video in Chinese, the video placed at the current position can be adjusted in the following manner: the video at the current position is exchanged with videos at other positions after a preset number (for example, twenty positions).

[0111] After making the above-mentioned adjustments to the video placed at the current position, it is necessary to determine whether the video at the current position after the adjustment satisfies the conditional judgment rule. If not, it means that it is still not a natural landscape video in Chinese, so further adjustments are required. Therefore, after making the above-mentioned adjustments to the video placed at the current position, the following operations can be performed: using the conditional judgment rule to determine whether the video at the current position after the adjustment is a natural landscape video in Chinese, if not, restoring the videos at each position before the adjustment, and swapping the video at the current position with the video at a position after another preset number of positions (for example, twenty-one positions), and repeating this operation until the video at the current position is a natural landscape video in Chinese.

[0112] Then, similarly, the conditional judgment rules are used to determine whether the video at the next position is a natural landscape video in Chinese, until a position where the video placed there is not a natural landscape video in Chinese, after a preset number of adjustments, still cannot place a natural landscape video in Chinese, or the videos at the previous preset number of positions are all natural landscape videos in Chinese.

[0113] The above are all scenarios for the case where there is only one conditional judgment rule in the conditional judgment rule set. The following is an exemplary description of the case where there are two conditional judgment rules in the conditional judgment rule set.

[0114] The third scenario is still a video sequence scenario, but the video operator hopes to put the Chinese natural landscape videos in the front, and the three consecutive Chinese natural landscape videos are not in the same area. In this case, based on the same principle as before, two conditional judgment rules can be designed. Since the conditional judgment rules for N consecutive beads (N=3 in this scenario) generally start to judge from the Nth position of the material sequence, in order to make the videos at the first N-1 positions be Chinese natural landscape videos, it is possible to first judge whether the video is a Chinese natural landscape video, and then judge whether it forms an N-link with the previous video. At the same time, only the first conditional judgment rule is used for judgment and adjustment for the first N-1 positions, and the two conditional judgment rules are used for judgment and adjustment starting from the Nth position.

[0115] The first conditional judgment rule can be the same as the rule designed to place the Chinese natural landscape video as far forward as possible in the second scenario above. The second conditional judgment rule can be the same as the rule designed to avoid three consecutive products in the first scenario above. Therefore, the specific configuration of the material pairs in each conditional judgment rule will not be described in detail.

[0116] In this case, first, the first conditional judgment rule is used to determine whether the video at the current position is a natural landscape video in Chinese. If so, the second conditional judgment rule is used to determine whether the video at the current position is related to the same region as the videos at the previous two positions (i.e., whether they are in a three-in-a-row format). If so, the video at the current position (represented by the first video) needs to be adjusted, for example, swapped with the video (the second video) at a position after a preset number (e.g., 20) positions. The second video is then considered to be temporarily placed at the current position. The first conditional judgment rule is then used again to determine whether the second video temporarily placed at the current position is a natural landscape video in Chinese. If so, the second conditional judgment rule is used to determine whether the second video placed at the current position is related to the same region as the videos at the previous two positions (i.e., whether they are in a three-in-a-row format). If not, the adjustment of the video at the current position ends, i.e., the second video is determined to be placed at the current position and will not be changed during the adjustment process of the videos at the subsequent positions. Then, a similar judgment and adjustment process is started for the video placed at the next position using the first / second conditional judgment rule.

[0117] Alternatively, if the first conditional judgment rule is reused to determine that the second video temporarily placed at the current position is not a natural landscape video in Chinese, then the second video is also not suitable for being placed at the current position, and therefore the videos at the various positions before the swap are restored, and then the first video at the current position after the restoration is swapped with the third video (for example, the video at the position after the 21st position), and the first conditional judgment rule is reused to determine whether the third video temporarily placed at the current position is related to videos of the same region as the videos at the first two positions (i.e., whether they are in a three-in-a-row format). If not, the adjustment of the video at the current position ends, i.e., the third video is determined to be placed at the current position, and will not be changed during the adjustment process of the videos at the subsequent positions. Then, a similar judgment and adjustment process is started for the video placed at the next position using the first / second conditional judgment rule.

