CN117541106A

CN117541106A - Object processing method, rule configuration method and computing device

Info

Publication number: CN117541106A
Application number: CN202311414616.9A
Authority: CN
Inventors: 许鼎; 陶征策; 黄柏川
Original assignee: Hangzhou Alibaba Overseas Internet Industry Co ltd
Current assignee: Hangzhou Alibaba Overseas Internet Industry Co ltd
Priority date: 2023-10-27
Filing date: 2023-10-27
Publication date: 2024-02-09

Abstract

The embodiment of the application provides an object processing method, a rule configuration method and computing equipment. Determining an object to be processed and an evaluation rule; extracting at least one index data from object related information of the object; judging whether the object meets the evaluation conditions in the evaluation rule or not by combining the at least one index data; determining at least one corresponding adjustment mode according to at least one target evaluation condition which is met by the object; generating an evaluation result according to the at least one adjustment mode; and feeding back the evaluation result to the user. The technical scheme provided by the embodiment of the application improves the evaluation effect.

Description

Object processing method, rule configuration method and computing device

Technical Field

The embodiment of the application relates to the technical field of electronics, in particular to an object processing method, a rule configuration method and computing equipment.

Background

With the development of electronic technology and network technology, more and more users provide products in an online system in an online form, so that consumers can execute network activities such as product exchange, virtual shops can be opened in the online system, and various products can be provided. To facilitate product exchange, etc., users need to know whether the store and the provided products meet the market demand.

In order to help users to know market demands, in the prior art, market data are generally analyzed and mined by adopting a big data analysis mode to summarize and obtain evaluation data such as relevant characteristics of products required by market places or subversion relevant characteristics, and then the evaluation data are provided for users to make adjustment modes for the users, and objects such as stores or provided products are correspondingly adjusted in an online system.

However, this existing approach is less effective for evaluation.

Disclosure of Invention

The embodiment of the application provides an object processing method, a rule configuration method and computing equipment, which are used for solving the technical problem of poor object evaluation effect in the prior art.

In a first aspect, an embodiment of the present application provides an object processing method, including:

determining an object to be processed and an evaluation rule;

extracting at least one index data from object related information of the object;

judging whether the object meets the evaluation conditions in the evaluation rule or not by combining the at least one index data;

determining at least one corresponding adjustment mode according to at least one target evaluation condition which is met by the object;

generating an evaluation result according to the at least one adjustment mode;

And feeding back the evaluation result to the user.

Optionally, the determining the object to be processed and the evaluation rule include:

determining an evaluation rule;

determining an object to be processed which accords with the object type and/or comprises index data corresponding to the index type according to the object type and/or the index type specified by the evaluation rule;

extracting at least one index data from object related information of the object includes:

and extracting at least one index data corresponding to the index type specified by the evaluation rule from the object related information of the object.

Optionally, the method further comprises:

generating evaluation information by combining the at least one index data and the at least one target evaluation condition;

the generating the evaluation result according to the at least one adjustment mode includes:

generating recommendation information according to the at least one adjustment mode;

and generating an evaluation result comprising the evaluation information and the recommendation information.

Optionally, the generating the evaluation result including the evaluation information and the recommendation information includes:

and generating an evaluation result by using an information processing model based on the recommendation information, the evaluation information and the user characteristics of the user.

Optionally, the feeding back the evaluation result to the user includes:

receiving an evaluation request of a user for the object to be processed;

and under the condition that the object hits a plurality of evaluation rules, sequentially feeding back evaluation results corresponding to the plurality of evaluation rules to the user according to the priorities of the plurality of evaluation rules.

Optionally, the method further comprises:

receiving a confirmation request of the user for a target adjustment mode selected from the at least one adjustment mode;

and processing the object according to the target adjustment mode.

Optionally, the method further comprises:

after the object is processed according to the target adjustment mode, calculating index change information of the at least one index data in a preset time;

and feeding back the index change information to the user.

Optionally, the method further comprises:

acquiring feedback information of the user aiming at the evaluation result;

generating update prompt information for the evaluation rule by combining the feedback information and the index change information;

and feeding back the updated prompt information to related personnel.

Optionally, the object comprises a product or a store;

in the case that the object is a product, the at least one index data includes: one or more of exposure, access, poll, order, guest conversion, poll conversion, and payment conversion;

In the case where the object is a store, the at least one index data includes: one or more of a total number of products, a number of exposed products, a number of accessed products, a number of products with an inquiry, a number of products with a payment, a total conversion rate for access, a total conversion rate for inquiry, and a total conversion rate for payment.

Optionally, the determining the evaluation rule includes:

determining an evaluation rule in response to the evaluation instruction; the evaluation instructions are generated periodically.

Optionally, the determining, according to the object type and/or the index type specified in the evaluation rule, the object to be processed which accords with the object type and/or includes index data corresponding to the index type includes:

and determining an object to be processed which accords with the object type and/or comprises index data corresponding to the index type from at least one object which meets the evaluation requirement according to the object type and/or the index type specified in the evaluation rule.

Optionally, the feeding back the evaluation result to the user includes:

receiving an evaluation request of a user for the object to be processed;

and feeding back the evaluation result to the user.

Optionally, the sequentially feeding back the evaluation results corresponding to the plurality of evaluation rules to the user includes:

Feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user;

and receiving a switching request sent by the user, and feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user from the non-feedback evaluation results according to the priorities of the plurality of evaluation rules.

Optionally, the generating the evaluation result according to the at least one adjustment mode includes:

determining operation controls corresponding to the at least one adjustment mode respectively;

generating an evaluation result comprising operation controls respectively corresponding to the at least one adjustment mode;

the receiving the confirmation request of the user aiming at the target adjustment mode comprises the following steps:

and receiving a confirmation request triggered by the operation control corresponding to the target adjustment mode by the user.

receiving an evaluation request sent by the user, and determining an object to be processed requesting evaluation;

and determining an evaluation rule corresponding to the object.

In a second aspect, an embodiment of the present application provides an object processing method, including:

providing object evaluation prompt information of at least one object on a user interface;

responding to a confirmation operation of evaluating prompt information for any object, and sending an evaluation request for the corresponding object;

Acquiring at least one evaluation result corresponding to the object; the evaluation result is generated according to at least one adjustment mode corresponding to the object; the at least one adjustment mode is determined according to at least one target evaluation condition in the evaluation rule which is met by at least one index data corresponding to the object; the at least one index data is determined from object related information of the object;

and displaying the at least one evaluation result on the user interface.

Optionally, the evaluation result includes operation controls corresponding to the at least one adjustment mode respectively;

the method further comprises the steps of:

responding to a confirmation operation triggered by an operation control aiming at a target adjustment mode, and sending a confirmation request; the confirmation request is used for indicating the object to be processed according to the target adjustment mode.

