CN114782224A - Webpage evaluation cheating monitoring method and device based on user characteristics and electronic equipment - Google Patents
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Abstract
The application relates to the technical field of artificial intelligence, and particularly discloses a webpage evaluation cheating monitoring method and device based on user characteristics and an electronic device, wherein the method comprises the following steps: acquiring the rate of examination questions, the rate of answer questions and historical work information of an appraiser, wherein the rate of examination questions is used for identifying the average rate of reading the questions by the appraiser, and the rate of answer questions is used for identifying the average rate of the answers input by the appraiser; determining the difficulty level of the current examination questions according to the historical work information; determining a thinking time threshold of an appraiser according to the difficulty level; determining an examination question time threshold according to the question stem of the current examination question and the examination question rate of an examiner; determining an answer time threshold value according to the standard answers of the current examination questions and the answer rate of the examinee; summing the thinking time threshold, the examination question time threshold and the answer time threshold to obtain a monitoring time threshold of the current examination question; acquiring the actual time of the appraiser completing the current examination; and determining whether the appraiser has cheating behaviors or not according to the actual time and the monitoring time threshold.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a method and a device for monitoring webpage evaluation cheating based on user characteristics and electronic equipment.
Background
At present, the cost and the pressure of both appraisers can be greatly reduced through the online webpage appraising technology, and good experience is brought to both the appraisers. The existing online webpage evaluation system has certain cheating risks. In order to ensure the fairness of the appraisal, the behavior of the appraiser needs to be monitored to a certain extent during the examination. The current common method is to collect the answer duration of an appraiser in answering questions, and if the answer duration is greater than a threshold value, the applicant is considered to have the suspicion of cheating.
However, this method is difficult to set an accurate threshold value, and in addition, the operation habit of each person is different, and the operation time may be different, thereby resulting in a low accuracy of cheating monitoring.
Disclosure of Invention
In order to solve the above problems in the prior art, the embodiment of the application provides a method, a device and an electronic device for monitoring webpage evaluation cheating based on user characteristics, which can dynamically predict a corresponding answer duration threshold value in real time through the user characteristics of an evaluator and a currently answered question, and then set different time thresholds for different evaluators and different questions, so as to improve the accuracy of webpage cheating monitoring.
In a first aspect, an embodiment of the present application provides a method for monitoring web page appraisal cheating based on user characteristics, where the method includes:
acquiring an examination rate, an answer rate and historical work information of an appraiser, wherein the examination rate is used for identifying the average rate of reading questions of the appraiser, and the answer rate is used for identifying the average rate of inputting answers by the appraiser;
determining the difficulty level of the current examination question according to the historical work information;
determining a thinking time threshold of an appraiser according to the difficulty level;
determining an examination question time threshold according to the question stem of the current examination question and the examination question rate of an examiner;
determining an answer time threshold value according to the standard answers of the current examination questions and the answer rate of the examinee;
summing the thinking time threshold, the examination time threshold and the answer time threshold to obtain a monitoring time threshold of the current examination question;
acquiring the actual time of the appraiser for completing the current examination questions;
and determining whether cheating behaviors exist in the appraisers according to the actual time and the monitoring time threshold.
In a second aspect, an embodiment of the present application provides a web page appraisal cheating monitoring device based on user characteristics, including:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring the examination rate, the answer rate and the historical work information of an appraiser, the examination rate is used for identifying the average rate of reading questions of the appraiser, and the answer rate is used for identifying the average rate of inputting answers by the appraiser;
the analysis module is used for determining the difficulty level of the current examination question according to the historical working information, determining the thinking time threshold of the appraiser according to the difficulty level, determining the examination question time threshold according to the question stem of the current examination question and the examination question rate of the appraiser, determining the answer time threshold according to the standard answer of the current examination question and the answer rate of the appraiser, and summing the thinking time threshold, the examination question time threshold and the answer time threshold to obtain the monitoring time threshold of the current examination question;
and the monitoring module is used for acquiring the actual time of the appraiser for finishing the current examination questions and determining whether the cheating behavior exists in the appraiser according to the actual time and the monitoring time threshold.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor coupled to the memory, the memory for storing a computer program, the processor for executing the computer program stored in the memory to cause the electronic device to perform the method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, the computer program causing a computer to perform the method according to the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program, the computer operable to cause the computer to perform a method according to the first aspect.
