CN110874313B - Writing tool testing method and device - Google Patents
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- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
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Abstract
The application discloses a testing method and device of an intelligent writing tool, and relates to the field of intelligent writing. The specific implementation scheme is as follows: testing an interface of the writing tool to obtain a first test result; when the first test result is that the interface can work normally under a set load, article data generated by the writing tool aiming at input data are obtained; and testing the first correlation between the article data and the input data and the smoothness of the article data to obtain a second test result. According to the embodiment of the application, the intelligent writing tool can be tested comprehensively and accurately.
Description
Technical Field
The application relates to the field of computers, in particular to the field of intelligent writing.
Background
Intelligent authoring refers to a computer acquiring data from various fields on the internet and generating Articles (AGC) using algorithms. With the vast information of the internet today, some traditional media workers are somewhat frustrating in facing the large number of events that occur each day. While algorithmic generation articles may help them share heavy work tasks. Intelligent authoring has attracted attention from many internet companies and scholars as a currently popular field. Intelligent authoring robots have been able to generate tens of thousands of articles per day for human reading.
With the increase of the application amount of intelligent writing, a new demand is correspondingly generated, namely, the readability of the intelligent writing articles is improved. Because intelligent writing is used for generating articles through a machine, compared with manual writing, the problems that the contents of many articles are irrelevant to topics, the sentences of the articles are not smooth and the like can occur. Therefore, a method for testing the intelligent writing tool needs to be proposed to ensure the quality of the intelligent writing article.
Disclosure of Invention
In order to solve at least one of the above technical problems, an embodiment of the present application provides a method and an apparatus for testing a writing tool.
In a first aspect, an embodiment of the present application provides a method for testing a writing tool, including:
testing an interface of the writing tool to obtain a first test result;
when the first test result is that the interface can work normally under a set load, article data generated by the writing tool aiming at input data are obtained;
and testing the first correlation between the article data and the input data and the smoothness of the article data to obtain a second test result.
In the embodiment of the application, the functions and the performances of the intelligent writing tool and the produced articles are tested, so that a user of the intelligent writing tool can know the normal or abnormal conditions of the intelligent writing tool, and the effect of the articles produced by the intelligent writing tool can be improved under the condition that the user of the intelligent writing tool does not consume huge manpower.
In one embodiment, testing the interface of the authoring tool comprises:
and sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meet set conditions or not.
In the embodiment of the application, the interface request data is sent to the interface of the writing tool, whether the function of the interface is normal is judged according to the received feedback data, the interface of the intelligent writing tool can be tested in combination with the intelligent writing process, and the intelligent writing interface is ensured to work normally in the initial stage of the intelligent writing process.
In one embodiment, testing the interface of the authoring tool comprises:
testing the maximum load of the interface; the maximum load is greater than the set load.
In the embodiment of the application, the maximum load of the interface is tested, so that a user of the writing tool can know the pressure condition born by the interface, and the interface is prevented from being overloaded by adopting certain measures, or errors in the produced articles are prevented by adopting modes such as manual inspection and the like when the interface is overloaded.
In one embodiment, testing the article data for a first relevance to the input data includes:
testing a second correlation between the summary of the article data and the summary of the reference article data of the input data;
and obtaining the first correlation according to the second correlation.
In the embodiment of the application, the correlation between the article data produced by the writing tool and the given subject can be tested, and the readability of the produced data under the condition that the interface works normally is ensured.
In one embodiment, testing the article data for compliance includes:
for each sentence in the article data, calculating the probability that the occurrence of the nth word is related to the n-1 words in front of the nth word; n is the number of words in each sentence;
judging the relevance of the article data and the input data according to the probability;
and calculating the smoothness according to the relevance, the number of times of reference article data, the number of times of the article data and the weight corresponding to n.
Because the machine performs intelligent writing, the machine can be filled according to a template with a preset format, and the situation that sentences are not smooth is easy to occur. According to the embodiment of the application, the smoothness of the article data is tested, and the readability of the article data produced by the intelligent writing interface can be ensured.
In a second aspect, an embodiment of the present application provides a test device for a writing tool, including:
a first test module: the interface is used for testing the writing tool to obtain a first test result;
article output acquisition module: when the first test result is that the interface can work normally under a set load, article data generated by the writing tool for input data are obtained;
and a second test module: and the method is used for testing the first correlation between the article data and the input data and the smoothness of the article data, and obtaining a second test result.
In one embodiment, the first test module includes:
interface test unit: and the interface request data is used for sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meets the set conditions or not.
In one embodiment, the first test module includes:
load test unit: for testing a maximum load of the interface; the maximum load is greater than the set load.