Optionally, the displaying the at least one evaluation result on the user interface includes:

displaying an evaluation result corresponding to the evaluation rule with the highest priority on the user interface;

and responding to the switching request triggered by the user, and displaying an evaluation result corresponding to the evaluation rule with the highest priority from the undelivered evaluation results.

Optionally, the evaluation result includes evaluation information generated based on at least one target evaluation condition, recommendation information corresponding to the at least one adjustment mode, and operation control and prompt information corresponding to the at least one adjustment mode respectively.

In a third aspect, an embodiment of the present application provides a rule configuration method, including:

providing a rule configuration interface;

providing a plurality of parameter components at the rule configuration interface;

determining, in response to an input operation for the plurality of parameter components, a plurality of parameter contents that are input;

generating an evaluation rule according to the plurality of parameter contents; the evaluation rule is used for combining at least one index data extracted from object related information of an object, judging whether the object accords with evaluation conditions in the evaluation rule, determining at least one corresponding adjustment mode according to at least one target evaluation condition which the object accords with, and generating an evaluation result according to the at least one adjustment mode; the evaluation result is used for being fed back to the user.

In a fourth aspect, embodiments of the present application provide a computing device comprising a processing component and a storage component;

The storage component stores one or more computer instructions; the one or more computer instructions are operable to be invoked by the processing component to implement an object handling method as described in the first aspect above or an object handling method as described in the second aspect above or a rule configuration method as described in the third aspect above.

In a fifth aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program which, when executed by a computer, implements the object processing method according to the first aspect described above or the object processing method according to the second aspect described above or the rule configuration method according to the third aspect described above.

In the embodiment of the application, for the object to be processed, at least one index data may be extracted from the object to be processed, and in combination with the at least one index data, it may be determined whether the object meets at least one evaluation condition defined in the evaluation rule, so as to determine at least one target evaluation condition that the object meets; according to at least one target evaluation condition which is met by the object, at least one adjustment mode corresponding to the at least one target evaluation condition can be determined, so that an evaluation result can be generated according to the at least one adjustment mode and fed back to a user.

These and other aspects of the present application will be more readily apparent from the following description of the embodiments.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 illustrates a schematic diagram of one embodiment of an object handling system provided herein;

FIG. 2 illustrates a flow chart of one embodiment of an object processing method provided herein;

FIG. 3 is a flow chart illustrating yet another embodiment of an object processing method provided herein;

FIG. 4a shows an interface schematic of a user interface in a practical application of an embodiment of the present application;

FIG. 4b shows another interface schematic of a user interface in one practical application of an embodiment of the present application;

FIG. 5 illustrates a flow chart of one embodiment of a rule configuration method provided herein;

FIG. 6 shows a schematic view of a scenario in one practical application of an embodiment of the present application;

FIG. 7 is a flowchart illustrating the execution of an object handling process in one practical application according to an embodiment of the present application;

FIG. 8 shows a system architecture diagram to which embodiments of the present application are applicable in one practical application;

FIG. 9 is a schematic diagram of an embodiment of an object processing apparatus according to an embodiment of the present application;

FIG. 10 is a schematic diagram of an object processing apparatus according to another embodiment of the present application;

FIG. 11 is a schematic structural view of an embodiment of a rule configuration device according to the embodiment of the present application;

FIG. 12 illustrates a schematic diagram of one embodiment of a computing device provided by embodiments of the present application.

Detailed Description

In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.

In some of the flows described in the specification and claims of this application and in the foregoing figures, a number of operations are included that occur in a particular order, but it should be understood that the operations may be performed in other than the order in which they occur or in parallel, that the order of operations such as 101, 102, etc. is merely for distinguishing between the various operations, and that the order of execution is not by itself represented by any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

The technical solution of the embodiment of the present application may be applied to an electronic business scenario that provides a network activity such as product exchange, for example, an electronic business scenario that performs a business activity such as product exchange through a network, where a product is referred to herein as a commodity. In such an electronic transaction scenario, consumers may exchange products using virtual resources, such as currency. A user referred to herein may refer to a product provider, a user may set up a virtual store in an online system, and provide a variety of virtual products in the store, and thus an object referred to herein may refer to a product or store. The product may correspond to a tangible object under the wire, and may of course also refer to an intangible service.

Because the user needs to know whether the store and the provided products meet the market demands, the store or the products can be adjusted accordingly, the product exchange is promoted, and the product conversion rate is improved. On the one hand, the existing large data analysis mode needs processing and analysis of a large amount of data, a large amount of cost and manpower resources are required to be input, in addition, noise and inaccurate data exist in the large data, complex algorithm processing and cleaning are required, and the quality of the data is difficult to ensure. The big data technology is used for accurately analyzing personalized requirements of potential consumers, so that an evaluation result is inaccurate, market data is analyzed and mined, the requirements of different commodities in different stores are different, personalized requirements are difficult to meet, the evaluation effect of the traditional mode is poor, a user cannot obtain an effective evaluation result, the use frequency of a system is greatly increased, and therefore the performance of the system is also affected.

In order to improve the evaluation effect, the inventor provides a technical scheme of the embodiment of the application through a series of researches, in the embodiment of the application, personalized evaluation on the object is realized by utilizing the evaluation rule, and an accurate adjustment mode can be provided for the user without manually reading data by the user, so that more personalized and accurate object evaluation is realized, and the object evaluation effect is improved.

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.

The technical solution of the embodiment of the present application may be applied to an object processing system as shown in fig. 1, where the object processing system may include a server 101 and a client 102.

To facilitate product exchange, etc., users need to know whether the store and the provided products meet the market demand.

In order to help users understand market demands, in the traditional mode, market data are generally analyzed and mined by adopting a big data analysis mode to summarize and obtain evaluation data such as relevant characteristics of products or subversion relevant characteristics required by market, and then the evaluation data are provided for users to formulate an adjustment mode for the users, and objects such as stores or provided products are correspondingly adjusted in an online system.

The client 102 may be a browser, APP (Application), or a web Application such as H5 (HyperText Markup Language, 5 th edition of hypertext markup language) Application, or a light Application (also called applet, a lightweight Application program) or cloud Application, etc., and the client 102 may be deployed in an electronic device, which needs to run depending on the device or some APPs in the device, etc., and the electronic device may have a display screen and support information browsing, etc., for example, may be a personal mobile terminal such as a mobile phone, a tablet computer, a personal computer, etc., and for ease of understanding, fig. 1 mainly shows the client with a device image. Various other types of applications may also be configured in the electronic device, such as search types, instant messaging types, and the like.

The server 101 may be one or more servers providing various services, that is, may be implemented as a distributed server cluster formed by a plurality of servers, may be implemented as a single server, may also be a server of a distributed system, or may be a server combined with a blockchain, or may be a cloud server, or may be an intelligent cloud computing server or an intelligent cloud host with artificial intelligence technology, etc.

