CN110706035A - Updating effect evaluation method and device, storage medium and electronic equipment - Google Patents
Updating effect evaluation method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application discloses an updating effect evaluation method and device, a storage medium and electronic equipment. The method comprises the following steps: and if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request. Acquiring a first recommendation result of an online environment according to the recommendation information request; and acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request. And comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment. By operating the technical scheme provided by the application, the purpose that the same request content is simultaneously obtained to the return results of the online environment and the pre-sending environment can be achieved, and developers can analyze the effect of updating the content.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to an updating effect evaluation method and device, a storage medium and electronic equipment.
Background
With the rapid development of technology, various applications recommend information based on the search content of the user, and have become an important way to assist the user in targeting information.
However, since the version of the application program needs to be updated continuously, new functional modules and business logic are often added when the version is updated. When the algorithm for recommending information for the user needs to be updated, the application program needs to be updated. In order to improve the updating effect of the application program, a pre-launch environment and an online environment are often used by different users. And the users in the pre-release environment white list can experience the functions of the new version in advance, and can release the functions to the online environment for all users of the application program to use only when the update has no problem. This provides a data base for improvements in whether new versions are running problematically and need to be more optimized. However, since the users in the pre-distribution environment and the online environment are separated, if the content updated in the pre-distribution environment is compared with the content in use in the online environment, the basic information of the user is not matched, and the obtained result is not comparable.
Disclosure of Invention
The embodiment of the application provides an updating effect evaluation method and device, a storage medium and electronic equipment, so that the purpose that the same request content is simultaneously obtained to the return results of an online environment and a pre-sending environment, and developers can analyze the effect of updating the content is achieved.
In a first aspect, an embodiment of the present application provides an update effect evaluation method, where the method includes:
if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request;
acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
In a second aspect, an embodiment of the present application provides an apparatus for evaluating an update effect, including:
the recommendation information request marking module is used for marking the recommendation information request to obtain a marked recommendation information request if the recommendation information request is detected;
the recommendation result acquisition module is used for acquiring a first recommendation result of the online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and the effect determining module is used for comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method for evaluating the update effect according to the present application.
In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable by the processor, where the processor executes the computer program to implement the method for evaluating the update effect according to the embodiment of the present application.
According to the technical scheme provided by the embodiment of the application, if the recommendation information request is detected, marking is carried out on the recommendation information request to obtain a marked recommendation information request; acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request; and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment. By adopting the technical scheme provided by the embodiment, the purpose that the same request content is simultaneously obtained to the return results of the online environment and the pre-sending environment for developers to analyze the effect of updating the content can be realized.
Drawings
Fig. 1 is a flowchart of an update effect evaluation method provided in an embodiment of the present application;
FIG. 2 is a flowchart of an update effect evaluation method provided in an embodiment of the present application;
FIG. 3 is a flowchart of a method for evaluating an update effect according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of an apparatus for evaluating an update effect according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Fig. 1 is a flowchart of an update effect evaluation method provided in an embodiment of the present application, where the present embodiment is suitable for analyzing a situation of an update content effect, and the method may be executed by an update effect evaluation device provided in an embodiment of the present application, where the update effect evaluation device may be implemented by software and/or hardware, and may be integrated in an electronic device such as an intelligent terminal.
As shown in fig. 1, the method for evaluating the update effect includes:
and S110, if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request.
The recommendation information request can be issued passively by the system based on the search operation of the user, such as intelligent sorting, default sorting, and the like. Or may be issued by the system actively, such as a home page recommendation, a detail page recommendation, etc., which is not limited in this embodiment. In the process of evaluating the updating effect, the user for testing can randomly obtain the user currently active on the line.
The recommendation information request is marked, and the purpose is to distinguish the recommendation information request from the marking recommendation information request so as to process the recommendation information request in different environments. The recommendation information request and the mark recommendation information request have the same request parameters, and only the difference is that the mark recommendation information request is marked.
S120, acquiring a first recommendation result of the online environment according to the recommendation information request; and acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request.
The first recommendation result is used for reflecting a recommendation result generated by the recommendation information request in an online environment. The second recommendation result is used for representing the recommendation result generated by the recommendation information request in the pre-sending environment.
S130, comparing the first recommendation result with the second recommendation result, and determining the content updating effect of the pre-sending environment.
And comparing the first recommendation result with the second recommendation result to obtain the difference generated in the online environment and the pre-sending environment aiming at the same recommendation information request, so as to obtain the effect generated by the updated recommendation strategy or model in the pre-sending environment.