In one embodiment, the second test module includes:
correlation test unit: for testing a second correlation between the summary of the article data and the summary of the reference article data of the input data;
correlation calculation unit: for obtaining the first correlation from the second correlation.
In one embodiment, the second test module includes:
probability calculation unit: for calculating, for each sentence in the article data, a probability that the occurrence of the nth word is related to the n-1 word preceding it; n is the number of words in each sentence;
correlation calculation unit: the article data input method comprises the steps of judging the relevance of article data and input data according to the probability;
and a smoothness calculation unit: and the method is used for calculating the smoothness according to the relevance, the number of times of reference article data, the number of times of the article data and the weight corresponding to n.
One embodiment of the above application has the following advantages or benefits: through testing the interface of the intelligent writing tool and the article data produced by the intelligent writing tool, a comprehensive and accurate test result can be provided, so that a user can know the normal or abnormal condition of the intelligent writing tool, and the user can produce articles with readability by using the intelligent writing tool. Because the interface of the intelligent writing tool and the produced article data are tested, the technical problem that the intelligent writing tool needs to be tested to improve the article output quality is solved, and the technical effects of being beneficial to the use and improvement of the intelligent writing tool are achieved.
Other effects of the above alternative will be described below in connection with specific embodiments.
Drawings
The drawings are for better understanding of the present solution and do not constitute a limitation of the present application. Wherein:
FIG. 1 is a flow chart of a method for testing a authoring tool in accordance with a first embodiment of the present application;
FIG. 2 is a flow chart of a method of testing a authoring tool in accordance with a second embodiment of the present application;
FIG. 3 is a flow chart of a method for testing a authoring tool in accordance with a third embodiment of the present application;
FIG. 4 is a flow chart of a method for testing a authoring tool in accordance with a fourth embodiment of the present application;
FIG. 5 is a schematic diagram of a writing tool testing device according to a fifth embodiment of the present application;
FIG. 6 is a schematic diagram of a writing tool testing device according to a sixth embodiment of the present application;
FIG. 7 is a schematic diagram of a writing tool testing device according to a seventh embodiment of the present application;
FIG. 8 is a schematic diagram of a writing tool testing device according to an eighth embodiment of the present application;
FIG. 9 is a schematic diagram of a writing tool testing device according to a ninth embodiment of the present application;
FIG. 10 is a block diagram of an electronic device for implementing the authoring tool testing method of an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic flow chart of a writing tool testing method provided in an embodiment of the present application, and as shown in fig. 1, the writing tool testing method provided in the embodiment of the present application includes:
step S11: and testing an interface of the writing tool to obtain a first test result.
Step S12: and when the first test result is that the interface can work normally under the set load, acquiring article data generated by the writing tool aiming at the input data.
Step S13: and testing the first correlation of the article data and the input data and the universality of the article data to obtain a second test result.
The final purpose of intelligent writing is to produce an article which can be read smoothly by readers and accords with logic. The writing tool testing method provided by the application example taking the purpose as a starting point can ensure the quality of data provided by each module in the process of generating the article and the quality of the finally produced article. In the embodiment of the application, the functions and the performances of the interface of the intelligent writing tool and the produced articles are tested, so that a user of the intelligent writing tool can know the normal or abnormal conditions of the intelligent writing tool, and the effect of the articles produced by the intelligent writing tool can be improved under the condition that the user of the intelligent writing tool does not consume huge manpower.
In the embodiment of the present application, the interface of the test writing tool may be whether the test interface can return normal data under the specified condition.
In the embodiment of the application, the interface can work normally under the set load, and the interface can operate under the set load without breakdown. The interface can work normally under the set load, or the interface can produce normal data under the normal load.
In this embodiment of the present application, the first correlation between the article data and the input data may be the first correlation between the produced article data and the input data, or the first correlation between the produced article data and the reference article corresponding to the input data.
In one embodiment, an interface for a test authoring tool comprises:
and sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meet set conditions or not.
In the embodiment of the application, the interface request data is sent to the interface of the writing tool, whether the function of the interface is normal is judged according to the received feedback data, the interface of the intelligent writing tool can be tested in combination with the intelligent writing process, and the intelligent writing interface is ensured to work normally in the initial stage of the intelligent writing process.
Generally, a smart authoring process can be summarized as establishing topics, material selection, title generation, paragraph production, and template filling. Establishing the theme may be performed by manual operations and the remaining steps may be performed by the intelligent authoring tool. If the interface of the intelligent writing tool has a problem and cannot work normally, the data fed back in the material selection stage has a problem. By the method provided by the embodiment of the application, the test can be started from all stages of the whole intelligent writing, and the intelligent writing tool at each stage can be ensured to normally operate.