The user may interact with the server 101 through the user terminal 102 to receive or send a message, etc., in this embodiment of the present application, for example, the feedback result may be obtained, and the corresponding operation of the user may be perceived to achieve the purpose of processing the object.

It should be noted that, in the embodiments of the present application, the use of user data may be involved, and in practical applications, user specific personal data may be used in the schemes described herein within the scope allowed by applicable legal regulations in the country where the applicable legal regulations are met (for example, the user explicitly agrees to the user to actually notify the user, etc.).

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region, and provide corresponding operation entries for the user to select authorization or rejection.

It should be noted that, the technical solution of the embodiment of the present application is applicable to a network virtual environment, where the described user is generally referred to as a "virtual user", and a real user may register a user account in a server through a registration manner to obtain a user identity in the network environment.

It should be understood that the number of clients and servers in fig. 1 is merely illustrative. There may be any number of clients and servers, as desired for implementation.

Implementation details of the technical solutions of the embodiments of the present application are set forth in detail below.

Fig. 2 is a flowchart of an embodiment of an object processing method provided in the embodiment of the present application, where the technical solution of the present embodiment may be executed by a server, and the method may include the following steps:

201: an object to be processed and an evaluation rule are determined.

In the embodiment of the application, the object to be processed may refer to a product or a store providing a plurality of products.

Wherein the evaluation rule may be preconfigured.

As an alternative, the evaluation rule may be determined first, and then, according to the object type and/or the index type specified by the evaluation rule, the object to be processed that conforms to the object type and/or includes index data corresponding to the index type may be determined.

That is, an object type and/or an index type may be defined in the evaluation rule, and the object type may include, for example, a product or a store, to determine what object the evaluation rule is to evaluate. The evaluation rules may define the index type to specify what data to evaluate in connection with.

The evaluation rule may refer to any one of evaluation rules, and for each evaluation rule, objects may be periodically grasped to perform evaluation processing, and the like.

Where the object is a product, the index type may include, for example, exposure data, query data, order data, click data, conversion data, and the like. The exposure data may refer to, for example, the exposure amount of the product, that is, the number of times to be displayed; the query data can refer to the query quantity of the product, namely the number of times of being consulted; the order data is based on the order quantity, namely the number of traded times; the click data may be the pointing stroke amount, i.e. the number of strokes performed; the conversion data may include, for example, access conversion rate, query conversion rate, payment conversion rate, etc.; the access conversion rate can be determined, for example, from the ratio of the click rate to the exposure rate; the query conversion rate can be determined according to the ratio of the query amount to the click amount; the payment conversion rate can be determined according to the ratio of the order quantity and the inquiry quantity, for example.

In the case of a store, the index types may include, for example, total number of products, number of exposed products, number of accessed products, number of products with a query, number of products with a payment, conversion data, number of RFQ (request for quotation, bid request), and the like; wherein the conversion data may include, for example, access total conversion rate, query total conversion rate, payment total conversion rate, etc.; the total conversion of visits may be determined, for example, from the ratio of the number of products that have visits to the number of products that have exposures, or from a weighted average of the conversion of visits to the various products offered by the store; the total query conversion rate can be determined according to the ratio of the number of products with query and the number of products with access, for example, and can be determined according to the weighted average of the query conversion rates of various products provided by shops; the total conversion rate of payment can be determined according to the ratio of the number of products with payment to the number of products with inquiry, for example, and can be determined according to the weighted average value of the conversion rates of payment of various products provided by shops;

of course, the specification is merely illustrative, and the type of the index is not limited thereto, and the specific calculation method is not limited thereto, and the type of the index required for the evaluation rule is set in accordance with the actual requirement, and the like.

Alternatively, an evaluation rule may be determined in response to an evaluation instruction. The evaluation instruction may be generated periodically, or may be generated based on a trigger operation by a person. The server side configures a plurality of evaluation rules in advance, and the evaluation rules may refer to any one evaluation rule.

Optionally, according to the object type and/or the index type specified in the evaluation rule, determining the object to be processed that meets the object type and/or includes index data corresponding to the index type may be:

and determining the object to be processed which accords with the object type and/or comprises index data corresponding to the index type from at least one object which meets the evaluation requirement according to the object type and/or the index type specified in the evaluation rule.

I.e. evaluation rules, evaluation requirements can also be defined for object screening.

The evaluation requirements may include, for example, one or more of the following:

the user grade of the corresponding user is a preset grade;

the corresponding user is a paying user;

the transaction behavior exists within the appointed time; the method comprises the steps of,

the number of transactions is greater than a specified number, or the like, although the present application is not limited thereto.

As another alternative, determining the object to be processed and the evaluation rule may include: receiving an evaluation request sent by a user, and determining an object to be processed requesting evaluation; and determining an evaluation rule corresponding to the object.

The object to be processed is determined according to the evaluation request, and then the evaluation rule matched with the object is searched. Wherein, as an alternative way, the corresponding evaluation rule can be determined according to the object category, such as the object being a product, which can be referred to as a product category, the object being a store, which can be referred to as an industry, etc.; as another alternative, an evaluation type may be defined in the evaluation rule, and the evaluation type may include, for example, a question type for evaluating a question currently existing by the object and an opportunity type for evaluating a current vantage of the object. The evaluation request may carry an evaluation type, and thus, an evaluation rule that matches an object may be determined in combination with the evaluation type and/or the object category.

Wherein, the object evaluation prompt information can be sent to the user side, and the evaluation request can be generated and sent in response to the triggering operation for the object evaluation prompt information.

202: at least one index data is extracted from object related information of the object.

Wherein, the corresponding index data can be extracted according to at least one preset index type.

Further, as is apparent from the above description, the index type may be defined in the evaluation rule, and thus, extracting at least one index data from the object-related information of the object may include: and extracting at least one index data corresponding to the index type specified by the evaluation rule from the object related information of the object.

The object related information may be data generated by the object in the object processing system, for example, the basic data may include product data such as product identifier, product category, exposure data, query data, order data, click data, conversion data, etc. and user basic information such as total number of products, exposed number of products, number of products with access, number of products with query, number of products with payment, conversion data, RFQ number, etc., the industry data may include industry to which a store belongs and category to which a product belongs, the transaction data may include order amount, transaction amount, etc., the label data may refer to product label such as new product, hot product, explosive product, etc., the action data may include real-time action data and offline action data, etc., the message data may refer to session information between a user and a consumer, between a user and the system, etc., and the like, though the application is not limited thereto. At least one index data can be extracted from the object-related information.

203: and combining at least one index data to judge whether the object meets the evaluation condition in the evaluation rule.

One or more evaluation conditions may be defined in the evaluation rule, and each evaluation condition may specify a corresponding index type to determine whether the corresponding index data meets the evaluation condition. Therefore, whether the index data meets the evaluation condition can be judged according to the index data corresponding to each evaluation condition.