Taking intelligent sorting as an example, in an online environment, a user obtains intelligent sorting for searched contents, so that the system passively sends a recommendation information request. The system obtains a first recommendation result in the online environment, such as a first intelligent recommendation sequence or first intelligent recommendation content, according to the recommendation information request and by analyzing the user information.
In a pre-sending environment, a user obtains intelligent sequencing on searched contents, so that a system passively sends a recommendation information request, and marks the recommendation information request to obtain a marked recommendation information request. The system obtains a second recommendation result in the pre-sending environment, such as a second intelligent recommendation sequence or second intelligent recommendation content, by marking the recommendation information request and analyzing the user information.
And comparing the first intelligent recommendation result with the second intelligent recommendation result to determine the content updating effect of the pre-sending environment.
According to the technical scheme provided by the embodiment of the application, if the recommendation information request is detected, marking is carried out on the recommendation information request to obtain a marked recommendation information request; acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request; and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment. The method can achieve the purpose that the same request content is simultaneously obtained to the return results of the online environment and the pre-sending environment, and developers can analyze the effect of updating the content.
On the basis of the above technical solutions, optionally, marking the recommendation information request to obtain a marked recommendation information request includes:
adding a preset mark field to the recommendation information request to obtain a mark recommendation information request; and when the request interface calls the tag recommendation information request, acquiring a recommendation result corresponding to the tag recommendation information request from a pre-sending environment.
The recommendation information request is added with a preset identification field for processing, so that the recommendation information request is distinguished from the marked recommendation information request, the marked recommendation information request is processed in a pre-sending environment, and a recommendation result in the pre-sending environment is obtained.
On the basis of the technical scheme, optionally, if a recommendation information request is detected, identifying whether the recommendation information request comprises a preset identification field;
if not, marking the recommendation information request; if so, deleting the preset identification field in the recommendation information request, so that when the request interface calls the recommendation information of deleting the preset identification field, acquiring a recommendation result corresponding to the mark recommendation information request from an online environment.
Marking the recommendation information requests without the preset identification fields in the detected recommendation information requests so as to obtain recommendation results corresponding to the marked recommendation information requests from the pre-sending environment. Deleting the preset identification field of the recommendation information request with the preset identification field so as to obtain a recommendation result corresponding to the marked recommendation information request from the online environment. The advantage of this arrangement is that it can be determined whether the sender of the current request is the user using the pre-sent environment through pre-recognition, and if so, the request can simultaneously go to the online environment by deleting the preset identification field, so as to obtain the recommendation results of the two environments.
Fig. 2 is a flowchart of an update effect evaluation method provided in an embodiment of the present application, and this technical solution is explained with respect to a process of obtaining a recommendation result. Compared with the scheme, the scheme compares the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment, and comprises the following steps: respectively extracting the characteristics of each piece of data in the first recommendation result and each piece of data in the second recommendation result; and comparing the first recommendation result with the second recommendation result according to the extracted features, and determining the content updating effect of the pre-sending environment. Specifically, the flow of the update effect evaluation method is shown in fig. 2:
s210, if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request.
S220, acquiring a first recommendation result of the online environment according to the recommendation information request; and acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request.
And S230, respectively extracting the features of each piece of data in the first recommendation result and each piece of data in the second recommendation result.
In the technical scheme, after the first recommendation result and the second recommendation result are obtained, feature extraction can be performed on each piece of data in the first recommendation result and each piece of data in the second recommendation result respectively. The feature extraction may be to extract features of one or more dimensions in each piece of data according to a pre-designed feature extraction manner, as extraction features.
S240, comparing the first recommendation result with the second recommendation result according to the extracted features, and determining the content updating effect of the pre-sending environment.
In the technical scheme, each piece of data in the first recommendation result and each piece of data in the second recommendation result are subjected to feature extraction, and the extracted features are compared, so that the updating effect is evaluated more carefully and accurately.
On the basis of the above technical solutions, optionally, after feature extraction is performed on each piece of data in the first recommendation result and each piece of data in the second recommendation result, the method further includes:
supplementing the feature data extracted from each piece of data to a supplementary field of the piece of data, and performing encapsulation processing;
traversing all data in the first recommendation result and all data in the second recommendation result to obtain an encapsulation result of the first recommendation result and an encapsulation result of the second recommendation result;
correspondingly, comparing the first recommendation result with the second recommendation result according to the extracted features, and determining the content updating effect of the pre-sending environment comprises the following steps:
and comparing the packaging results of the first recommendation result and the second recommendation result one by one to determine the content updating effect of the pre-sending environment.