[0118] By reference Figure 3As can be seen from the description of the sorting process of the above-mentioned various example scenarios, a set of conditional judgment rules can be configured on the user side through a formatted configuration language according to various sorting goals, so as to be used for sequence adjustment, which is more convenient for computer implementation and enterprise users to adjust the sequence quickly and conveniently.

[0119] According to other embodiments of the present disclosure, the conditional judgment rule set may need to be updated in real time. For example, if a merchant needs to immediately change a customized conditional judgment rule set, the present disclosure also provides a solution for online hot updating of the conditional judgment rule set. This can be achieved through redundant storage technology.

[0120] Figure 4 A schematic diagram of an online hot update solution for implementing a condition judgment rule set according to an embodiment of the present disclosure is shown.

[0121] When enterprise users such as B-side customers configure a configuration file combination, they generally write the configuration file combination into a storage unit, so that when a processing unit such as a processor needs to obtain a set of conditional judgment rules, it reads the configuration file combination from the storage unit and executes (for example, parses) the configuration file combination to obtain it.

[0122] In the embodiment of the present disclosure, when redundant storage technology is adopted, Figure 4 As shown in the left part, two storage units can be set, namely the first storage unit and the second storage unit, and the currently executed configuration file combination is stored in the two storage units. At the same time, a monitoring unit is also set to monitor the status of the first storage unit and the second storage unit to monitor whether there is an updated configuration file combination in the first storage unit and the second storage unit. Figure 4The flowchart on the right side assumes that, when a processing unit, such as a processor, needs to obtain a set of conditional judgment rules, it retrieves a configuration file combination from the first storage unit. For example, the processing unit sends a first read request to the monitoring unit, which then controls the first storage unit to return the configuration file combination to the processing unit. Furthermore, by default, users can only write configuration file combinations to the second storage unit (for example, the user-written configuration file combination is stored in a cache, thereby triggering an overwrite operation on the second storage unit). When the monitoring unit detects a status update in the second storage unit (the configuration file combination is written to the second storage unit), upon receiving a second read request, the monitoring unit controls the second storage unit to return the updated configuration file combination to the processing unit, triggering the second storage unit to write the updated configuration file combination to the first storage unit, thereby overwriting the existing configuration file combination in the first storage unit. Subsequently, the monitoring unit can detect a status update in the first storage unit again, and upon receiving a third read request, it can control the first storage unit to return the updated configuration file combination to the processing unit for subsequent judgment and material sequence adjustment.

[0123] Therefore, based on Figure 4 The online hot update solution shown, Figure 1 The step of obtaining the condition judgment rule set in step S120 may include reading the condition judgment rule set from the first storage unit by sending a first read request, and after the updated condition judgment rule set is written to the second storage unit and before the updated condition judgment rule set is written from the second storage unit to the first storage unit, the step of obtaining the condition judgment rule set may include obtaining the updated condition judgment rule set from the second storage unit by sending a second read request, and after the updated condition judgment rule set is written from the second storage unit to the first storage unit, the step of obtaining the condition judgment rule set may include obtaining the updated condition judgment rule set from the first storage unit by sending a third read request.

[0124] Therefore, by setting up redundant storage means, online hot update of the condition judgment rule set can be achieved, thereby saving time costs.