The implementation of the embodiment of the application has the following beneficial effects:
in the embodiment of the application, the difficulty level of the currently answered examination questions for the appraiser is determined by acquiring the historical work information of the appraiser. And then determining the thinking time threshold of the appraiser for the current examination question based on the difficulty level. Then, acquiring an examination question rate for identifying the average rate of question reading of the examinee and an answer rate for identifying the average rate of answer input by the examinee, determining an examination question time threshold and an answer time threshold of the examinee by combining the question stem and the standard answer of the current examination question, and taking the sum of the thinking time threshold, the examination question time threshold and the answer time threshold as a monitoring time threshold for the examinee to answer the current examination question. And finally, acquiring the actual time of the appraiser for finishing the current examination questions, and determining whether the appraiser has cheating behaviors according to the actual time and the monitoring time threshold. Therefore, the corresponding answer time length threshold value is dynamically predicted in real time through the user characteristics of the appraisers and the current answer questions, different time threshold values are formulated according to different appraisers and different examination questions, and the accuracy of webpage cheating monitoring is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic diagram of a hardware structure of a web page evaluation cheating monitoring device based on user characteristics according to an embodiment of the present application;
fig. 2 is a system framework diagram of a web page evaluation cheating monitoring method based on user characteristics according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a method for monitoring web page appraisal cheating based on user characteristics according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating a method for determining difficulty level of a current question according to historical work information according to an embodiment of the present application;
fig. 5 is a schematic diagram illustrating that information extraction is performed on historical work information according to at least one preset keyword to obtain at least one piece of target information according to an embodiment of the present application;
fig. 6 is a schematic diagram illustrating a first similarity between the work area information and the evaluation area information according to an embodiment of the present application;
fig. 7 is a schematic diagram of matching in a preset standard thought time base according to difficulty levels to obtain a standard thought time threshold according to an embodiment of the present application;
fig. 8 is a block diagram illustrating functional modules of a device for monitoring web page appraisal cheating based on user characteristics according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making creative efforts shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
First, referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a web page evaluation cheating monitoring device based on user characteristics according to an embodiment of the present application. The web page appraisal cheating monitoring device 100 based on the user characteristics comprises at least one processor 101, a communication line 102, a memory 103 and at least one communication interface 104.
In this embodiment, the processor 101 may be a general-purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more ics for controlling the execution of programs according to the present disclosure.
The communication link 102, which may include a path, carries information between the aforementioned components.
The communication interface 104 may be any transceiver or other device (e.g., an antenna, etc.) for communicating with other devices or communication networks, such as an ethernet, RAN, Wireless Local Area Network (WLAN), etc.
The memory 103 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In this embodiment, the memory 103 may be independent and connected to the processor 101 through the communication line 102. The memory 103 may also be integrated with the processor 101. The memory 103 provided in the embodiments of the present application may generally have a nonvolatile property. The memory 103 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 101 to execute. The processor 101 is configured to execute computer-executable instructions stored in the memory 103, thereby implementing the methods provided in the embodiments of the present application described below.
In alternative embodiments, computer-executable instructions may also be referred to as application code, which is not specifically limited in this application.
In alternative embodiments, processor 101 may include one or more CPUs, such as CPU0 and CPU1 of FIG. 1.
In an alternative embodiment, the web page appraisal cheating monitoring device 100 based on user characteristics may include a plurality of processors, such as the processor 101 and the processor 107 in fig. 1. Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and/or processing cores that process data (e.g., computer program instructions).
In an optional embodiment, if the web page evaluation cheating monitoring device 100 based on the user characteristics is a server, for example, the server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like. The web page appraisal cheating monitoring apparatus 100 based on the user characteristics may further include an output device 105 and an input device 106. The output device 105 is in communication with the processor 101 and may display information in a variety of ways. For example, the output device 105 may be a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display device, a Cathode Ray Tube (CRT) display device, a projector (projector), or the like. The input device 106 is in communication with the processor 101 and may receive user input in a variety of ways. For example, the input device 106 may be a mouse, a keyboard, a touch screen device, or a sensing device, among others.
The web page appraisal cheating monitoring device 100 based on the user characteristics may be a general-purpose device or a special-purpose device. The embodiment of the present application does not limit the type of the web page evaluation cheating monitoring device 100 based on the user characteristics.
Secondly, it should be noted that the webpage evaluation cheating monitoring method based on the user characteristics provided by the application can be suitable for various job title evaluation scenes such as pet doctors and teachers. In this embodiment, a web page evaluation cheating monitoring method based on user characteristics provided by the present application will be described with reference to a web page evaluation cheating monitoring scenario based on user characteristics of a pet physician as an example, and the web page evaluation cheating monitoring method based on user characteristics in other scenarios is similar to the web page evaluation cheating monitoring method based on user characteristics of the pet physician in the web page evaluation cheating monitoring scenario based on user characteristics, and will not be described herein again.
Finally, fig. 2 is a system framework diagram of a web page appraisal cheating monitoring method based on user characteristics in a web page appraisal cheating monitoring scene based on user characteristics of a pet physician according to an embodiment of the present application. Specifically, the system may include: the system comprises a web page evaluation device 201 and a cheating monitoring device 202, wherein the web page evaluation device 201 can be a smart Phone (such as an Android Mobile Phone, an iOS Mobile Phone, a Windows Phone Mobile Phone, and the like), a tablet personal computer, a palm computer, a notebook computer, a Mobile Internet device MID (Mobile Internet Devices, Mobile Internet Devices for short: MID) and the like, and is used for displaying evaluation test questions, receiving answers input by a pet physician according to the displayed evaluation test questions, and counting the time for the pet physician to answer each evaluation test question. The cheating monitoring device 202 may be a server, and is configured to receive time taken by the pet physician to answer each examination question sent by the web page evaluation device 201, and then determine whether the cheating behavior exists in the pet physician.
