KR20160135451A - System of fixing department and method thereof - Google Patents

Abstract

The present invention relates to a system and a method for normalizing a database, which has been tested on graduate students majoring in respective departments, to regenerate standard databases for respective departments according to properties of majoring students in the respective departments, comparing the standard database with test results of middle and high school students, and providing a comparison result to a mobile terminal. The department group selection system according to the present invention is characterized in comprising: a content management module which collects and manages promotion content related to schools and departments; a mobile communication module which is connected with a department selection module and transmits at least one among department selection result information, promotion content, and an additional service related to the department to an external mobile terminal; and the mobile terminal which acknowledges the department selection result information and the additional service related to the department transmitted from the mobile communication module, and executes the additional service related to the department. According to the present invention, subjects having the same department group selection result information can create a cluster meeting.

Description

[0001] The present invention relates to a system and a method for selecting a department,

The present invention relates to a system and a method for selecting a department, and more specifically, a database that has been tested on the basis of graduate students majoring in each department is regenerated to regenerate a standard database for each department according to the characteristics of each department To a system and method for comparing and analyzing such a standard database with test results of middle and high school students and providing the resulting information to a mobile terminal.

Because modern society is a society where the schooling is important, the parents' education heat is excessive, and this over - education reality is causing the side effect of promoting many regional disparities and universalism.

Therefore, the Ministry of Education is planning to announce and implement measures to cope with the situation in a timely manner. However, it is the prevailing mood of the general society atmosphere that the present educational heat and the priority atmosphere of the school will continue to be maintained. The present and future middle and high school students are placed in the reality that they should select the expected college according to their teaching ability or ability, and in addition, the department which is the first step to decide the career of their life, The decision is the most important thing.

If you do not consider a department that does not fit your own characteristics, or if you decide to give priority to a university decision by compromising your will or your ability, it will be a real one. In this case, It can lead to side effects that have significant adverse effects. Therefore, in order to overcome these problems, various institutions and companies are currently developing and implementing a testing system to determine anticipated courses and series for middle and high school students. The question itself is neither abstract nor concrete, For example, if you prefer to answer the question "Good subject in Korean language", you are being tested offline or online through too general and fragmented questions such as Korean literature and anticipation, and the results tend to be different for each different institution. This results in a confusion between students and parents.

This is because secondary and tertiary students do not yet have experience in college and society, so it is difficult to be sure that their choice is the right course for the test questions conducted by various organizations, and how their interests and abilities are utilized after graduation This is a difficult reality because the existing test evaluation system only draws results for simple questions without taking this reality into consideration.

To solve this same problem, Korean Patent No. 10-334138 entitled "Career Diagnosis System" refers to a means of databaseing 120 types of occupational characteristics based on six types of theories of the RIASEC theory Means for searching the general environment, job preference, academic performance and the like to find an objective occupational environment and a subjective occupational characteristic of the pimple terminal by the database, and means for preparing the OMR card by the database of the occupational personality theory The score is ranked according to the score, and the score is ranked in descending order. In this way, a sub-code is derived according to the score order, and a score corresponding to the code of the 120 types of occupational personality types stored in the database To provide information so that you can choose the right job for your job And that it has the effect of solving the problem of the career more accurately and reliably.

According to the above system, it is possible to derive the same result as the expert's diagnosis based on the theory of the work personality. However, since the opinion of the student in the department is not reflected in reality, In addition to the fact that the questions and diagnosis are detailed, the overall evaluation process is based on a general logic of logic (logic) in which a score is given to a question and a simple calculation is made to derive the result. There is a disadvantage that it is difficult to obtain a particular difference from the existing system because it does not deviate greatly from the process or process.

Korean Registered Patent No. 10-334138B1, Apr. 12, 2002.

SUMMARY OF THE INVENTION The present invention has been made in order to solve the above problems, and it is an object of the present invention to provide a system and method for selecting a department and a method of the present invention, in which a graduate student and an expert, And the result information of the subject is processed through the combination of the result database and the result information of the subject, thereby providing a more realistic and reliable department and selection result, and providing the result information of the subject and the service information of the department to the mobile terminal.