[0125] According to other embodiments of the present disclosure, the user can configure a new set of conditional judgment rules before each time the order of the material sequence is desired to be adjusted, so as to adjust the material sequence only using the new set of conditional judgment rules. In addition, since the enterprise user can configure the conditional judgment rules based on the sorting target in real time according to different scenarios (for example, for new products and for product promotions), the conditional judgment rules after each configuration can be stored, which is equivalent to the existence of a resource pool, and the number of these conditional judgment rules is theoretically unlimited, as long as the capacity of the storage unit is large enough, so a large number of historical conditional judgment rules for different scenarios may be stored in the storage unit. At this time, the user does not have to repeatedly configure, but can, for example, select the optimal conditional judgment rule set for the specific scenario from the historically stored historical conditional judgment rules through a random optimization algorithm, and apply the optimal conditional judgment rule set to the previous reference. Figure 1-2 Describes the adjustment method for the material series.

[0126] An example of a random optimization algorithm is a genetic algorithm (GA). For example, an initial population is randomly generated based on N conditional judgment rules configured by the user. The initial population includes M individuals, each of which has a chromosome, and each chromosome is randomly generated in the following manner.

[0127] The N configured conditional judgment rules are numbered (starting at 1), and for each chromosome, the number of conditional judgment rules to be applied is randomly determined, as shown in the table below. A flag bit of 0 for each conditional judgment rule indicates that it is not applied, and a flag bit of 1 indicates that it is applied. For example, the table below shows a chromosome coded as 11…01. The remaining chromosomes are randomly generated and coded in a similar manner.

[0128]

[0129] In genetic algorithms, fitness represents the adaptability of a chromosome to its environment. The larger the value, the higher the fitness and the better the chromosome. Fitness can be obtained by reflecting preferred behaviors, for example, by using the click behavior of the audience / buyers facing the material sequence. For example, the MAP (MAP is a ranking indicator) of the click behavior is calculated in the material sequence generated based on the conditional judgment rule set corresponding to each chromosome, and the MAP is used as the fitness value of the chromosome. The larger the MAP, the better the fitness of the corresponding chromosome, and the more it should be retained. There may be incompatible rules in the conditional judgment rule set included in the randomly generated chromosome. When adjusting materials based on the conditional judgment rule set, if one of the conditional judgment rules still cannot meet the conditional judgment rule after a preset number of adjustments, the fitness value of the conditional judgment rule set can be directly set to a lower level. After defining chromosomes and fitness in the GA algorithm, the various steps in the genetic algorithm can be performed based on an initial population of M individuals, such as determining which parent to select, crossover, mutation, etc. After a certain number of iterations, the optimization solution can be obtained, and the optimal set of conditional judgment rules can be obtained. Because GA is a very traditional algorithm and the corresponding algorithm engineers are familiar with it, this disclosure will not provide a detailed introduction to it. Of course, other types of random optimization algorithms are also feasible, such as simulated annealing algorithm, ant colony algorithm, particle swarm algorithm, etc.

[0130] Therefore, based on the random optimization algorithm, the optimal set of conditional judgment rules suitable for specific scenarios can be selected from the multiple conditional judgment rules that have been configured for different scenarios, thereby improving the performance of material sequence adjustment.

[0131] According to another aspect of the present disclosure, a device for adjusting a material sequence is also provided.

[0132] Figures 5A-5C Disclosed is a schematic block diagram of a device 700 for adjusting a material sequence according to an embodiment of the present disclosure.

[0133] like Figure 5A As shown, the adjustment device 500 may include a material sequence acquisition module 510 , a rule acquisition module 520 and an adjustment module 530 .

[0134] The material sequence acquisition module 510 is used to acquire a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials placed at the multiple positions respectively, and each material has characteristic data.

[0135] The rule acquisition module 520 is used to acquire a condition judgment rule set, wherein the condition judgment rule set is obtained by user configuration.

[0136] In addition, the rule acquisition module 520 can also be used to select the condition judgment rule set from the historical condition judgment rules included in the historical condition judgment rule set configured by the user based on a random optimization algorithm for a specific scenario.