And filling the data obtained after feature extraction as supplementary fields in the basic fields of the corresponding data for each piece of data, and packaging to form independent fields of each piece of data. Wherein, the basic field is the basic attribute of the searched object directly obtained after searching.
The characteristic data extracted from each piece of data is supplemented to the supplementary fields of the data, the data is packaged, comparison is carried out item by item according to the packaging result, the updating content effect of the pre-sending environment is determined, the searched content is more comprehensive, and the updating effect of the evaluation recommendation information is more accurate.
On the basis of the above technical solutions, optionally, comparing the first recommendation result and the second recommendation result one by one according to the encapsulation result of the first recommendation result and the encapsulation result of the second recommendation result, including:
and sending the encapsulation result of the first recommendation result and the encapsulation result of the second recommendation result to a comparison server so as to receive the comparison results returned by the comparison server one by one.
The comparison server is a machine specially used for performing the encapsulation result comparison service, so that the final updating effect can be obtained more accurately and rapidly.
In order to make the technical solution disclosed in the present application more clear to those skilled in the art, the present application also provides a preferred embodiment.
Fig. 3 is a flowchart of an update effect evaluation method provided in an embodiment of the present application. As shown in fig. 3, the method for evaluating the update effect includes:
s310, a recommendation information request is detected.
S320, identifying whether the recommendation information request comprises a preset identification field; if not, go to S330; if yes, go to S340.
S330, marking the recommendation information request to obtain a marked recommendation information request; and goes to S350.
And S340, deleting the preset identification field in the recommendation information request.
And deleting the preset identification field in the recommendation information request, so that when the request interface calls the recommendation information of deleting the preset identification field, a recommendation result corresponding to the mark recommendation information request is obtained from an online environment.
S350, acquiring a first recommendation result of the online environment according to the recommendation information request without the preset identification field; and acquiring a second recommendation result of the pre-sending environment according to the recommendation information request with the preset identification field.
And S360, obtaining the encapsulation result of the first recommendation result and the encapsulation result of the second recommendation result.
The process of obtaining the encapsulation result of the first recommendation result specifically includes performing feature extraction on each piece of data in the first recommendation result, supplementing the feature data extracted from each piece of data to a supplementary field of the piece of data, performing encapsulation processing, and traversing all data in the first recommendation result to obtain the encapsulation result of the first recommendation result.
The process of obtaining the encapsulation result of the second recommendation result specifically includes performing feature extraction on each piece of data in the second recommendation result, supplementing the feature data extracted from each piece of data to a supplementary field of the piece of data, performing encapsulation processing, and traversing all data in the second recommendation result to obtain the encapsulation result of the second recommendation result.
And S370, determining the updated content effect of the pre-sending environment.
And determining the updating content effect of the pre-sending environment by comparing the packaging result of the first recommendation result and the packaging result of the second recommendation result one by one, wherein the different points are the updating content effect of the pre-sending environment.
Fig. 4 is a schematic structural diagram of an apparatus for evaluating an update effect according to an embodiment of the present application. As shown in fig. 4, the apparatus for evaluating the update effect includes:
a recommended information request marking module 410, configured to mark the recommended information request to obtain a marked recommended information request if the recommended information request is detected;
a recommendation result obtaining module 420, configured to obtain a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and the effect determining module 430 is configured to compare the first recommendation result with the second recommendation result, and determine an update content effect of the pre-sending environment.
According to the technical scheme provided by the embodiment of the application, if the recommendation information request is detected, marking is carried out on the recommendation information request to obtain a marked recommendation information request; acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request; and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment. The method can achieve the purpose that the same request content is simultaneously obtained to the return results of the online environment and the pre-sending environment, and developers can analyze the effect of updating the content.
On the basis of the above technical solutions, optionally, the recommendation information request marking module 410 includes:
the tag recommendation information request acquisition submodule is used for increasing a preset tag field for processing the recommendation information request to obtain a tag recommendation information request; and when the request interface calls the tag recommendation information request, acquiring a recommendation result corresponding to the tag recommendation information request from a pre-sending environment.
On the basis of the above technical solutions, optionally, the marked recommendation information request acquisition sub-module further includes a preset identification field recognition unit, configured to, if a recommendation information request is detected, recognize whether the recommendation information request includes a preset identification field;
if not, marking the recommendation information request; if so, deleting the preset identification field in the recommendation information request, so that when the request interface calls the recommendation information of deleting the preset identification field, acquiring a recommendation result corresponding to the mark recommendation information request from an online environment.