In this embodiment, the web page evaluation device 201 may display a plurality of test questions to the pet physician before the formal evaluation, where the test questions may be some shallow questions, and have a certain length of question stem and a certain length of answer text. Thus, the rate of examination and the rate of response of the pet physician for evaluation may be determined from these test questions and sent to the cheat-monitoring device 202. The cheating monitoring device 202 may then determine, based on the identity information of the evaluated pet physician, for example: the name, the identification number, the evaluation title and the like, and historical work information of the pet physician is inquired, then the work field, the work deviation and the work content of the evaluated pet physician are determined according to the historical work information, and then the difficulty level of the examination questions evaluated by the evaluated pet physician is judged. Based on this, the historical work information may be the work log of the appraised pet physician within approximately 6 months to ensure timeliness of the reason information. Then, the cheating monitoring device 202 may determine a threshold value of the thinking time of the pet physician to be examined according to the difficulty level of each test question; determining an examination time threshold according to the question stem of each examination question and the examination rate of the pet physician to be examined; and determining a question answering time threshold according to the standard answers of each test question and the question answering rate of the pet physician to be examined. And then, summing the thinking time threshold, the examination time threshold and the answer time threshold to obtain the monitoring time threshold of the current examination question. Finally, the actual time of the pet physician completing the currently displayed test question sent by the web page evaluation device 201 is received, and then whether the cheating behavior exists in the pet physician is determined according to the actual time and the monitoring time threshold of the currently displayed test question.
In the embodiment, the corresponding answer time length threshold value is dynamically predicted in real time through the user characteristics of the appraisers and the current answers, then different time threshold values are formulated according to different appraisers and different answers, the accuracy of webpage cheating monitoring is improved, and the fairness of the examination is ensured.
The web page evaluation cheating monitoring method based on the user characteristics disclosed by the application is explained by taking a web page evaluation cheating monitoring scene based on the user characteristics of a pet doctor as an example:
referring to fig. 3, fig. 3 is a schematic flowchart of a web page review cheating monitoring method based on user characteristics according to an embodiment of the present application. The webpage evaluation cheating monitoring method based on the user characteristics comprises the following steps:
301: and acquiring the examination rate, the answer rate and the historical work information of the appraiser.
In this embodiment, the review rate is used to identify the average rate at which the appraisers read the questions, and the answer rate is used to identify the average rate at which the appraisers input the answers. Specifically, before formal evaluation, a plurality of test questions can be sequentially displayed to an appraiser, and the test questions are low in difficulty and have question stem texts and answer texts with certain lengths. Therefore, the time for the appraiser to finish each test question can be obtained, and meanwhile, the question answering time and the question answering time for the appraiser to answer each test question can be obtained by recording the time for the appraiser to perform input operation in each test question. Then, the question stem length and the answer length of each test question are combined to obtain a first question examination rate and a first question answer rate when the appraiser answers each test question. And finally, taking the average value of the first examination question rates corresponding to all the test questions as the examination question rate of the appraiser, and taking the average value of the first answer rates corresponding to all the test questions as the answer rate of the appraiser.
Meanwhile, in the present embodiment, the identity information submitted by the appraiser at the time of requesting the appraisal, for example: the name, the identification card number, the appraisal job title and the like, and the historical work information of the user is inquired. The historical work information may be information in which the daily work condition of the person to be evaluated is recorded, such as: company situation, job title, daily work, etc. In addition, in order to ensure the timeliness of the historical working information, the working log of the appraiser in the last 6 months can be selected as the historical working information.
302: and determining the difficulty level of the current examination questions according to the historical work information.
In the embodiment, the work field, work bias and work content of the examinee can be determined by the historical work information, and then the knowledge and operation which are good at the examinee and the mastery degree of the knowledge and operation can be predicted. Then, the difficulty level of the examination question for the appraiser is determined by combining the content of the examination of the current examination question and the depth of the examination.
Based on this, in the present embodiment, a method for determining the difficulty level of a current question according to historical work information is provided, as shown in fig. 4, the method includes:
401: and extracting information from the historical working information according to at least one preset keyword to obtain at least one target information.
In this embodiment, the at least one target information is in one-to-one correspondence with at least one keyword, which is set based on data required for subsequent analysis of knowledge and operation that the appraiser is skilled in. Specifically, as shown in fig. 5, at least one target information may be obtained by performing matching search on the historical work information of the person to be evaluated through each keyword in the at least one keyword. For example: the method comprises the steps of performing word embedding processing on each keyword to obtain a corresponding word vector, performing sliding retrieval on the word vector in the vector of each text in historical working information to determine whether each text contains the corresponding keyword, and extracting the text containing the corresponding keyword to serve as target information corresponding to the keyword.
402: and determining the work field information, the work deviation information and the work log information of the appraisers according to the at least one piece of target information.