Another goal is to enable cluster gathering among subjects with information on the results of the same department selection.

The present invention selects a department including a course preference database, a department suitability database, a job preference database, a series preference database, a standard comparison database, a question evaluation module, a pair comparison module, a numerical comparison calculation module, a priority processing module, A content management unit for collecting and managing publicity contents related to the school and the department, and at least one or more of the department selection result information, the publicity content, and the department related additional service is transmitted to the external mobile terminal, A mobile communication module, a mobile terminal for confirming the department and selection result information transmitted from the mobile communication module and the department related supplementary service, and executing the supplementary service related to the department.

In addition, the present invention includes a step of databaseing a plurality of questionnaires for subject preference test, departmental fitness test, occupational environment preference test, and family preference test, and determining a predetermined numerical value according to an answer to each questionnaire; Generating a standard comparison database by normalizing numerical values obtained by executing a predetermined number of graduate students per each major; Performing a test on a subject to obtain a numerical value of each subject of the questionnaire; Comparing the numerical value of the subject and the numerical value of the graduate student, and deriving the final numerical value of the subject according to the type by the QFD (Quality Function Development) method through the predetermined weighting; Deriving the final numerical value of the subject by assigning predetermined weights to the numerical values obtained through the dual comparison of each question through the AHP (Analytic Hierarchy Process) method in the sequence preference test, and extracting a predetermined number of priority subjects; (A) using a mobile communication module, at least one of the department selection result information, the publicity contents, and the department related supplementary services, including the step of summing and comparing the final figures and selecting the final department (B) confirming transmitted department and selection result information and department related supplementary services by using the mobile terminal, and executing the department related supplementary services by using the mobile terminal do.

As described above, the system and method for selecting a department according to the present invention can be realized by regenerating a normalized standard comparison database by firstly testing the graduate students and experts attending each department, It is possible to derive a more realistic and reliable department and selection result by providing the result information of the subject and the service information of the department additional service to the mobile terminal, thereby greatly improving the convenience of the user.

In addition, it is possible to make clusters among the subjects who have information on the results of the selection of the similar department, so that a large number of subjects can share various department series information.

1 is a block diagram showing a schematic configuration of a department selection system according to the present invention;
FIG. 2 is a flowchart showing a schematic procedure of a method of selecting a department in accordance with the present invention; FIG.
3 is a block diagram showing a schematic configuration of four kinds of inspection databases according to the present invention;
FIG. 4 is a diagram illustrating a process of subject preference checking through a subject preference database in a questionnaire evaluation module according to the present invention; FIG.
FIG. 5 is a diagram illustrating an example of priorities of a subject preference test through a subject preference database in a priority processing module according to the present invention; FIG.
FIG. 6 is a diagram illustrating a process of a sequence preference check through a sequence preference database in a pair comparison module according to the present invention; FIG.
FIG. 7 is an explanatory diagram showing a description of priorities and consistency of a subject preference test through a subject preference database according to the present invention; FIG.
FIG. 8 is an exemplary diagram illustrating a prioritized department of the departmental fitness test through a departmental fitness database in the priority processing module according to the present invention; FIG.
9 is a diagram illustrating an example of a prioritized department of the occupational environment preference test through the occupational environment preference database in the priority processing module according to the present invention.
FIG. 10 is an exemplary diagram showing a final priority course of examination of four types of databases in the department selection module according to the present invention; FIG.
11 is a diagram illustrating an explanation display state of a final priority department derived from a department selection module according to the present invention;
12 is a configuration diagram showing a detailed configuration of a virtual competitive rate estimation module according to the present invention;
13 is a configuration diagram showing a detailed configuration of a mobile terminal according to the present invention;
14 is a configuration diagram showing a detailed configuration of a cluster meeting unit according to the present invention;
15 is a flow chart illustrating a schematic operation flow according to the use of a mobile terminal according to the present invention.
16 is a flowchart showing an operation flow of a cluster meeting unit according to the present invention;

Hereinafter, a system and method for selecting a department based on the present invention will be described in detail.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

In the course selection system according to the present invention, each category is classified by a method of grouping the selected questions according to experiential or well-known educational theories into course preference, department degree of association, occupational environment preference, and family preference, do.