[0137] The adjustment module 530 is used to judge, for at least a part of the positions in the material sequence, in the order of the positions in the material sequence: use each conditional judgment rule in the conditional judgment rule set to judge the judgment feature data in the feature data of at least one of the material at the current position and the material at the position associated with the current position, and obtain a comprehensive judgment result for each conditional judgment rule, wherein each conditional judgment rule indicates the current position associated position, and based on the comprehensive judgment result for the current conditional judgment rule, determine whether to adjust the material at the current position.

[0138] The specific content and configuration method of each condition judgment rule are the same as those in the previous reference Figure 1-2 The contents described are the same, so they will not be repeated here.

[0139] More specifically, if Figure 5B As shown, the adjustment module 530 may include: a feature data acquisition submodule 5301, which is used to obtain the feature data for judging the materials of each material pair included in the current condition judgment rule based on the various indication information and various data information included; a judgment submodule 5302, which is used to judge the respective feature data for judging according to the respective judgment methods included in the judgment conditions of each material pair included in the current condition judgment rule, and obtain the respective judgment results of the judgment conditions of each material pair; and a result generation submodule 5303, which is used to obtain a comprehensive judgment result for the current condition judgment rule based on the various judgment results according to the generation method included in the current condition judgment rule.

[0140] For example, the adjustment module 530 may also include an adjustment submodule 5304 for determining whether to adjust the material at the current position based on the comprehensive judgment result of the current condition judgment rule. Specifically, when the comprehensive judgment result of the current condition judgment rule is valid, the adjustment submodule 5304: uses the adjustment method included in the current condition judgment rule to make an adjustment to the material placed at the current position; and after making an adjustment to the material placed at the current position, based on the subsequent operation mode included in the current condition judgment rule, uses the condition judgment rule set to further adjust the material at the current position or stop adjusting the material at the current position (the specific content of the operation based on the subsequent operation mode is the same as that in the previous reference). Figure 1-2 The description is the same and therefore not repeated here).

[0141] Furthermore, the adjustment submodule 5304 is further configured to, if the comprehensive judgment result for the current conditional judgment rule is invalid, not adjust the material placed at the current location; and, based on the next conditional judgment rule in the set of conditional judgment rules, determine selected feature data to be used for judgment in the feature data of at least one of the material at the current location and the material at a location associated with the current location indicated in the next conditional judgment rule, to determine whether to adjust the adjusted material at the current location, until all conditional judgment rules have been judged or it is determined that the material at the current location should be adjusted for a certain conditional judgment rule. That is, first obtain a comprehensive judgment result for the next conditional judgment rule, and then determine whether to adjust the material placed at the current location based on the comprehensive judgment result for the next conditional judgment rule, until all conditional judgment rules have been judged and the comprehensive judgment results are invalid, or the comprehensive judgment result for a certain conditional judgment rule is valid.

[0142] In addition, in some implementations, the adjustment device 500 may also apply redundant storage technology to implement online hot updates of configuration file combinations (conditional judgment rule sets).

[0143] like Figure 5CAs shown, the adjustment device 500 may further include a first storage unit 550, a second storage unit 560, and a monitoring unit 570, or the first storage unit 550, the second storage unit 560, and the monitoring unit 550 may exist independently of the adjustment device 500. The first storage unit and the second storage unit are used to store configuration file combinations, and the monitoring unit is used to monitor the status of the first storage unit and the second storage unit to monitor whether there is an updated configuration file combination in the first storage unit and the second storage unit. Optionally, the rule acquisition unit 520 generally only obtains the configuration file combination from the first storage unit, for example, by sending a first read request to the monitoring unit, which then controls the first storage unit to return the configuration file combination to the rule acquisition unit 520, and the user only writes the configuration file combination to the second storage unit (for example, the configuration file combination written by the user is saved in the cache, which in turn triggers a rewrite operation of the second storage unit). When the monitoring unit detects a status update in the second storage unit (a configuration file combination is written to the second storage unit), based on the receipt of a second read request, the monitoring unit controls the second storage unit to return the updated configuration file combination to the rule acquisition unit 520, and triggers the second storage unit to write the updated configuration file combination to the first storage unit, thereby overwriting the original configuration file combination in the first storage unit. Subsequently, the monitoring unit can monitor the status update of the first storage unit again, and based on the receipt of a third read request, the monitoring unit can control the first storage unit to return the updated configuration file combination to the rule acquisition unit 520 for subsequent judgment and material sequence adjustment.