On the basis of the above technical solutions, optionally, the effect determining module 430 includes a feature extraction sub-module, configured to perform feature extraction on each piece of data in the first recommendation result and each piece of data in the second recommendation result respectively;
and the characteristic comparison submodule is used for comparing the first recommendation result with the second recommendation result according to the extracted characteristics and determining the content updating effect of the pre-sending environment.
On the basis of the above technical solutions, optionally, further comprising,
the data encapsulation unit is used for supplementing the feature data extracted by each piece of data to the supplementary field of the piece of data after the feature extraction submodule and carrying out encapsulation processing;
the package result acquisition module is used for traversing all data in the first recommendation result and all data in the second recommendation result to obtain a package result of the first recommendation result and a package result of the second recommendation result;
correspondingly, the feature comparison sub-module comprises:
and the packaging result comparison unit is used for comparing the packaging results of the first recommendation result and the second recommendation result one by one to determine the content updating effect of the pre-sending environment.
On the basis of the above technical solutions, optionally, the encapsulation result comparing unit includes:
and the packaging result sending subunit is used for sending the packaging result of the first recommendation result and the packaging result of the second recommendation result to the comparison server so as to receive the comparison results returned by the comparison server one by one.
The product can operate the method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the operation method.
Embodiments of the present application also provide a storage medium containing computer executable instructions, which when executed by a computer processor, are configured to perform a method for evaluating an update effect, the method including:
if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request;
acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network (such as the internet). The second computer system may provide the program instructions to the computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present application is not limited to the above-described evaluation operation of the update effect, and may also execute the relevant operations in the evaluation method of the update effect provided in any embodiments of the present application.
The embodiment of the application provides electronic equipment, and the electronic equipment can be integrated with the evaluation device for the updating effect provided by the embodiment of the application. Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 5, the present embodiment provides an electronic device 500, which includes: one or more processors 520; the storage device 510 is configured to store one or more programs, and when the one or more programs are executed by the one or more processors 520, the one or more processors 520 implement the method for evaluating the update effect provided in the embodiment of the present application, the method includes:
if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request;
acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
Of course, those skilled in the art can understand that the processor 520 may also implement the technical solution of the method for evaluating the update effect provided in any embodiment of the present application.
The electronic device 500 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 5, the electronic device 500 includes a processor 520, a storage 510, an input 530, and an output 540; the number of the processors 520 in the electronic device may be one or more, and one processor 520 is taken as an example in fig. 5; the processor 520, the storage 510, the input device 530, and the output device 540 in the electronic apparatus may be connected by a bus or other means, and are exemplified by a bus 550 in fig. 5.
The storage device 510 is a computer-readable storage medium, and can be used to store software programs, computer executable programs, and module units, such as program instructions corresponding to the update effect evaluation method in the embodiment of the present application.
The storage device 510 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 510 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 510 may further include memory located remotely from processor 520, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 530 may be used to receive input numbers, character information, or voice information, and to generate key signal inputs related to user settings and function control of the electronic apparatus. The output device 540 may include a display screen, speakers, etc.
The electronic device provided by the embodiment of the application can achieve the purpose that the same request content is simultaneously obtained to the return results of the online environment and the pre-sending environment, and developers can analyze the effect of updating the content.
The device for evaluating the update effect, the storage medium and the electronic device provided in the above embodiments may be used to execute the method for evaluating the update effect provided in any embodiment of the present application, and have corresponding functional modules and beneficial effects for executing the method. For technical details that are not described in detail in the above embodiments, reference may be made to the method for evaluating the update effect provided in any of the embodiments of the present application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. A method for evaluating an update effect, comprising:
if the recommendation information request is detected, marking the recommendation information request to obtain a marked recommendation information request;
acquiring a first recommendation result of an online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
2. The method of claim 1, wherein marking the recommendation information request to obtain a marked recommendation information request comprises:
adding a preset mark field to the recommendation information request to obtain a mark recommendation information request; and when the request interface calls the tag recommendation information request, acquiring a recommendation result corresponding to the tag recommendation information request from a pre-sending environment.
3. The method of claim 2, further comprising:
if the recommendation information request is detected, identifying whether the recommendation information request comprises a preset identification field;
if not, marking the recommendation information request; if so, deleting the preset identification field in the recommendation information request, so that when the request interface calls the recommendation information of deleting the preset identification field, acquiring a recommendation result corresponding to the mark recommendation information request from an online environment.