Among the four databases (110, 120, 130, 140) that gathered these questions, the databases (110, 120, and 130) about subject preferences, departmental associations, and occupational environment preferences can be used to derive numerical values for each questionnaire after the subject has been tested. The

Specifically, the 7-point scale, ie not at all (1), very (almost) not (2), slightly (slightly) not (3), average (4), slightly (5) , Very (almost) yes (6 points), and totally yes (7 points). Of course, the idea according to the present invention can be various other numerical values in such a manner that weighting can be given regardless of the 7-point scale, or grades can be given differentiated scores.

Sequence preference will be described later, but the sequence characteristic can be derived by an analytic hierarchy process (AHP) rather than the numerical derivation method.

Three databases (110, 120, and 130) among the databases, which are the basis for deriving the numerical values, are obtained by first deriving the numerical values according to the respective questions for a graduate student having a corresponding major in the population

Next, when ranking is performed, the degree of conformity of each major according to each question is derived. Normalization of such degree of conformity is performed to generate the standard comparison database 160.

Thereafter, the examinee examines the questions stored in the three types of databases 110, 120, and 130, derives the preference for each question as a numerical value, compares the preference with each of the standard comparison databases 160 generated for each department, The results of the questionnaire are as follows.

The specific configuration and method of the department selection system according to the present invention based on these basic characteristics will be described as follows.

FIG. 1 is a block diagram schematically showing the overall configuration of a department selection system according to the present invention, and FIG. 2 is a flowchart illustrating a general procedure of a department selection method according to the present invention.

1, the system according to the present invention includes a subject preference database 110, a subject relevance database 120, a job preference database 130, a sequence preference database 140, Based on the subject preference database 110, the subject suitability database 120 and the occupational environment preference database 130 among the subjects 110, 120, 130 and 140, a questionnaire is conducted based on the actual subject / department's population, specifically, A tester database 150 for calculating numerical values, a standard comparison database 160 for extracting realistic and trustworthy information through a normalization process through the tester database 150, a questionnaire survey database A questionnaire evaluation module 210 that conducts a questionnaire, A numerical comparison calculation module 220 for comparing the numerical value with a numerical value constituted by each department of the standard comparison database 160 and calculating a final regeneration final value specific to each question, A pair comparison module 230 for extracting a numerical value for obtaining subject preference and relative preference for each subject of each university based on the data obtained from each of the four databases 110, 120, 130, and 140, A priority processing module 240 for selecting five classes, for example, a predetermined number of classes in accordance with each test, a consistency checking module 260 for comparing the four tests to check whether the results are consistent, (110,120,130,140), the questionnaire was conducted to the expert group of each major field, and then the comparative data characterized by each field The shipment includes an expert group database 170, a department and series selection module 250 for comparing and analyzing the numerical values of the major departments derived according to the four databases 110, 120, 130, and 140 with the expert group database 170 and selecting the final department series consist of.

3 is a block diagram showing a schematic configuration of four kinds of databases according to the present invention.

First, the subject preference database 110 is for examining a subject's preference degree, and it is determined whether or not any subjects such as a middle school student (graduate student) or a current student (middle school student as a subject) , Which means that the contents of a good and favorite subject are very helpful, and a collection containing a questionnaire to perform a function to tell what a subject is.

The question configuration of the subject preference database 110 is as follows.

1) It is composed of all the subjects from the middle school to the whole school and the first grade of the high school (grade 10). 2) It includes the contents of the subjects of social studies, science inquiry in major subjects such as language, repair, 3) Inquiry area is based on major elective courses.

4) It contains contents that can measure the practical and practical students' preferences such as computer and artistic practical subjects, and 5) the contents of the subject by reference. (Grades) as well as their preferences for the students. The responses of individual students are measured by combining their preference and achievement.

The questionnaire composed of these bases is detailed in the following Tables 1 and 2.

The answers to the questionnaire are exemplified as physical grades (15 grades) to 7 grades, and the higher the score, the better the grades are.

Each of the above Tables 1 and 2 is illustrative and exemplary in nature, and addition, modification, and replacement are possible depending on the circumstances and the times.