In the embodiment, each target information with less calcium can be extracted by a feature vector and a semantic vector, and then the work field, work bias and actual work content of the appraiser can be determined according to the extracted feature vector and semantic vector.
403: and acquiring evaluation field information, evaluation deviation information and evaluation content information of the current evaluation.
In this embodiment, the method for acquiring the evaluation field information, the evaluation bias information, and the evaluation content information of the current examination question is similar to the method for acquiring the work field information, the work bias information, and the work log information of the examiner in step 402, and is not described herein again.
404: a first similarity between the work area information and the evaluation area information is calculated.
In this embodiment, the first similarity between the work area information and the evaluation area information may be determined by calculating a similarity between the feature vector of the work area information and the feature vector of the evaluation area information. Specifically, as shown in fig. 6, an angle cosine value between the feature vector of the work area information and the feature vector of the evaluation area information may be calculated by dot product, and the angle cosine value is used as a similarity between the feature vector of the work area information and the feature vector of the evaluation area information.
In the present embodiment, the cosine value of the included angle is used as the similarity between the feature vector of the work area information and the feature vector of the evaluation area information, and the range of the cosine value is [ -1, 1], so that the cosine value still has the properties of being 1 when the cosine value is the same, 0 when the cosine value is orthogonal, and-1 when the cosine value is opposite in the case of high dimension. That is, the closer the cosine value is to 1, the closer the direction between the two vectors is, the higher the similarity is; the closer they approach-1, the more opposite their direction, the lower the similarity; close to 0 indicates that the two features are nearly orthogonal, which may reflect a relative difference in the orientation of the two features. Therefore, the cosine value is used as the similarity between the characteristic vector of the work field information and the characteristic vector of the evaluation field information, and the similarity between the characteristic vector of the work field information and the characteristic vector of the evaluation field information can be accurately represented.
405: a second similarity between the work bias information and the evaluation bias information is calculated.
In this embodiment, the method for calculating the second similarity between the work deviation information and the evaluation deviation information is similar to the method for calculating the first similarity between the work area information and the evaluation area information in step 404, and is not described herein again.
406: and determining a first grade score according to the work log information and the evaluation content information.
In the present embodiment, the first ranking score is used to identify the mastery degree of the evaluation content corresponding to the evaluation content information by the evaluation person. In other words, the first rating score of the current examination question is used as an example, and the first rating score is the understanding degree or the application degree of the examiner to the content examined by the current examination question.
Illustratively, the first level score may be represented by a level difference between a standard difficulty level corresponding to the current question and a standard difficulty level corresponding to the actual level of the appraiser. The standard difficulty level is a dividing mode for dividing all knowledge according to difficulty, and the standard difficulty level corresponding to the actual level of the appraiser can be confirmed by the standard difficulty level corresponding to the actual knowledge mastered by the appraiser.
Specifically, first, a work level and a level of the appraiser may be determined from the work log information, wherein the work level is used to identify a standard difficulty level of daily work of the appraiser, and the level is used to identify a degree of mastery of the daily work by the appraiser. And then, determining the examination question grade and the depth grade of the current examination question according to the examination content information, wherein the examination question grade is used for identifying the standard difficulty grade of the current examination question, and the depth grade is used for identifying the depth degree of the current examination question. And finally, determining the first grade score according to the working grade, the level grade, the examination question grade and the depth grade. Illustratively, the first-level score may be represented by formula (r):
P1＝k1×Q1-k2×Q2.........①
where P1 represents the first ranking score, k1 represents the depth ranking, Q1 represents the question ranking, k2 represents the horizontal ranking, and Q2 represents the job ranking.
407: adjusting the first grade score according to the first similarity and the second similarity to obtain a second grade score;
in the present embodiment, the first similarity is used to identify the familiarity of the appraiser with the application field of the knowledge under consideration, and the second similarity is used to identify the familiarity of the appraiser with the application bias of the knowledge under consideration. The smaller these two similarities, the lower the familiarity of the appraiser with the content being examined by the current question, the higher the corresponding difficulty relative to the more familiar person to the field being examined by the current question. Therefore, in determining the difficulty level of the current question relative to the appraiser, the familiarity of the appraiser with the field in which the question is being examined also needs to be considered. Therefore, in the embodiment, the first grade score needs to be adjusted according to the first similarity and the second similarity to obtain the second grade score, so that the difficulty is more accurately determined.
Specifically, the second level score may be represented by the formula (ii):
where P1 represents the first-level score, P2 represents the second-level score, f1 represents the first similarity, and f2 represents the human similarity.
408: and determining the difficulty level of the current examination question according to the second grade score.
In this embodiment, the value range corresponding to the second level score may be partitioned to correspond to different difficulty levels, for example: [0-0.05) for level 0, [0.05-0.2) for level 1, [0.2-0.5) for level 3, [0.5-0.8) for level 4, [0.8-1] for level 5. Therefore, according to the section where the second grade score falls, the difficulty grade corresponding to the section can be used as the difficulty grade of the current examination question for the person to be evaluated.
303: and determining the thinking time threshold of the appraiser according to the difficulty level.