4. The method of claim 1, wherein determining the updated content effect of the pre-launch environment based on the comparison of the first recommendation and the second recommendation comprises:
respectively extracting the characteristics of each piece of data in the first recommendation result and each piece of data in the second recommendation result;
and comparing the first recommendation result with the second recommendation result according to the extracted features, and determining the content updating effect of the pre-sending environment.
5. The method of claim 4, wherein after performing feature extraction on each piece of data in the first recommendation and each piece of data in the second recommendation, the method further comprises:
supplementing the feature data extracted from each piece of data to a supplementary field of the piece of data, and performing encapsulation processing;
traversing all data in the first recommendation result and all data in the second recommendation result to obtain an encapsulation result of the first recommendation result and an encapsulation result of the second recommendation result;
correspondingly, comparing the first recommendation result with the second recommendation result according to the extracted features, and determining the content updating effect of the pre-sending environment comprises the following steps:
and comparing the packaging results of the first recommendation result and the second recommendation result one by one to determine the content updating effect of the pre-sending environment.
6. The method of claim 5, wherein comparing the packaged result of the first recommendation and the packaged result of the second recommendation one by one comprises:
and sending the encapsulation result of the first recommendation result and the encapsulation result of the second recommendation result to a comparison server so as to receive the comparison results returned by the comparison server one by one.
7. An evaluation apparatus for updating effect, comprising:
the recommendation information request marking module is used for marking the recommendation information request to obtain a marked recommendation information request if the recommendation information request is detected;
the recommendation result acquisition module is used for acquiring a first recommendation result of the online environment according to the recommendation information request; acquiring a second recommendation result of the pre-sending environment according to the marked recommendation information request;
and the effect determining module is used for comparing the first recommendation result with the second recommendation result to determine the content updating effect of the pre-sending environment.
8. The apparatus of claim 7, wherein the recommendation information requests a marking module, comprising:
the tag recommendation information request acquisition submodule is used for increasing a preset tag field for processing the recommendation information request to obtain a tag recommendation information request; and when the request interface calls the tag recommendation information request, acquiring a recommendation result corresponding to the tag recommendation information request from a pre-sending environment.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of evaluating an update effect according to any one of claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for evaluating an update effect according to any one of claims 1 to 6 when executing the computer program.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111352833A (en) * | 2020-02-24 | 2020-06-30 | 北京百度网讯科技有限公司 | Recommendation system test method, device, equipment and computer storage medium |
| CN112286553A (en) * | 2020-10-27 | 2021-01-29 | 北京深思数盾科技股份有限公司 | User lock upgrading method, device, system, electronic equipment and storage medium |
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| US20140173586A1 (en) * | 2012-12-14 | 2014-06-19 | Motorola Mobility Llc | Systems and Methods for Managing Updates To Applications |
| CN108958900A (en) * | 2017-05-18 | 2018-12-07 | 腾讯科技（深圳）有限公司 | A kind of task dissemination method and task delivery system |
| CN109471647A (en) * | 2018-11-06 | 2019-03-15 | 北京字节跳动网络技术有限公司 | A kind of update method of data, device, electronic equipment and readable medium |
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| US20140173586A1 (en) * | 2012-12-14 | 2014-06-19 | Motorola Mobility Llc | Systems and Methods for Managing Updates To Applications |
| CN108958900A (en) * | 2017-05-18 | 2018-12-07 | 腾讯科技（深圳）有限公司 | A kind of task dissemination method and task delivery system |
| CN109471647A (en) * | 2018-11-06 | 2019-03-15 | 北京字节跳动网络技术有限公司 | A kind of update method of data, device, electronic equipment and readable medium |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111352833A (en) * | 2020-02-24 | 2020-06-30 | 北京百度网讯科技有限公司 | Recommendation system test method, device, equipment and computer storage medium |
| CN112286553A (en) * | 2020-10-27 | 2021-01-29 | 北京深思数盾科技股份有限公司 | User lock upgrading method, device, system, electronic equipment and storage medium |
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Application publication date: 20200117 Assignee: Nanjing Manyun Cold Chain Technology Co.,Ltd. Assignor: JIANGSU MANYUN SOFTWARE TECHNOLOGY Co.,Ltd. Contract record no.: X2023980038397 Denomination of invention: A method, device, storage medium, and electronic device for evaluating the effectiveness of updates Granted publication date: 20220823 License type: Common License Record date: 20230724 |