Each evaluation condition may be used to determine one or more index data, to determine whether each evaluation condition is met, etc. The evaluation conditions may be set in connection with actual requirements, and possible implementations are listed herein, but it should be noted that the present application is not limited thereto.

204: and determining at least one corresponding adjustment mode according to at least one target evaluation condition which is met by the object.

According to the above judgment result, the evaluation condition which the object meets can be determined, and for convenience of distinguishing description, the evaluation condition which the object meets is named as the target evaluation condition. If any evaluation condition met by the object does not exist, the flow can be ended.

The corresponding adjustment modes can be defined in the evaluation rule according to different evaluation conditions, so that at least one corresponding adjustment mode can be determined according to at least one target evaluation condition.

The evaluation condition may include one or more factors of an index time period, a comparison object, an output data type, a limitation dimension, and the like, and the related personnel may perform configuration of the evaluation condition according to the factor, and the index time period may include, for example, a time range of approximately 7 days, approximately 90 days, and the like, or may refer to a ring ratio, a late year period, and the like. The comparison object may include, for example, its own store, the same or similar products, etc. The output data types may include, for example, a quantitative type or a qualitative type, etc. The constraint dimension may refer to a constraint, for example, may be participation in a particular promotional activity, for a specified crowd, and so forth.

For easy understanding, the following illustrates possible implementation manners of the evaluation conditions, and it should be noted that the present application is not limited thereto, and may be set in connection with actual requirements:

for example, in the case where the object is a product, the evaluation condition may be, for example: the dish inquiry conversion rate in nearly 30 days is higher than the average XX% of shops. The corresponding adjustment mode can be, for example, advertisement delivery, adding to a specific promotion page, sending promotion messages to a specified crowd, etc.

The specified types corresponding to the evaluation conditions can comprise, for example, a near 30-day inquiry conversion rate and a near 30-day product with the front 10 inquiry conversion rate in the store, so that the near 30-day inquiry conversion rate of the product with the front 10 inquiry conversion rate in the store can be calculated to obtain a store average value according to the evaluation conditions, and further whether the near 30-day inquiry conversion rate of the product is higher than the store average value XX% can be judged.

For example, in the case where the object is a store, the evaluation condition may be, for example: the number of products exposed in the near 90 days is lower than the average value of the same row; the corresponding adjustment method may be, for example, sending a promotion message to a specified crowd, etc.

In addition, a corresponding evaluation type or the like may also be determined according to at least one target evaluation condition to which the object corresponds.

205: and generating an evaluation result according to at least one adjustment mode.

206: and feeding back the evaluation result to the user.

The evaluation result can prompt the user of the at least one adjustment mode, so that the user can conveniently and intuitively determine the object adjustment mode without self-reading and self-making the adjustment mode by combining personal experience, and the evaluation accuracy is ensured.

In the embodiment, the personalized evaluation of the object is realized by utilizing the evaluation rule, and an accurate adjustment mode can be provided for the user without manually reading data by the user, so that more personalized and accurate object evaluation is realized, and the object evaluation effect is improved.

In some embodiments, to facilitate the user's understanding of the reason for evaluation, etc., the method may further include:

and combining at least one index data and at least one target evaluation condition to generate evaluation information.

The evaluation result may be generated based on at least one adjustment and the evaluation information.

Alternatively, the evaluation information may be generated in combination with at least one index data, at least one target evaluation condition, and an evaluation type. The assessment information can inform the user of the opportunities or problems, the reasons for the existence of the opportunities or problems and the like, so that the current situation of the object can be known, whether the market demands are met or not and the like.

For example, the evaluation condition is that the payment conversion rate is higher than X% and is a new product of nearly 90 days, and the advertisement is not put in, etc.; the at least one index data may include payment conversion rate, product type, whether to participate in promotion, etc.; the evaluation type is an opportunity type; the corresponding evaluation information may be, for example: the market growth space is large, and the products can obtain a certain market effect, so that the popularization and investment can be increased, and the market can be preempted; the product is in an emerging market, the conversion of the current product is high, and the pay drainage can be increased to make explosive products.

As an alternative, the evaluation information corresponding to the combination of different evaluation conditions may be defined in the evaluation rule, and thus, the evaluation information corresponding to the configuration in the evaluation rule may be determined by combining at least one index data and at least one target evaluation condition.

The evaluation rule may be an information identifier corresponding to the specific corresponding configuration evaluation information, and the evaluation information may be stored in the information base, so that the corresponding evaluation information may be searched according to the information identifier.

The evaluation information may include text contents in different languages, so that the evaluation information corresponding to the text contents belonging to the target voice corresponding to the information identifier may be searched according to the information identifier and the target language corresponding to the country to which the user belongs.

Alternatively, the at least one index data and the at least one target evaluation condition may be input into a first generation model, and evaluation information may be generated using the first generation model.

The first generative model may be obtained in advance by training.

By feeding back the evaluation information to the user, the recommendation reason of the adjustment mode is increased, the interpretability of the evaluation result is improved, the trust feeling of the evaluation result is improved by the user, and finally the object adjustment is improved, so that the system utilization rate and the like can be improved.

In some embodiments, in order to facilitate the user to understand the reason for recommending the at least one adjustment mode, increasing the interpretability, improving the trust feeling of the adjustment mode, and the like, the generating the evaluation result according to the at least one adjustment mode may include:

generating recommendation information according to at least one adjustment mode; and generating an evaluation result comprising the evaluation information and the recommendation information.

For example, the adjustment mode is advertisement delivery, and the corresponding recommendation information may be: the advertisement delivery can rapidly drain the product, obtain the conversion opportunity, propose advertisement delivery, and the like.

The evaluation rule may define recommendation information corresponding to different adjustment modes, or, of course, may input at least one adjustment mode into the second generation model, and generate recommendation information using the second generation model.

Optionally, an information identifier corresponding to the recommended information may be specifically configured in the evaluation rule, and the recommended information is saved in the information base, so that the recommended information may be searched from the information base based on the information identifier. The recommended information may include document contents in different languages, so that the recommended information corresponding to the document contents belonging to the target voice corresponding to the information identifier may be searched according to the information identifier and the target language of the country to which the user belongs.

In addition, in some embodiments, in order to further improve the reliability of the evaluation result, improve the accuracy of the evaluation result, and the like, the generating the evaluation result including the evaluation information and the recommendation information may include:

based on the recommendation information, the evaluation information and the user characteristics of the user, an evaluation result is generated by using the information processing model.

The user characteristics may include, for example, a document type, a document format, etc. that are preferred by the user, so that the recommendation information and the evaluation information may be rearranged by using the information processing model, and the evaluation result may be output.

The information processing model can be realized by a large language model, and can be obtained by taking sample recommendation information, sample evaluation information and sample user characteristics as input data and taking a sample evaluation result as output data for training in advance.