[0144] Through the material sequence adjustment device according to the embodiment of the present disclosure, users can customize the sorting of materials in real time. In addition, the use of a formatted configuration language makes the configuration on the user side more convenient. At the same time, according to the conditional judgment rule set configured on the user side, the sequence adjustment is performed based on the comprehensive judgment result generated by each conditional judgment rule, without the need for human interference. In addition, the method of configuring various judgment processes based on material pairs is more convenient for computer implementation, and for different scenarios, a random optimization algorithm can be used to select the optimal conditional judgment rule set suitable for a specific scenario from a variety of conditional judgment rules that have been configured, thereby improving the performance of material sequence adjustment. Finally, by setting up redundant storage means, online hot update of the conditional judgment rule set can be achieved, thereby saving time and cost.

[0145] According to yet another aspect of the present disclosure, a computer device is provided.

[0146] Figures 6A-6B Disclosed is a schematic block diagram of a computer device according to an embodiment of the present disclosure.

[0147] like Figure 6AAs shown, the computer device 600A includes a processor, a memory, a network interface, an input device, and a display screen connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the terminal stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor can implement the aforementioned reference. Figure 1-2 The internal memory may also store a computer program that, when executed by the processor, causes the processor to perform the various operations described in each step of the method for adjusting a material sequence.

[0148] For example, these operations may include: obtaining a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials at the multiple positions, each material having characteristic data; obtaining a set of conditional judgment rules, wherein the set of conditional judgment rules is obtained by user configuration; and for at least a part of the positions in the material sequence, according to the order of the positions in the material sequence: using each conditional judgment rule in the set of conditional judgment rules to judge the characteristic data in the characteristic data of at least one of the material at the current position and the material at the position associated with the current position in turn, to obtain a comprehensive judgment result for each conditional judgment rule, wherein each conditional judgment rule indicates the current position associated position, and based on the comprehensive judgment result for the current conditional judgment rule, determine whether to adjust the material at the current position.

[0149] The specific content and configuration method of each condition judgment rule are the same as those in the previous reference Figure 1-2 The contents described are the same, so they will not be repeated here.

[0150] For example, the operations for obtaining the comprehensive judgment result of each conditional judgment rule include: for the current conditional judgment rule, based on the various indication information and various data information included, obtaining the judgment feature data of the materials of each material pair included in the current conditional judgment rule; judging the respective judgment feature data according to the respective judgment methods included in the judgment conditions of each material pair included in the current conditional judgment rule, and obtaining the respective judgment results of the judgment conditions of each material pair; obtaining the comprehensive judgment result for the current conditional judgment rule based on the respective judgment results according to the generation method included in the current conditional judgment rule.

[0151] For example, when the comprehensive judgment result of the current condition judgment rule is valid, the adjustment method included in the current condition judgment rule is used to adjust the material placed at the current position once; and after the material placed at the current position is adjusted once, the condition judgment rule set is used to further adjust the material at the current position or stop adjusting the material at the current position based on the subsequent operation mode included in the current condition judgment rule (the specific content of the operation based on the subsequent operation mode is the same as that in the previous reference). Figure 1-2 The description is the same and therefore not repeated here).