In this embodiment, the standard thinking time base can be matched in a preset standard thinking time base according to the difficulty level to obtain a standard thinking time threshold, wherein the standard thinking time base is used for recording the average thinking time of the appraiser when facing the examination questions with different difficulty levels in the working field. And then, acquiring historical evaluation information of the appraisers, and determining answer habit information of the appraisers according to the historical evaluation information. And finally, determining a thinking time threshold according to the answer habit information, the first similarity and the second similarity.
Illustratively, as shown in fig. 7, the average thinking time of the persons with the same level in the standard thinking time base in answering the questions with the same difficulty level can be queried as the standard thinking time threshold by evaluating the level of the person and the difficulty level of the current question. However, the average thinking time recorded by the standard thinking time base is based on the examinees and questions in the same field, the average thinking time required by the examinees and the questions in the same field is used for answering, and the influence of different fields on the thinking time is not considered. Therefore, the standard thinking time threshold needs to be adjusted by the first similarity and the second similarity reflecting the familiarity of the appraiser with the application field of the knowledge considered by the current question and the familiarity biased by the application of the knowledge considered by the appraiser to the current question, so as to obtain a more accurate time threshold as the candidate thinking time threshold.
Meanwhile, after the examination, the examinee has time limitation and cannot think without limit. Therefore, in this embodiment, in the present embodiment, the answer habit information of the appraiser is determined by the historical appraisal information of the appraiser, and then the maximum thinking time threshold of the appraiser is determined by combining the historical answer sheet of the appraiser. I.e. once the thought exceeds this time threshold, the appraiser is most likely to give up answering the question.
Based on this, in the present embodiment, the maximum thought time threshold of the examinee and the candidate thought time threshold can be compared to determine the thought time threshold of the current question. Specifically, when the maximum thought time threshold is less than or equal to the candidate thought time threshold, the maximum thought time threshold is taken as the thought time threshold; and when the maximum thinking time threshold is larger than the candidate thinking time threshold, taking the candidate thinking time threshold as the thinking time threshold.
304: and determining an examination question time threshold according to the question stem of the current examination question and the examination question rate of the examiner.
In the present embodiment, the quotient of the length of the question stem and the question rate of the examiner may be used as the question time threshold.
305: and determining the answer time threshold value according to the standard answer of the current examination question and the answer rate of the examinee.
In this embodiment, the quotient of the length of the standard answer and the answer rate of the appraiser may be used as the threshold of the answer time.
306: and summing the thinking time threshold, the examination time threshold and the answer time threshold to obtain the monitoring time threshold of the current examination question.
In this embodiment, the error coefficients of the thinking time threshold, the examination time threshold and the answer time threshold can be obtained respectively, and then the monitoring time threshold is obtained by a weighted summation method. Wherein, the error coefficient can be obtained by analyzing the historical evaluation data.
307: and acquiring the actual time of the appraiser for finishing the current examination questions.
In the embodiment, the retention time of the appraiser on the interface of the current appraisal can be counted by displaying one test question each time, and then the actual time for the appraiser to finish the current appraisal is obtained.
308: and determining whether cheating behaviors exist in the appraisers according to the actual time and the monitoring time threshold.
In the present embodiment, when the actual time exceeds the monitoring time threshold, the appraiser is considered to be suspected of cheating, and the appraisal by the appraiser is stopped. Further, in order to prevent a delay problem caused by a certain misoperation, in the cheating monitoring process, the detected times with cheating suspicion (that is, the actual time exceeds the monitoring time threshold) can be accumulated, and when the accumulated number is larger than a preset threshold, the appraiser is finally considered to have cheating behaviors, and the appraisal of the appraiser is stopped.
In summary, in the web page evaluation cheating monitoring method based on the user characteristics provided by the invention, the difficulty level of the currently answered examination questions to the appraiser is determined by acquiring the historical work information of the appraiser. And then determining the thinking time threshold of the appraiser for the current examination question based on the difficulty level. Then, acquiring an examination question rate for identifying the average rate of question reading of the examinee and an answer rate for identifying the average rate of answer input by the examinee, determining an examination question time threshold and an answer time threshold of the examinee by combining the question stem and the standard answer of the current examination question, and taking the sum of the thinking time threshold, the examination question time threshold and the answer time threshold as a monitoring time threshold for the examinee to answer the current examination question. And finally, acquiring the actual time of the appraiser for finishing the current examination questions, and determining whether the appraiser has cheating behaviors according to the actual time and the monitoring time threshold. Therefore, the corresponding answer duration threshold value is dynamically predicted in real time through the user characteristics of the appraisers and the current answers, different time threshold values are formulated according to different appraisers and different answers, and the accuracy of webpage cheating monitoring is improved.