In addition, the evaluation result can also comprise at least one operation control and prompt information which correspond to the adjustment modes respectively, and the prompt information can be displayed in the operation control to prompt a user to adjust the adjustment modes corresponding to the operation control. Therefore, in some embodiments, the method may further include determining an operation control and a prompt corresponding to the at least one adjustment mode respectively;

The evaluation result including the evaluation information, the recommendation information and the operation control and the prompt information respectively corresponding to at least one adjustment mode can be generated.

The operation control can sense the operation of a user to determine a target adjustment mode selected by the user and the like.

As can be seen from the above description, the evaluation rule may be determined first, then the object is recalled according to the evaluation rule, and after the evaluation result is generated, the evaluation result may be sent to the user account in the form of a message notification, and in addition, in some embodiments, the foregoing feedback of the evaluation result to the user may include:

receiving an evaluation request of a user for an object to be processed; and feeding back the evaluation result to the user.

Wherein, the object evaluation prompt information may be sent to the user terminal, and the evaluation request may be generated in response to a triggering operation for the object evaluation prompt information.

In some embodiments, because one object may hit multiple evaluation rules, feeding back the evaluation results to the user may include:

receiving an evaluation request of a user for an object to be processed; and under the condition that the object hits a plurality of evaluation rules, sequentially feeding back evaluation results corresponding to the plurality of evaluation rules to the user according to the priorities of the plurality of evaluation rules.

Namely, the evaluation results corresponding to the evaluation rules are fed back to the user one by one. The priorities of the plurality of evaluation rules may be preset.

In some embodiments, sequentially feeding back the evaluation results corresponding to the plurality of evaluation rules to the user may include:

feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user; and receiving a switching request sent by a user, and feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user from the non-feedback evaluation results according to the priorities of the plurality of evaluation rules.

The evaluation result may further include a handover prompt message, and the handover request may be generated and transmitted for a triggering operation of the handover prompt message.

In some embodiments, the method may further comprise:

receiving a confirmation request of a user for a target adjustment mode selected from at least one adjustment mode; and processing the object according to the target adjustment mode.

That is, the user can determine a target adjustment mode according with the own requirement according to at least one adjustment mode in the evaluation result, and then can process the object according to the target adjustment mode. Therefore, in the embodiment of the application, not only can automatic object evaluation be realized, but also automatic object adjustment can be realized, the object improvement mode is improved, and the user experience is improved.

In some embodiments, as can be seen from the above description, the evaluation result may further include an operation control corresponding to at least one adjustment manner and prompt information displayed in the operation space, where the generating the evaluation result according to the at least one adjustment manner may be determining the operation control corresponding to the at least one adjustment manner respectively; generating an evaluation result comprising operation controls corresponding to at least one adjustment mode respectively;

the receiving the confirmation request of the user aiming at the target adjustment mode may be: and receiving a confirmation request triggered by an operation control corresponding to the target adjustment mode by the user.

That is, the confirmation request may be generated by the user end in response to the triggering operation of the operation control corresponding to the target adjustment mode by the user.

In some embodiments, the processing the object according to the target adjustment manner may include: and sending adjustment prompt information to the user terminal, and processing the object according to the adjustment request sent by the user and the target adjustment mode. The adjustment prompt information can prompt the user to process the confirmation information and the like required by the object according to the target adjustment mode, so that the user can complete adjustment according to the prompt requirement.

In some embodiments, to facilitate the user's understanding of the improvement effect after the object adjustment, the method may further include:

After processing the object according to the target adjustment mode, counting index change information of at least one index data in a preset time; and feeding back index change information to the user.

The index change information can comprise index data corresponding to different moments in preset time, and can be in a text form or a statistical chart form, so that the index data at different moments can be visually presented, and a user can conveniently check the change trend.

In some embodiments, the method may further comprise:

acquiring feedback information of a user aiming at an evaluation result; generating update prompt information aiming at the evaluation rule by combining the feedback information and the index change information; and feeding back the updated prompt information to related personnel.

The evaluation result may further include a feedback control, where the feedback information may be generated in response to a feedback operation of the user on the feedback control, and the feedback control may include, for example, a confirmation control whether the evaluation result is satisfied.

The update prompt message may include feedback information and index change information, so that the relevant personnel can know and decide whether to improve the evaluation rule.

Fig. 3 is a flowchart of another embodiment of an object processing method provided in the embodiment of the present application, where the technical scheme of the present embodiment is executed by a user side, and the method may include the following steps:

301: object assessment hints for at least one object are provided at a user interface.

302: and responding to the confirmation operation of the prompt information for evaluating any object, and sending an evaluation request for the corresponding object.

The server may determine, according to the evaluation request, an evaluation rule corresponding to the object, and the like, and the evaluation result of each object may be generated in advance at regular time, and the server may search, according to the evaluation request, the evaluation result corresponding to the object and send the result to the client.

303: and obtaining at least one evaluation result corresponding to the object.

Wherein, the evaluation result can be specifically generated according to at least one adjustment mode corresponding to the object; at least one adjustment mode is determined according to at least one target evaluation condition in the evaluation rule which is met by at least one index data corresponding to the object; at least one index data is determined from object related information of the object.

The specific generation manner of the evaluation result may be described in detail in the above corresponding embodiments, and the detailed description is not repeated here.

304: at least one evaluation result is presented in a user interface.

In the embodiment, through a man-machine interaction mode, personalized evaluation of the object is realized based on the evaluation rule, an accurate adjustment mode can be provided for a user without manually reading data by the user, and the user can conveniently operate and view the object, so that more personalized and accurate object evaluation is realized, and the object evaluation effect is improved.

In some embodiments, the presenting at least one evaluation result in the user interface includes:

displaying an evaluation result corresponding to the evaluation rule with the highest priority on a user interface;

and responding to a switching request triggered by a user, and displaying an evaluation result corresponding to the evaluation rule with the highest priority from the undelivered evaluation results.

The switching control can also be displayed in a user interface, and the user terminal can generate a switching request in response to switching operation triggered by a user on the switching control.

In some embodiments, each evaluation result may include at least one operation control corresponding to the adjustment mode respectively;

the method may further include:

responding to a confirmation operation triggered by an operation control aiming at a target adjustment mode, and sending a confirmation request; the validation request is used to instruct the processing of the object to be processed in a targeted manner.

In addition, the evaluation result may further include evaluation information generated based on at least one target evaluation condition, recommendation information corresponding to at least one adjustment mode, and the like.

In some embodiments, presenting at least one evaluation result at the user interface may include:

displaying result prompt information corresponding to any evaluation result on a user interface; and responding to the triggering operation aiming at the result prompt information, and displaying the evaluation result on a user interface.

The result prompt information may include extracting key information or summary information from the evaluation result.

For ease of understanding, as shown in fig. 4a, a schematic diagram of one possible display of a user interface in one practical application is shown, in which object evaluation prompt information 401 corresponding to each object may be provided. The object evaluation prompt information may be in the form of a control, and the user may send an evaluation request to the server by operating the object evaluation prompt information 401.