[0152] For example, if the comprehensive judgment result for the current conditional judgment rule is invalid, the material placed at the current position is not adjusted; based on the next conditional judgment rule in the set of conditional judgment rules, the selected feature data to be used for judgment of the feature data of at least one of the material at the current position and the material at the position associated with the current position indicated in the next conditional judgment rule is judged to determine whether to adjust the adjusted material at the current position, until all conditional judgment rules have been judged or it is determined that the material at the current position is to be adjusted for a certain conditional judgment rule. That is, the comprehensive judgment result for the next conditional judgment rule is first obtained, and based on the comprehensive judgment result for the next conditional judgment rule, it is determined whether to adjust the material placed at the current position, until all conditional judgment rules have been judged and the comprehensive judgment results are invalid, or the comprehensive judgment result for a certain conditional judgment rule is valid.

[0153] For example, for a specific scenario, the condition judgment rule set is selected from the historical condition judgment rules included in the historical condition judgment rule set configured by the user based on a random optimization algorithm.

[0154] The processor can be an integrated circuit chip with signal processing capabilities. The above-mentioned processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure. The general-purpose processor can be a microprocessor or any conventional processor, etc., and can be an X84 architecture or an ARM architecture.

[0155] The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. It should be noted that the memory of the methods described in the present disclosure is intended to include, but is not limited to, these and any other suitable types of memory.

[0156] The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the terminal housing, or an external keyboard, touchpad or mouse.

[0157] In addition, the embodiment of the present disclosure also implements online hot update of configuration file combination based on redundant storage technology. Figure 6B As shown, the memory may include a first storage unit and a second storage unit, or the first storage unit and the second storage unit may exist independently of the memory, and even the first storage unit and the second storage unit and the monitoring unit described later may exist independently of the computer device 600B. The computer device further includes a monitoring unit for monitoring the status of the first storage unit and the second storage unit to monitor whether there is an updated configuration file combination in the first storage unit and the second storage unit. The interaction between the first storage unit, the second storage unit, the monitoring unit and the processor is the same as that described above. Figure 5C The interactions among the first storage unit 550 , the second storage unit 560 , the monitoring unit 570 and the rule acquisition module 520 are the same as described above, and thus will not be described again here.

[0158] Through the computer device according to the embodiment of the present disclosure, users can customize the sorting of materials in real time. In addition, the use of a formatted configuration language makes the configuration on the user side more convenient. At the same time, according to the conditional judgment rule set configured on the user side, the sequence is adjusted based on the comprehensive judgment result generated by each conditional judgment rule, without the need for human interference. In addition, the method of configuring various judgment processes based on material pairs is more convenient for computer implementation, and for different scenarios, a random optimization algorithm can be used to select the optimal conditional judgment rule set suitable for a specific scenario from a variety of conditional judgment rules that have been configured, thereby improving the performance of material sequence adjustment. Finally, by setting up redundant storage means, online hot update of the conditional judgment rule set can be achieved, thereby saving time and cost.

[0159] According to another aspect of the present disclosure, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the material sequence adjustment method as described above.

[0160] According to another aspect of the present disclosure, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the computer program implements the steps of the above-mentioned material sequence adjustment method.

[0161] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the module, program segment, or part of the code contains at least one executable instruction for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from 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 boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0162] In general, various example embodiments of the present disclosure may be implemented in hardware or dedicated circuitry, software, firmware, logic, or any combination thereof. Certain aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that may be executed by a controller, microprocessor, or other computing device. When various aspects of the embodiments of the present disclosure are illustrated or described as block diagrams, flow charts, or using some other graphical representation, it will be understood that the blocks, devices, systems, techniques, or methods described herein may be implemented, as non-limiting examples, in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or a controller or other computing device, or some combination thereof.

[0163] The exemplary embodiments of the present disclosure described in detail above are merely illustrative and not restrictive. Those skilled in the art will appreciate that various modifications and combinations may be made to these embodiments or their features without departing from the principles and spirit of the present disclosure, and such modifications should fall within the scope of the present disclosure.