Referring to fig. 8, fig. 8 is a block diagram illustrating functional modules of a web page review cheating monitoring device based on user characteristics according to an embodiment of the present application. As shown in fig. 8, the apparatus 800 for monitoring web page appraisal cheating based on user characteristics includes:
the obtaining module 801 is configured to obtain an examination question rate, an answer rate and historical work information of an examination and evaluation person, where the examination question rate is used to identify an average rate at which the examination and evaluation person reads questions, and the answer rate is used to identify an average rate at which the examination and evaluation person inputs answers;
the analysis module 802 is configured to determine a difficulty level of a current test according to historical work information, determine a thinking time threshold of an appraiser according to the difficulty level, determine an examination time threshold according to a stem of the current test and an examination rate of the appraiser, determine an answer time threshold according to a standard answer of the current test and the answer rate of the appraiser, and sum the thinking time threshold, the examination time threshold and the answer time threshold to obtain a monitoring time threshold of the current test;
and the monitoring module 803 is used for acquiring the actual time of the appraiser completing the current examination questions, and determining whether the cheating behavior exists in the appraiser according to the actual time and the monitoring time threshold.
In an embodiment of the present invention, in determining the difficulty level of the current examination question according to the historical work information, the analysis module 802 is specifically configured to:
extracting information of the historical working information according to at least one preset keyword to obtain at least one piece of target information, wherein the at least one piece of target information corresponds to the at least one keyword one to one;
determining work field information, work deviation information and work log information of an appraiser according to at least one piece of target information;
acquiring evaluation field information, evaluation deviation information and evaluation content information of the current evaluation;
calculating a first similarity between the work field information and the evaluation field information;
calculating a second similarity between the work deviation information and the evaluation deviation information;
determining a first grade score according to the work log information and the evaluation content information, wherein the first grade score is used for identifying the mastery degree of an evaluator on the evaluation content corresponding to the evaluation content information;
adjusting the first grade score according to the first similarity and the second similarity to obtain a second grade score;
and determining the difficulty level of the current examination question according to the second grade score.
In an embodiment of the present invention, in determining the first rating score according to the work content information and the evaluation content information, the analysis module 802 is specifically configured to:
determining the work level and the level of the appraiser according to the work log information, wherein the work level is used for identifying the standard difficulty level of the daily work of the appraiser, and the level is used for identifying the mastery degree of the daily work of the appraiser;
determining the examination question grade and the depth grade of the current examination question according to the examination content information, wherein the examination question grade is used for identifying the standard difficulty grade of the current examination question, and the depth grade is used for identifying the depth degree of the current examination question;
and determining a first grade score according to the work grade, the level grade, the examination question grade and the depth grade.
In an embodiment of the present invention, the first grade score may be expressed by formula (c):
P1＝k1×Q1-k2×Q2.........③
wherein, P1Indicates a first rating score, k1Indicating the shade level, Q1Representing examination level, k2Indicating a horizontal grade, Q2Indicating the level of operation.
In an embodiment of the present invention, the second level score may be represented by the formula (iv):
wherein, P1Represents a first rating score, P2Represents a second rating score, f1Denotes a first degree of similarity, f2Representing human similarity.
In an embodiment of the present invention, in determining the thinking time threshold of the appraiser according to the difficulty level, the analysis module 802 is specifically configured to:
matching in a preset standard thinking time base according to the difficulty level to obtain a standard thinking time threshold, wherein the standard thinking time base is used for recording the average thinking time of an appraiser facing examination questions with different difficulty levels in the working field;
acquiring historical evaluation information of an evaluator;
determining answer habit information of an appraiser according to the historical appraisal information;
and determining a thinking time threshold according to the answering habit information, the first similarity and the second similarity.
In the embodiment of the present invention, in terms of determining the thinking time threshold according to the answering habit information, the first similarity and the second similarity, the analysis module 802 is specifically configured to:
determining the maximum thinking time threshold of the appraiser according to the answer habit information;
adjusting the standard thinking time threshold according to the first similarity and the second similarity to obtain a candidate thinking time threshold;
when the maximum thinking time threshold is smaller than or equal to the candidate thinking time threshold, taking the maximum thinking time threshold as the thinking time threshold;
and when the maximum thinking time threshold is larger than the candidate thinking time threshold, taking the candidate thinking time threshold as the thinking time threshold.
Referring to fig. 9, fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 9, the electronic device 900 includes a transceiver 901, a processor 902, and a memory 903. Connected to each other by a bus 904. The memory 903 is used to store computer programs and data, and may transfer the data stored by the memory 903 to the processor 902.
The processor 902 is configured to read the computer program in the memory 903 to perform the following operations:
acquiring the rate of examination questions, the rate of answer questions and historical work information of an appraiser, wherein the rate of examination questions is used for identifying the average rate of reading the questions by the appraiser, and the rate of answer questions is used for identifying the average rate of inputting answers by the appraiser;
determining the difficulty level of the current examination questions according to the historical work information;
determining a thinking time threshold of an appraiser according to the difficulty level;
determining an examination question time threshold according to the question stem of the current examination question and the examination question rate of an examiner;
determining an answer time threshold value according to the standard answers of the current examination questions and the answer rate of the examinee;
summing the thinking time threshold, the examination time threshold and the answer time threshold to obtain a monitoring time threshold of the current examination question;
acquiring the actual time of the appraiser completing the current examination;
and determining whether the appraiser has cheating behaviors or not according to the actual time and the monitoring time threshold.