The user side may obtain a corresponding evaluation result from the server side, and as shown in fig. 4b, the evaluation result 402 may be shown in the user interface. The evaluation result may include evaluation information generated based on at least one target evaluation condition, recommendation information corresponding to at least one adjustment mode, and the like.

In addition, a switch control 403 may be displayed in the user interface, and the user may trigger a switch request for the switch control, so that the next evaluation result may be displayed in a switching manner.

In addition, the evaluation result may include at least one operation control 404 corresponding to each adjustment mode, and the user may trigger a confirmation request for the operation control of the target adjustment mode.

It can be seen from the above description that the evaluation rule may include an evaluation condition, an evaluation type, an object type, an adjustment manner, evaluation information corresponding to the evaluation condition, and the like, and further include an evaluation target, where the evaluation target may be, for example, an increase in exposure, an increase in conversion rate, and the like.

The evaluation rule in the embodiment of the present application may be developed by a relevant person, for example, a configuration code of the evaluation rule may be as follows:

"id":1, (rule identification for identifying evaluation rules)

"description": "near 30 days the visitor number is below threshold XXX",

"rule"："isCgs＝Y and payCount>payAvg and buyerCount>＝1",

"ruleName": "Low_flow_for_monitor", (define evaluation requirement)

"score"：1,

"target": "monitor", (defining an evaluation target)

"isValid"：true,

"type": "problem", (defining evaluation type)

"hoverMcms"："intl-mydata.diagnose.rule.visitorslowtag",

"hoverMcmsValue": "near 30 days visitor count is below threshold XXX", (evaluation conditions are defined)

"mcmsKey"："intl-mydata.diagnose.rule.visitorslowsummary",

"mcmsValue": "visitor number is low, flow needs to be increased", (evaluation information is defined)

"actions": "P4P, showCase, SNS, top_ranking, new_Arrival, spotlight_Saving" (defining the adjustment mode)

"reasonMcms"："intl-mydata.diagnose.rule.visitors",

"releasmcmsvalue": "the access amount of the product does not reach the basic value XX, more flow is needed to be introduced in the current stage, and advertisement delivery can be carried out. (defining assessment information).

Furthermore, since the evaluation result may include an adjustment manner, the adjustment manner may be configured as follows, for example:

"id":1, (definition mode identification for identifying adjustment mode)

"action"："P4P",

"actionName": "P4P" (defining the adjustment means, P4P stands for advertisement delivery)

"score"：1,

"isValid"：true,

"description"："P4P",

"mcmsKey"："intl-mydata.diagnose.action.p4p",

"mcmsValue": "80% P4P user obtains flow increment by opening P4P [ what course is P4P ], commodity is not yet put in shop window", (definition of recommended information)

"buttonMcmsKey"："intl-mydata.diagnose.action.p4pbutton",

"button McmsValue": "evoked [ join P4P plan ] component", (define operation control)

"actionMcms"："intl-mydata.diagnose.action.p4p.suggestion",

"actionMcmsValue": "get traffic in P4P delivery plan" (define prompt information for operation control display)

"url"："",

"urlMcmsKey"："intl-mydata.diagnose.action.p4plink"

The above codes are merely illustrative, and the present application is not limited thereto.

In addition, in order to facilitate rule configuration, as shown in fig. 5, the embodiment of the present application further provides a rule configuration method, and the technical solution of the present embodiment may be executed by a configuration end, where the method may include the following steps:

501: a rule configuration interface is provided.

502: a plurality of parameter components are provided in a rule configuration interface.

503: in response to an input operation for the plurality of parameter components, the input plurality of parameter content is determined.

504: an evaluation rule is generated based on the plurality of parameter contents.

The plurality of parameter components may include, for example, parameter components corresponding to rule identification, evaluation target, evaluation type, object type, index type, evaluation condition, adjustment mode, and the like, respectively.

According to a plurality of parameter contents input by a user, a rule code can be automatically generated, and in the embodiment, evaluation rules can be automatically generated only by inputting the parameter contents by the user, so that convenience of rule configuration is improved.

Wherein, generating the evaluation rule according to the plurality of parameter contents may be sending the plurality of parameter contents to the server in response to the release request, so that the server generates the evaluation rule according to the plurality of parameter contents.

The evaluation rule is used for combining at least one index data extracted from object related information of an object, judging whether the object accords with evaluation conditions in the evaluation rule, determining at least one corresponding adjustment mode according to at least one target evaluation condition which the object accords with, and generating an evaluation result according to the at least one adjustment mode; the evaluation result is used for being fed back to the user. The specific implementation of object evaluation using evaluation rules may be omitted from the embodiments shown in fig. 2 or fig. 3.

In order to facilitate understanding, the technical solution of the embodiment of the present application is described below with reference to the schematic scenario diagram shown in fig. 6, as shown in fig. 6, related personnel may configure the evaluation rule through the configuration terminal 103 and the service terminal 101, and the service terminal 101 may send the object evaluation prompt information of at least one object corresponding to the user terminal 102; the user terminal 102 may display object evaluation prompt information of at least one object in the user interface, and may send an evaluation request for a corresponding object to the server terminal 101 in response to a confirmation operation for any one of the object evaluation prompt information; the server 101 may first send an evaluation result corresponding to an evaluation rule with the highest priority, which is not currently displayed and corresponds to the object, to the client 102; the user terminal 102 may display the evaluation result in the user interface, the user terminal 102 may also sense a switching operation of the user, send a switching request to the server terminal 101, and the server terminal 101 may send an evaluation result corresponding to an evaluation rule with the highest priority, which is not currently displayed, to the user terminal 102, so as to display the evaluation result in the user terminal 102.

The evaluation result server 101 may periodically generate an evaluation instruction, so that an evaluation rule may be determined according to the evaluation instruction, and then, according to an object type and/or an index type specified by the evaluation rule, an object to be processed that meets the object type and/or includes index data corresponding to the index type is determined, and the object is evaluated. The specific execution flow of the server 101 may refer to the flow chart shown in fig. 7, as shown in fig. 7, an evaluation task is triggered periodically, so as to generate an evaluation instruction 701, then an evaluation task 702 may be executed, an object evaluation may be performed in response to the evaluation instruction, an evaluation rule may be pulled from a rule configuration library 703, and an object may be evaluated based on the evaluation rule, so as to obtain an evaluation result. The obtained evaluation results may be stored in the results repository 704, and the user may send an evaluation request to query the results repository 704 for the corresponding diagnostic results, etc. In addition, the user side can also send the feedback result of the user aiming at the evaluation result to the server side so as to realize diagnosis feedback.

Of course, the server 101 may also receive the evaluation request, determine the evaluation rule corresponding to the object, and evaluate the object in real time.

The technical solution of the embodiment of the present application may be specifically implemented by using a system architecture diagram shown in fig. 8, where the system architecture may include a data layer, a storage layer, a service layer, and an access layer.