Claims

1. A method for adjusting a material sequence, comprising: Acquire a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials respectively at the multiple positions, and each material has characteristic data; Obtaining a set of conditional judgment rules, wherein the set of conditional judgment rules is configured by a user; and For at least a portion of the positions in the material sequence, in order of their positions in the material sequence: Using each conditional judgment rule in the conditional judgment rule set, judgment is performed on the judgment feature data of at least one of the feature data of the material at the current position and the material at the position associated with the current position in turn, and a comprehensive judgment result for each conditional judgment rule is obtained, wherein each conditional judgment rule indicates the current position associated position, and Based on the comprehensive judgment result of the current condition judgment rules, determine whether to adjust the material at the current location.

2. The adjustment method according to claim 1, wherein: Each conditional judgment rule is defined by a configuration file written by the user on the user side using a formatted configuration method, wherein the formatted configuration includes various configuration fields for material pair configuration.

3. The adjustment method according to claim 1 or 2, wherein: Each conditional judgment rule includes a specific number of material pair judgment conditions and a method for generating a comprehensive judgment result based on the judgment results of each material pair judgment condition, and, Each material pair judgment condition includes: indication information of a current position and a position associated therewith, data information of feature data for judgment, and a judgment method for the material pair used to generate a judgment result.

4. The adjustment method according to claim 3, wherein: Using each conditional judgment rule in the conditional judgment rule set, the judgment feature data in the feature data of at least one of the material at the current position and the material at the position associated with the current position are judged in turn to obtain a comprehensive judgment result for each conditional judgment rule, including: for each conditional judgment rule, Acquire feature data for judging materials of each material pair based on each indication information and each data information included in the current condition judgment rule; According to the judgment methods included in the judgment conditions of each material included in the current condition judgment rule, the respective judgment feature data are judged to obtain the respective judgment results of each material against the judgment conditions; According to the generation method included in the current condition judgment rule, a comprehensive judgment result for the current condition judgment rule is obtained based on each judgment result.

5. The adjustment method according to claim 4, wherein: The judgment method for material pairs includes one of the following: Determine whether the values of the judgment feature data of the two materials in the material pair are both equal to the threshold value or whether the values of the judgment feature data of the two materials in the material pair are equal; Determine whether the values of the judgment feature data of the two materials in the material pair are less than a threshold or greater than a threshold; as well as It is determined whether the absolute value of the difference between the values of the judgment feature data of the two materials in the material pair is smaller than or larger than a threshold value.

6. The adjustment method according to claim 4 or 5, wherein: Each conditional judgment rule also includes the adjustment method of the material at the current position and the subsequent operation mode. Wherein, determining whether to adjust the material at the current position based on the comprehensive judgment result of the current condition judgment rule includes: when the comprehensive judgment result of the current condition judgment rule is valid, Make an adjustment to the material at the current location using the adjustment method included in the current condition judgment rule; and After adjusting the material at the current position once, the material at the current position is further adjusted or the adjustment of the material at the current position is stopped using the condition judgment rule set based on the subsequent operation mode included in the current condition judgment rule.

7. The adjustment method according to claim 6, wherein: Further adjusting the material at the current location or stopping adjusting the material at the current location using the condition judgment rule set based on the subsequent operation mode included in the current condition judgment rule includes: Stop further adjustment of the adjusted material at the current position, and use each condition judgment rule in the condition judgment rule set to sequentially judge the judgment feature data in the feature data of at least one of the material at the next position and the material at the position associated with the next position to determine whether to adjust the material at the next position; or Reusing each conditional judgment rule in the conditional judgment rule set to sequentially judge the judgment feature data in the feature data of at least one of the material at the current position and the material at a position associated with the current position to determine whether to further adjust the adjusted material at the current position; or Reuse the current condition judgment rule to judge the judgment feature data in the feature data of at least one of the material at the current position and the material at the position associated with the current position to determine whether to further adjust the adjusted material at the current position.