In the embodiment of the application, the request data may be request data for interface call or request data for material selection, etc.
In the embodiment of the application, the article data may be an article generated by an interface, or an article template, or an article material, or an article sentence, etc.
In one embodiment, an interface for a test authoring tool comprises:
testing the maximum load of the interface; the maximum load is greater than the set load.
In the embodiment of the application, the maximum load of the interface is tested, so that a user of the writing tool can know the pressure condition born by the interface, and the interface is prevented from being overloaded by adopting certain measures, or errors in the produced articles are prevented by adopting modes such as manual inspection and the like when the interface is overloaded.
In one embodiment, as shown in fig. 2, testing a first relevance of article data to input data includes:
step S21: a second correlation between the summary of the test article data and the summary of the reference article data of the input data.
Step S22: from the second correlation, a first correlation is obtained.
In the embodiment of the application, the correlation between the article data produced by the writing tool and the given subject can be tested, and the readability of the produced data under the condition that the interface works normally is ensured.
In the embodiment of the application, the reference article data of the input data may be a reference article related to the input data or a summary of the reference article related to the input data.
In one embodiment, as shown in fig. 3, testing the generality of article data, includes:
step S31: for each sentence in the article data, calculating the probability that the n-th word appears in relation to the n-1 word in front of the n-th word; n is the number of words in each sentence.
Step S32: and judging the relevance of the article data and the input data according to the probability.
Step S33: and calculating the smoothness according to the relevance, the number of times of reference article data, the number of times of article data and the weight corresponding to n.
Because the machine performs intelligent writing, the machine can be filled according to a template with a preset format, and the situation that sentences are not smooth is easy to occur. According to the embodiment of the application, the smoothness of the article data is tested, and the readability of the article data produced by the intelligent writing interface can be ensured.
In one example of the present application, the authoring tool testing method includes the steps as shown in FIG. 4:
step S41: interface testing, i.e., functional testing. Test cases, i.e., input data, such as a written subject, etc., are prepared for interface testing. Under the condition that the test case is normal or abnormal, testing whether each interface can realize the function in the requirement, and returning corresponding auxiliary writing data such as materials and the like. Methods of directly requesting an interface are generally used with tools such as Postman.
Step S42: pressure testing, i.e., performance testing. The pressure test mainly aims at an auxiliary writing class interface, and a JMeter tool is used, wherein the JMeter is a Java-based pressure test tool developed by Apache organization. For stress testing of software, it was originally designed for Web application testing, but later extends to other testing areas. When the intelligent writing tool is used for writing, if the data request amount is too large, the interface load can be caused, and the produced data is abnormal. Through stress testing, each interface, such as a correlation analysis interface, a theme article generation interface, and the like, is tested for load capacity and maximum service performance. Thereby determining the ability to provide data over a period of time. Therefore, when the intelligent writing tool is used, the intelligent writing tool can be correctly used according to writing requirements.
The article data anomaly test may include step S43 and step S44. Step S43: article data correlation test. After establishing the authoring subject, the intelligent authoring tool prepares material data in the domain to which the subject belongs. How these data are evaluated and cleaned will directly affect the relevance of the title to the subsequent paragraph generation. So for data extracted from the knowledge base by the authoring-assisted interface, the Bleu algorithm can be used to determine its relevance to the topic, or an LDA (Latent Dirichlet Allocation, document topic generation model) topic model can be used to determine how close the topic distribution of the reference article data is to the topic distribution of the generated article data. Bleu is a text evaluation algorithm based on n-grams, which is commonly used in machine translation, and can also be used to determine the similarity between generated text data and a given topic. After judging the correlation between the generated article data and the subject, the generated article data and the reference article data can be subjected to secondary correlation judgment, and whether the generated article data and the reference article data belong to the same subject or not is judged by using LDA subject clustering, so that the correlation between the generated article data and the reference article data is verified. Furthermore, in embodiments of the present application, the relevance test may also include a sensitive word test such as a yellow-reversed word.