The data layer may include various databases, such as ODPS, PAI, blink, for storing object related information, such as base data, industry data, transaction data, real-time behavior data, offline behavior data, and the like.

The storage layer may include various storage systems such as mysql, opensearch, hbase, oneservice, tair and the like to store index data and the like extracted from the object-related information.

The service layer may include a service center, an arrangement engine, a query engine, a service engine, and the like, where the service center defines an index type and a data source, and the arrangement engine provides a visual configuration interface for related personnel to perform arrangement operation, generate an evaluation rule, and the like, and the query engine is configured to capture index data from a storage layer according to the index type defined by the service center, combine the index data by the service engine, determine whether an object meets an evaluation condition in the evaluation rule, determine at least one corresponding adjustment mode according to at least one target evaluation condition met by the object, and generate an evaluation result according to the at least one adjustment mode, and the like.

The access layer is responsible for interfacing with the user terminal, and can receive the evaluation request of the user terminal, perform service authentication to determine whether the user meets the evaluation requirement, and the like, and can perform log statistics, and can perform flow detection, and the like, under the condition that the number of the evaluation requests is large.

In addition, an operation and maintenance layer can be included to provide operation and maintenance support, such as detecting storage capacity, data, pages, etc.

The system architecture shown in fig. 8 may be implemented as the aforementioned server, and of course, the data layer and the storage layer may also be implemented as separate systems separately, which is not limited in this application.

In practical applications, the object may refer to a product provided by a user, in an e-commerce scenario, that is, a commodity, and of course, the object may also refer to a store opened by the user, so as to display or manage multiple products provided by the user. A user may refer to an enterprise user, etc., and a consumer to whom the offered product is directed may also be an enterprise user. That is, the technical solution of the embodiment of the present application may be specifically applied to B2B (Business-to-Business) scenarios, but the present application is not limited thereto, and is also applicable to B2C (Business-to-Consumer), C2C (customer to customer, person-to-person) and other e-commerce scenarios.

According to the technical scheme, the data in the website can be subjected to differential analysis aiming at different industries, so that the establishment of faster, more efficient and more accurate market analysis and adjustment modes is realized, the marketing efficiency and effect are improved, the intelligent data analysis and interpretation are realized, the accuracy and interpretation of the data analysis are improved, more accurate market analysis and marketing strategy establishment basis is provided for users, and the product competitiveness and market share are improved.

Fig. 9 is a schematic structural diagram of an embodiment of an object processing apparatus according to an embodiment of the present application, where the apparatus may include:

a first determining module 901, configured to determine an object to be processed and an evaluation rule;

a data extraction module 902, configured to extract at least one index data from the object related information of the object;

an object evaluation module 903, configured to determine, in combination with the at least one index data, whether the object meets an evaluation condition in the evaluation rule;

a second determining module 904, configured to determine at least one corresponding adjustment mode according to at least one target evaluation condition that is met by the object;

a first generating module 905, configured to generate an evaluation result according to the at least one adjustment manner;

And a feedback module 906, configured to feed back the evaluation result to the user.

In some embodiments, the first determination module may specifically determine the evaluation rule; determining an object to be processed which accords with the object type and/or comprises index data corresponding to the index type according to the object type and/or the index type specified by the evaluation rule;

the data extraction module may specifically extract, from the object related information of the object, at least one index data corresponding to the index type specified by the evaluation rule.

In some embodiments, the second determination module may determine the evaluation rule, in particular in response to an evaluation instruction; the evaluation instructions are generated periodically.

In some embodiments, the first determining module determines, according to the object type and/or the index type specified in the evaluation rule, an object to be processed that conforms to the object type and/or includes index data corresponding to the index type includes: and determining an object to be processed which accords with the object type and/or comprises index data corresponding to the index type from at least one object which meets the evaluation requirement according to the object type and/or the index type specified in the evaluation rule.

In some embodiments, the apparatus further comprises:

the second generation module is used for combining the at least one index data and the at least one target evaluation condition to generate evaluation information;

the second generation module may specifically generate recommendation information according to the at least one adjustment mode; and generating an evaluation result comprising the evaluation information and the recommendation information.

In some embodiments, the second generating module may specifically generate the evaluation result by using an information processing model based on the recommendation information, the evaluation information and the user characteristics of the user.

In some embodiments, the feedback module may specifically receive an evaluation request from a user for the object to be processed, and feedback the evaluation result to the user.

In some embodiments, the feedback module may specifically receive an evaluation request of a user for the object to be processed, and in case that the object hits a plurality of evaluation rules, sequentially feed back evaluation results corresponding to the plurality of evaluation rules to the user according to priorities of the plurality of evaluation rules.

In some embodiments, the feedback module sequentially feeds back, to the user, the evaluation results corresponding to the plurality of evaluation rules respectively, including: feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user; and receiving a switching request sent by the user, and feeding back an evaluation result corresponding to the evaluation rule with the highest priority to the user from the non-feedback evaluation results according to the priorities of the plurality of evaluation rules.

In some embodiments, the apparatus may further comprise:

the object processing module is used for receiving a confirmation request of the user for the target adjustment mode selected from the at least one adjustment mode; and processing the object according to the target adjustment mode.

In some embodiments, the first generating module may specifically determine operation controls corresponding to the at least one adjustment manner respectively; generating an evaluation result comprising operation controls respectively corresponding to the at least one adjustment mode;

the receiving, by the object processing module, the confirmation request of the user for the target adjustment mode may specifically be receiving a confirmation request triggered by the operation control corresponding to the target adjustment mode by the user.

In some embodiments, the feedback module is further configured to count index change information of the at least one index data within a predetermined time after the object is processed according to the target adjustment mode; and feeding back the index change information to the user.

In some embodiments, the apparatus may further comprise:

the updating module is used for acquiring feedback information of the user aiming at the evaluation result; generating update prompt information for the evaluation rule by combining the feedback information and the index change information; and feeding back the updated prompt information to related personnel.

In some embodiments, the first determining module is specifically configured to receive an evaluation request sent by the user, and determine an object to be processed that requests evaluation; and determining an evaluation rule corresponding to the object.

In some embodiments, the object comprises a product or store;

The object processing apparatus shown in fig. 9 may perform the object processing method described in the embodiment shown in fig. 2, and its implementation principle and technical effects are not repeated. The specific manner in which the respective modules and units of the object processing apparatus in the above embodiments perform operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

Fig. 10 is a schematic structural diagram of another embodiment of an object processing apparatus according to an embodiment of the present application, where the apparatus may include:

a first providing module 1001, configured to provide object assessment prompt information of at least one object in a user interface;

a request sending module 1002, configured to send an evaluation request for a corresponding object in response to a confirmation operation for evaluating the prompt information for any one object;

a result obtaining module 1003, configured to obtain at least one evaluation result corresponding to the object; the evaluation result is generated according to at least one adjustment mode corresponding to the object; the at least one adjustment mode is determined according to at least one target evaluation condition in the evaluation rule which is met by at least one index data corresponding to the object; the at least one index data is determined from object related information of the object;

the result display module 1004 is configured to display the at least one evaluation result on the user interface.