8. The adjustment method according to claim 1, wherein: Based on the comprehensive judgment result of the current condition judgment rule, determining whether to adjust the material at the current position also includes: when the comprehensive judgment result of the current condition judgment rule is invalid, No adjustments are made to the material at its current location; Based on the next conditional judgment rule in the conditional judgment rule set, the selected feature data to be used for judgment in the feature data of at least one of the material at the current position and the material at the position associated with the current position indicated in the next conditional judgment rule is judged to determine whether to adjust the adjusted material at the current position, until all conditional judgment rules have been used to make judgments or it is determined that the material at the current position needs to be adjusted for a certain conditional judgment rule.

9. The adjustment method according to any one of claims 6 to 8, wherein: The material at the current location is adjusted in one of the following ways: Swap the material at the current position with the material at another position in the material sequence; Insert another material at the current position, where the other material is a new material to be added to the material list from an external data source or a material at another position; as well as Delete the item at the current position.

10. The adjustment method according to claim 1, wherein: The acquiring of the condition judgment rule set includes reading a configuration file combination from a first storage unit by sending a first read request, wherein the configuration file combination defines the condition judgment rule set. wherein, after the updated configuration file combination is written into the second storage unit and before the updated configuration file combination is written from the second storage unit into the first storage unit, the acquisition condition judgment rule set includes acquiring the updated configuration file combination from the second storage unit by sending a second read request; After the updated configuration file combination is written from the second storage unit to the first storage unit, the acquiring condition judgment rule set includes acquiring the updated configuration file combination from the first storage unit by sending a third read request.

11. The adjustment method according to claim 1, further comprising: The condition judgment rules in the condition judgment rule set configured by the user in history are used as historical condition judgment rules; The acquisition of the condition judgment rule set includes: For a specific scenario, the condition judgment rule set is selected from the historical condition judgment rules based on a random optimization algorithm.

12. A computer device comprising: processor; A memory having a computer program stored thereon, wherein the computer program, when executed by the processor, implements the following operations: Acquire a material sequence to be adjusted, wherein the material sequence has multiple positions and includes multiple materials respectively at the multiple positions, and each material has characteristic data; Obtaining a set of conditional judgment rules, wherein the set of conditional judgment rules is configured by a user; and For at least a portion of the positions in the material sequence, in order of their positions in the material sequence: Using each conditional judgment rule in the conditional judgment rule set, judgment is performed on the judgment feature data of at least one of the feature data of the material at the current position and the material at the position associated with the current position in sequence, to obtain a comprehensive judgment result for each conditional judgment rule, wherein each conditional judgment rule indicates the current position associated with the position, and Based on the comprehensive judgment result of the current condition judgment rules, it is determined whether to adjust the material at the current location.

13. The computer device according to claim 12, wherein: Each conditional judgment rule also includes the adjustment method of the material at the current position and the subsequent operation mode after this adjustment. The computer program, when executed by the processor, implements an operation of determining whether to adjust the material at the current location based on a comprehensive judgment result of the current condition judgment rule, including: When the comprehensive judgment result of the current condition judgment rule is valid, Make an adjustment to the material at the current location using the adjustment method included in the current condition judgment rule; and After adjusting the material at the current position once, the material at the current position is further adjusted or the adjustment of the material at the current position is stopped using the condition judgment rule set based on the subsequent operation mode included in the current condition judgment rule.

14. The computer device of claim 13, further comprising: A first storage unit, a second storage unit and a monitoring unit, wherein: The first storage unit and the second storage unit are used to store a configuration file combination, and the configuration file combination defines the condition judgment rule set; The monitoring unit is used for: controlling the first storage unit to return the configuration file combination in response to a first read request; When monitoring that an updated configuration file combination is written into the second storage unit, controlling the second storage unit to return the updated configuration file combination in response to a second read request, and simultaneously controlling the second storage unit to write the updated configuration file combination into the first storage unit; In the case where it is monitored that the updated configuration file combination is written into the first storage unit, the first storage unit is controlled to return the updated configuration file combination in response to the third read request.

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

16. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 11.

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