In an embodiment of the present invention, in determining the difficulty level of the current examination from the historical working information, the processor 902 is specifically configured to:
extracting information of the historical working information according to at least one preset keyword to obtain at least one piece of target information, wherein the at least one piece of target information corresponds to the at least one keyword one to one;
determining work field information, work deviation information and work log information of an appraiser according to at least one piece of target information;
acquiring evaluation field information, evaluation deviation information and evaluation content information of a current evaluation question;
calculating a first similarity between the work field information and the evaluation field information;
calculating a second similarity between the work deviation information and the evaluation deviation information;
determining a first grade score according to the work log information and the evaluation content information, wherein the first grade score is used for identifying the mastery degree of an evaluation person on the evaluation content corresponding to the evaluation content information;
adjusting the first grade score according to the first similarity and the second similarity to obtain a second grade score;
and determining the difficulty level of the current examination question according to the second grade score.
In an embodiment of the present invention, in determining the first rating score according to the work content information and the evaluation content information, the processor 902 is specifically configured to:
determining the work level and the level of the appraiser according to the work log information, wherein the work level is used for identifying the standard difficulty level of the daily work of the appraiser, and the level is used for identifying the mastering degree of the appraiser on the daily work;
determining examination question grades and depth grades of current examination questions according to the examination content information, wherein the examination question grades are used for identifying standard difficulty degree grades of the current examination questions, and the depth grades are used for identifying the depth degrees of the current examination questions;
and determining a first grade score according to the work grade, the level grade, the examination question grade and the depth grade.
In an embodiment of the present invention, the first ranking score may be expressed by the formula (v):
P1＝k1×Q1-k2×Q2.........⑤
wherein, P1Indicates a first rating score, k1Indicating the shade level, Q1Representing examination level, k2Indicating a horizontal grade, Q2Indicating the level of operation.
In an embodiment of the present invention, the second ranking score may be represented by the formula (i):
wherein, P1Represents a first rating score, P2Representing a second grade score, f1Denotes a first degree of similarity, f2Representing human similarity.
In an embodiment of the present invention, in determining the thinking time threshold of the appraiser according to the difficulty level, the processor 902 is specifically configured to perform the following operations:
matching in a preset standard thinking time base according to the difficulty level to obtain a standard thinking time threshold, wherein the standard thinking time base is used for recording the average thinking time of an appraiser facing examination questions with different difficulty levels in the working field;
acquiring historical evaluation information of an evaluator;
determining answer habit information of an appraiser according to the historical appraisal information;
and determining a thinking time threshold according to the answering habit information, the first similarity and the second similarity.
In the embodiment of the present invention, in determining the threshold of thinking time according to the answer habit information, the first similarity and the second similarity, the processor 902 is specifically configured to perform the following operations:
determining the maximum thinking time threshold of the appraiser according to the answer habit information;
adjusting the standard thinking time threshold according to the first similarity and the second similarity to obtain a candidate thinking time threshold;
when the maximum thinking time threshold is smaller than or equal to the candidate thinking time threshold, taking the maximum thinking time threshold as the thinking time threshold;
and when the maximum thinking time threshold is larger than the candidate thinking time threshold, taking the candidate thinking time threshold as the thinking time threshold.
It should be understood that the web page evaluation cheating monitoring device based on user characteristics in the present application may include a smart Phone (e.g., an Android Phone, an iOS Phone, a Windows Phone, etc.), a tablet computer, a palm computer, a notebook computer, a Mobile Internet device MID (Mobile Internet Devices, abbreviated as MID), a robot, or a wearable device, etc. The web page evaluation cheating monitoring device based on the user characteristics is only an example, but not an exhaustive list, and includes but is not limited to the web page evaluation cheating monitoring device based on the user characteristics. In practical applications, the web page evaluation cheating monitoring device based on the user characteristics may further include: intelligent vehicle-mounted terminals, computer equipment and the like.
Through the above description of the embodiments, those skilled in the art will clearly understand that the present invention can be implemented by combining software and a hardware platform. With this understanding in mind, all or part of the technical solutions of the present invention that contribute to the background can be embodied in the form of a software product, which can be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods according to the embodiments or some parts of the embodiments.
Accordingly, the present application also provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement part or all of the steps of any one of the methods for monitoring web page appraisal cheating based on user characteristics as described in the above method embodiments. For example, the storage medium may include a hard disk, a floppy disk, an optical disk, a magnetic tape, a magnetic disk, a flash memory, and the like.
Embodiments of the present application further provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any one of the user characteristic-based web page appraisal cheating monitoring methods as described in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are all alternative embodiments and that the acts and modules referred to are not necessarily required by the application.
In the above embodiments, the description of each embodiment has its own emphasis, and for parts not described in detail in a certain embodiment, reference may be made to the description of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is merely a logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.