In some embodiments, the evaluation result includes operation controls corresponding to the at least one adjustment mode respectively;

the request sending module is also used for responding to the confirmation operation triggered by the operation control aiming at the target adjustment mode and sending a confirmation request; the confirmation request is used for indicating the object to be processed according to the target adjustment mode.

In some embodiments, the result display module may specifically display, on the user interface, an evaluation result corresponding to the evaluation rule with the highest priority; and responding to the switching request triggered by the user, and displaying an evaluation result corresponding to the evaluation rule with the highest priority from the undelivered evaluation results.

In some embodiments, the evaluation result includes evaluation information generated based on at least one target evaluation condition, recommendation information corresponding to the at least one adjustment mode, and operation control and prompt information corresponding to the at least one adjustment mode, respectively.

The object processing apparatus shown in fig. 10 may perform the object processing method described in the embodiment shown in fig. 3, and its implementation principle and technical effects are not repeated. The specific manner in which the respective modules and units of the object processing apparatus in the above embodiments perform operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

Fig. 11 is a schematic structural diagram of an embodiment of a rule configuration device provided in an embodiment of the present application, where the device may include:

a second providing module 1101 for providing a rule configuration interface; and providing a plurality of parameter components at the rule configuration interface;

A content determination module 1102 for determining a plurality of parameter contents inputted in response to an input operation for the plurality of parameter components.

The rule generating module 1103 is configured to generate an evaluation rule according to the plurality of parameter contents.

The evaluation rule is used for combining at least one index data extracted from object related information of an object, judging whether the object accords with evaluation conditions in the evaluation rule, determining at least one corresponding adjustment mode according to at least one target evaluation condition which the object accords with, and generating an evaluation result according to the at least one adjustment mode; the evaluation result is used for being fed back to the user.

The object processing apparatus shown in fig. 11 may execute the rule configuration method described in the embodiment shown in fig. 5, and its implementation principle and technical effects are not repeated. The specific manner in which the respective modules and units of the object processing apparatus in the above embodiments perform operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

Embodiments of the present application also provide a computing device, as shown in fig. 12, which may include a storage component 1201 and a processing component 1202;

The storage component 1201 includes one or more computer instructions that are invoked by the processing component 1202 to implement the object processing method of FIG. 2 or the object processing method of FIG. 3 or the rule configuration method of FIG. 5.

Of course, the computing device may necessarily include other components as well, such as input/output interfaces, display components, communication components, and the like.

In the case where the processing component in the computing device is used to implement the object processing method as shown in fig. 3 or the rule configuration method as described in fig. 5, the computing device may further include a display component to perform a corresponding display operation.

The input/output interface provides an interface between the processing component and a peripheral interface module, which may be an output device, an input device, etc. The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, and the like.

Wherein the processing component may include one or more processors to execute computer instructions to perform all or part of the steps of the methods described above. Of course, the processing component may also be implemented as one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic elements for executing the methods described above.

The storage component is configured to store various types of data to support operations at the terminal. The memory component may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.

The display component may be an Electroluminescent (EL) element, a liquid crystal display or a micro display having a similar structure, or a retina-directly displayable or similar laser scanning type display.

It should be noted that, in the case where the above computing device implements the object processing method shown in fig. 2, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform. It may be implemented as a distributed cluster of multiple servers or terminal devices, or as a single server or single terminal device.

In the case where the above computing device implements the object processing method shown in fig. 3 or the rule configuration method shown in fig. 5, the computing device may be specifically implemented as an electronic device, where the electronic device may be a device that is used by a user and has functions of computing, surfing the internet, communication, and the like, and may be, for example, a mobile phone, a tablet computer, a personal computer, a wearable device, and the like.

The embodiment of the application further provides a computer readable storage medium, in which a computer program is stored, where the computer program can implement the object processing method of the embodiment shown in fig. 2, the object processing method of the embodiment shown in fig. 3, or the rule configuration method of the embodiment shown in fig. 5 when executed by a computer. The computer-readable medium may be contained in the electronic device described in the above embodiment; or may exist alone without being incorporated into the electronic device.

The embodiments of the present application further provide a computer program product, which includes a computer program loaded on a computer readable storage medium, where the computer program when executed by a computer may implement an object processing method according to the embodiment shown in fig. 2, or an object processing method according to the embodiment shown in fig. 3, or a rule configuration method according to the embodiment shown in fig. 5. In such embodiments, the computer program may be downloaded and installed from a network, and/or installed from a removable medium. The computer program, when executed by a processor, performs the various functions defined in the system of the present application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. An object processing method, comprising:

determining an object to be processed and an evaluation rule;

generating an evaluation result according to the at least one adjustment mode;

and feeding back the evaluation result to the user.

2. The method of claim 1, wherein determining the object to be processed and evaluating the rule comprises:

Determining an evaluation rule;

3. The method as recited in claim 1, further comprising:

4. The method of claim 3, wherein the generating the evaluation result including the evaluation information and the recommendation information comprises:

5. The method of claim 1, wherein the feeding back the evaluation result to the user comprises:

receiving an evaluation request of a user for the object to be processed;

6. The method as recited in claim 1, further comprising:

and processing the object according to the target adjustment mode.

7. The method as recited in claim 6, further comprising:

and feeding back the index change information to the user.

8. The method as recited in claim 7, further comprising:

acquiring feedback information of the user aiming at the evaluation result;

And feeding back the updated prompt information to related personnel.

9. The method of claim 1, wherein the object comprises a product or a store;

10. An object processing method, comprising:

And displaying the at least one evaluation result on the user interface.

11. The method of claim 10, wherein the evaluation result includes operation controls corresponding to the at least one adjustment mode respectively;

the method further comprises the steps of:

responding to a confirmation operation triggered by an operation control aiming at a target adjustment mode, and sending a confirmation request; the validation request is to instruct processing of the object in the target adjustment manner.

12. The method of claim 10, wherein the presenting the at least one evaluation result at the user interface comprises:

13. A rule configuration method, comprising:

providing a rule configuration interface;

14. A computing device comprising a processing component and a storage component;

the storage component stores one or more computer instructions; the one or more computer instructions are to be invoked by the processing component to implement the object handling method of any one of claims 1 to 9 or the object handling method of any one of claims 10 to 12 or the rule configuration method of claim 13.

15. A computer-readable storage medium, characterized in that a computer program is stored, which, when being executed by a computer, implements the object handling method according to any one of claims 1 to 9 or the object handling method according to any one of claims 10 to 12 or the rule configuration method according to claim 13.