Step S44: content compliance testing of article data. For articles that the smart authoring tool has generated, they are evaluated using the ROUGE (Recall-Oriented Understudy for Gisting Evaluation, recall-oriented replacement gist evaluation) method. The ROUGE method uses original data (such as original text of extracted data) corresponding to input data as reference article data, tests co-occurrence information of N-gram and recall rate of N-gram in the reference article data and generated article data, and judges whether the generated article data is close to the original reference article data or not and judges whether the content is smooth or not. In this example, the reference article is an article related to the input data. For example, if the input data is object a, the reference article is an article related to object a, and the reference article is an article with readability. In general, the higher the proximity of the generated article data to the original reference article data, the higher the smoothness. In a specific operation, it is necessary to divide the reference article data and the generated article data according to sentence granularity, then divide chinese characters by space, and convert single characters into Unicode characters. The scores are calculated by adopting N-gram and ROUGE, the value of N in the N-gram can be 1 and 2, and the ROUGE can specifically adopt ROUGE-L (L means the longest public subsequence). After the test, the scores of ROUGE-1, ROUGE-2 and ROUGE-L can be obtained, and the higher the score is, the more smooth the sentence is represented. In addition, the compliance test may also include miscord checks, etc. in embodiments of the present application.
The embodiment of the application provides a writing tool testing device, and the structure of the writing tool testing device is shown in fig. 5 and comprises:
the first test module 51: and the interface is used for testing the writing tool to obtain a first test result.
Article output acquisition module 52: and acquiring article data generated by the writing tool for the input data when the first test result is that the interface can work normally under the set load.
The second test module 53: the method is used for testing the first correlation of the article data and the input data and the universality of the article data and obtaining a second test result.
In one embodiment, as shown in fig. 6, the first test module 51 includes:
interface test unit 61: and the interface request data is used for sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meets the set conditions or not.
In one embodiment, as shown in fig. 7, the first test module 51 includes:
load test unit 71: a maximum load for the test interface; the maximum load is greater than the set load.
In one embodiment, as shown in fig. 8, the second test module 53 includes:
correlation test unit 81: for testing a second correlation between the summary of the article data and the summary of the reference article data of the input data;
correlation calculation unit 82: for obtaining a first correlation from the second correlation.
In one embodiment, as shown in fig. 9, the second test module 53 includes:
probability calculation unit 91: for calculating, for each sentence in the article data, a probability that the occurrence of the nth word is related to the n-1 word preceding it; n is the number of words in each sentence;
correlation calculation unit 92: the method comprises the steps of judging the relevance of article data and input data according to probability;
the smoothness calculation unit 93: the method is used for calculating the universality according to the relevance, the number of times of reference article data, the number of times of article data and the weight corresponding to n.
According to embodiments of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 10, a block diagram of an electronic device according to a writing tool testing method according to an embodiment of the present application is shown. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the application described and/or claimed herein.
As shown in fig. 10, the electronic device includes: one or more processors 1001, memory 1002, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the electronic device, including instructions stored in or on memory to display graphical information of a graphical user interface (Graphical User Interface, GUI) on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple electronic devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 1001 is illustrated in fig. 10.
Memory 1002 is a non-transitory computer-readable storage medium provided herein. The memory stores instructions executable by the at least one processor to cause the at least one processor to perform the authoring tool testing method provided herein. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the authoring tool testing method provided by the present application.
The memory 1002 is used as a non-transitory computer readable storage medium for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the first test module 51, the article output acquisition module 52, and the second test module 53 shown in fig. 5) corresponding to the authoring tool testing method in the embodiment of the present application. The processor 1001 executes various functional applications of the server and data processing by executing non-transitory software programs, instructions, and modules stored in the memory 1002, that is, implements the authoring tool testing method in the above-described method embodiment.
Memory 1002 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created from the use of the authoring tool to test the electronic device, etc. In addition, the memory 1002 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1002 optionally includes memory remotely located with respect to the processor 1001, which may be connected to the authoring tool testing electronics over 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 electronic device of the writing tool testing method may further include: an input device 1003 and an output device 1004. The processor 1001, memory 1002, input device 1003, and output device 1004 may be connected by a bus or other means, for example by a bus connection in fig. 10.
The input device 1003 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the authoring tool test electronics, such as a touch screen, keypad, mouse, trackpad, touchpad, pointer stick, one or more mouse buttons, track ball, joystick, etc. input devices. The output means 1004 may include a display device, auxiliary lighting means (e.g., LEDs), tactile feedback means (e.g., vibration motors), and the like. The display device may include, but is not limited to, a liquid crystal display (Liquid Crystal Display, LCD), a light emitting diode (Light Emitting Diode, LED) display, and a plasma display. In some implementations, the display device may be a touch screen.