The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application, in essence or part of the technical solutions contributing to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk, and various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, and the memory may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the methods and their core ideas of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A webpage evaluation cheating monitoring method based on user characteristics is characterized by comprising the following steps:
acquiring the examination rate, the answer rate and the historical work information of an appraiser, wherein the examination rate is used for identifying the average rate of reading questions of the appraiser, and the answer rate is used for identifying the average rate of inputting answers by the appraiser;
determining the difficulty level of the current examination question according to the historical work information;
determining a thinking time threshold of the appraiser according to the difficulty level;
determining an examination question time threshold according to the question stem of the current examination question and the examination question rate of the examiner;
determining a question answering time threshold according to the standard answer of the current question and the question answering rate of the appraiser;
summing the thinking time threshold, the examination question time threshold and the answer time threshold to obtain a monitoring time threshold of the current examination question;
acquiring the actual time of the appraiser for finishing the current examination question;
and determining whether the appraisers cheat or not according to the actual time and the monitoring time threshold.
2. The method of claim 1, wherein determining the difficulty level of the current examination from the historical work information comprises:
extracting information of the historical working information according to at least one preset keyword to obtain at least one piece of target information, wherein the at least one piece of target information corresponds to the at least one keyword one to one;
determining the work field information, the work deviation information and the work log information of the appraiser according to the at least one piece of target information;
acquiring evaluation field information, evaluation deviation information and evaluation content information of the current examination question;
calculating a first similarity between the work field information and the evaluation field information;
calculating a second similarity between the work deviation information and the evaluation deviation information;
determining a first grade score according to the work log information and the evaluation content information, wherein the first grade score is used for identifying the mastery degree of the evaluation person on the evaluation content corresponding to the evaluation content information;
adjusting the first grade score according to the first similarity and the second similarity to obtain a second grade score;
and determining the difficulty level of the current examination question according to the second grade score.
3. The method of claim 2, wherein determining a first ranking score based on the job content information and the appraisal content information comprises:
determining the work level and the level of the appraiser according to the work log information, wherein the work level is used for identifying the standard difficulty level of the daily work of the appraiser, and the level is used for identifying the mastering degree of the daily work of the appraiser;
determining examination question grades and depth grades of the current examination questions according to the examination content information, wherein the examination question grades are used for identifying standard difficulty degree grades of the current examination questions, and the depth grades are used for identifying the depth degrees of the current examination questions;
and determining the first grade score according to the work grade, the level grade, the examination question grade and the depth grade.
4. The method of claim 3, wherein the first ranking score satisfies the following equation:
P1＝k1×Q1-k2×Q2
wherein, P1Represents the first rating score, k1Represents the depth level, Q1Representing the examination question level, k2Represents the level, Q2The operation level is represented.
5. The method of claim 2, wherein the second level score satisfies the following equation:
wherein, P1Represents the first rating score, P2Representing the second rating score, f1Representing said first degree of similarity, f2Representing the human similarity.
6. The method of claim 2, wherein said determining a time threshold for thinking by said candidate based on said difficulty rating comprises:
matching in a preset standard thinking time base according to the difficulty level to obtain a standard thinking time threshold, wherein the standard thinking time base is used for recording the average thinking time of an appraiser facing examination questions with different difficulty levels in the working field;
acquiring historical evaluation information of the evaluation person;
determining answer habit information of the appraisers according to the historical appraisal information;
and determining the thinking time threshold according to the answering habit information, the first similarity and the second similarity.
7. The method according to claim 6, wherein said determining the thinking time threshold according to the answer habit information, the first similarity and the second similarity comprises:
determining the maximum thinking time threshold of the appraiser according to the answer habit information;
adjusting the standard thinking time threshold according to the first similarity and the second similarity to obtain a candidate thinking time threshold;
when the maximum thought time threshold is less than or equal to the candidate thought time threshold, taking the maximum thought time threshold as the thought time threshold;
when the maximum thought time threshold is greater than the candidate thought time threshold, taking the candidate thought time threshold as the thought time threshold.
8. A web page evaluation cheating monitoring device based on user characteristics is characterized in that the device comprises:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring the examination rate, the answer rate and the historical work information of an appraiser, the examination rate is used for identifying the average rate of reading questions of the appraiser, and the answer rate is used for identifying the average rate of inputting answers by the appraiser;
the analysis module is used for determining the difficulty level of the current examination question according to the historical work information, determining the thinking time threshold of the appraiser according to the difficulty level, determining the examination question time threshold according to the question stem of the current examination question and the examination question rate of the appraiser, determining the answer time threshold according to the standard answer of the current examination question and the answer rate of the appraiser, and summing the thinking time threshold, the examination question time threshold and the answer time threshold to obtain the monitoring time threshold of the current examination question;
and the monitoring module is used for acquiring the actual time of the appraiser for finishing the current examination question and determining whether the cheating behavior exists in the appraiser according to the actual time and the monitoring time threshold.
9. An electronic device comprising a processor, memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, the one or more programs including instructions for performing the steps in the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which is executed by a processor to implement the method according to any one of claims 1-7.
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