Various implementations of the systems and techniques described here can be implemented in digital electronic circuitry, integrated circuitry, application specific integrated circuits (Application Specific Integrated Circuits, ASIC), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
These computing programs (also referred to as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable logic devices (programmable logic device, PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., CRT (Cathode Ray Tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (Local Area Network, LAN), wide area network (Wide Area Network, WAN) and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. …
According to the technical scheme, the interface of the intelligent writing tool and the produced article are tested, so that a user of the intelligent writing tool can know the normal or abnormal working condition of the intelligent writing tool, and the effect of the article produced by the intelligent writing tool is improved under the condition that the user of the intelligent writing tool does not consume huge manpower. …
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions disclosed in the present application can be achieved, and are not limited herein.
The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.
Claims (12)
1. A method of writing tool testing, comprising:
testing an interface of the writing tool to obtain a first test result;
when the first test result is that the interface can work normally under a set load, article data generated by the writing tool aiming at input data are obtained;
testing the first correlation between the article data and the input data and the compliance of the article data to obtain a second test result;
wherein the article data includes at least one of: the interface generates the articles, article templates, article materials and article sentences.
2. The method of claim 1, wherein testing the interface of the authoring tool comprises:
and sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meet set conditions or not.
3. The method of claim 1, wherein testing the interface of the authoring tool comprises:
testing the maximum load of the interface; the maximum load is greater than the set load.
4. The method of claim 1, wherein testing the article data for a first relevance to the input data comprises:
testing a second correlation between the summary of the article data and the summary of the reference article data of the input data;
and obtaining the first correlation according to the second correlation.
5. The method of claim 1, wherein testing the article data for compliance comprises:
for each sentence in the article data, calculating the probability that the occurrence of the nth word is related to the n-1 words in front of the nth word; n is the number of words in each sentence;
judging the relevance of the article data and the input data according to the probability;
and calculating the smoothness according to the relevance, the number of times of reference article data, the number of times of the article data and the weight corresponding to n.
6. A test device for a writing instrument, comprising:
a first test module: the interface is used for testing the writing tool to obtain a first test result;
article output acquisition module: when the first test result is that the interface can work normally under a set load, article data generated by the writing tool for input data are obtained;
and a second test module: the method comprises the steps of testing first correlation between article data and input data and compliance of the article data to obtain a second test result;
wherein the article data includes at least one of: the interface generates the articles, article templates, article materials and article sentences.
7. The apparatus of claim 6, wherein the first test module comprises:
interface test unit: and the interface request data is used for sending interface request data to an interface of the writing tool, and judging whether feedback data of the received interface request data meets the set conditions or not.
8. The apparatus of claim 6, wherein the first test module comprises:
load test unit: for testing a maximum load of the interface; the maximum load is greater than the set load.
9. The apparatus of claim 6, wherein the second test module comprises:
correlation test unit: for testing a second correlation between the summary of the article data and the summary of the reference article data of the input data;
correlation calculation unit: for obtaining the first correlation from the second correlation.
10. The apparatus of claim 6, wherein the second test module comprises:
probability calculation unit: for calculating, for each sentence in the article data, a probability that the occurrence of the nth word is related to the n-1 word preceding it; n is the number of words in each sentence;
correlation calculation unit: the article data input method comprises the steps of judging the relevance of article data and input data according to the probability;
and a smoothness calculation unit: and the method is used for calculating the smoothness according to the relevance, the number of times of reference article data, the number of times of the article data and the weight corresponding to n.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-5.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0302071D0 (en) * | 2003-01-29 | 2003-02-26 | Introspective It Services Ltd | Data driven test automation with intelligent navigation |
| WO2019113977A1 (en) * | 2017-12-15 | 2019-06-20 | 腾讯科技（深圳）有限公司 | Method, device, and server for processing written articles, and storage medium |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US7088949B2 (en) * | 2002-06-24 | 2006-08-08 | Educational Testing Service | Automated essay scoring |
| US7835902B2 (en) * | 2004-10-20 | 2010-11-16 | Microsoft Corporation | Technique for document editorial quality assessment |
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| US11430171B2 (en) * | 2018-04-03 | 2022-08-30 | Sri International | Explainable artificial intelligence |
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| CN108920455A (en) * | 2018-06-13 | 2018-11-30 | 北京信息科技大学 | A kind of Chinese automatically generates the automatic evaluation method of text |
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| CN109408829B (en) * | 2018-11-09 | 2022-06-24 | 北京百度网讯科技有限公司 | Method, device, equipment and medium for determining readability of article |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0302071D0 (en) * | 2003-01-29 | 2003-02-26 | Introspective It Services Ltd | Data driven test automation with intelligent navigation |
| WO2019113977A1 (en) * | 2017-12-15 | 2019-06-20 | 腾讯科技（深圳）有限公司 | Method, device, and server for processing written articles, and storage medium |
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