The academic suitability database 120 according to the present invention is composed of a questionnaire for informing the students of the department and department that best match their own intellectual, social, and personal abilities necessary for studying at a university. have.

The questionnaire that constitutes the department and the fitness database 120 is divided into three sub-items. Specifically, the questionnaire consists of 1) basic literacy (judgment standard: ability required to perform department study), 2) learning environment Criteria: physical and emotional characteristics of the department), and 3) academic characteristics (criterion: the overall nature of the study in the department).

The questionnaire composed of these bases is shown in detail in the following Tables 3 to 5.

Each of the above Tables 3 to 5 is also illustrative, and it is to be understood that additions, modifications, and alterations may be made in accordance with the situations and ages.

The occupational environment fitness database 130 according to the present invention can be classified into a department that can study to obtain a job of a desired condition and a questionnaire to know what the family is, Respectively.

The questionnaire that constitutes the occupational environment fitness database 130 includes a list of all the occupational environments corresponding to the respective occupations, and then the occupational environment corresponding to the occupational environment fitness database 130 is classified according to the types MECE (Mutually Exclusive and Collectively Exhaustive: ). It is composed of the questionnaire made according to the principle. (Note: Ministry of Labor's Occupational Psychological Test, Korea Job Information System 2005 Future Job World)

The classification based on these grounds is shown in detail in Table 6 below.

[9], [3], and [a little] match [1] according to the degree of agreement of the environment for the above occupation types. The detailed questionnaire is as follows.

Each of the questionnaires in Table 7 is also illustrative and exemplary, and it should be understood that additions, modifications and replacements may be made in accordance with the situations and times.

The family preference database 140 according to the present invention is a collection of questionnaires that indicate the series that can be studied most preferably in consideration of contents and learning goals in each major of the university.

In other words, the vocabulary and questions are reconstructed so that it is easy for the adolescents to understand based on the academic goals and main contents of each college.

The tester database 150 according to the present invention includes three databases among the four databases 110, 120, 130 and 140 having the above-described questionnaire, namely, a subject preference database 110, a subject relevance database 120, The present invention relates to a database in which a questionnaire is conducted based on actual graduate students on the basis of the database 130, and sheets are processed by calculating numerical values for each question within each major category of each major.

The generation of the tester database 150 and the numerical processing method of the numerical comparison and comparison module 220 to be described later are performed by an advanced hydraulic technique called quality function development (QFD). A brief description of the quality function deployment method is a method designed to clearly define the customer's needs defined through the design / operation and the product design process supporting the production management system. Specific activities include technological conversion Product planning, product design, process characteristics, step and parameter definition, process control planning, process control, , And are mainly used to design information systems and organizational structures.

The tester database 150 can be derived by applying the quality functional development (QFD) method. Specifically, the tester database 150 can be obtained by firstly analyzing a student who is studying at a graduate school of major universities such as Seoul National University, Yonsei University, Inquiries about the questionnaires of the above three databases (110, 120, and 130) for each major and the department against about 400 or more.

The reason for choosing the sample group through the selection of such a population, especially the graduate students and above, is that the students' academic achievement is higher than that of the other universities, This is because it is not a realistic academic selection criterion because it is based on the theory and so on. Therefore, it is aimed to establish a standard that can be directly helpful to current and secondary students. Of course, the present invention is not limited to the above-described universities, but it is also desirable to expand the number of selected universities and further increase the number of students who respond to the questionnaires to make them more universal and reliable.

When the questionnaire is conducted through the graduate students of each major who become the sample group, the numerical value evaluated by each student in each questionnaire can be calculated as the 7-point scale mentioned above.

Specifically, in the course preference test through the course preference database 110, the preference degree and the non-preference degree are displayed based on the 7-point scale for each questionnaire, and the achievement level is expressed by the actual grade (grade 15) (Lower, lower, middle, middle, middle, upper, lower, and upper). The numerical values through the displayed preferences are compared with the responses of the graduate students in each major, and the most suitable departments and departments are derived.

In the department fitness test (120), the fit characteristics of each department are derived from the questionnaire which the graduate students of each department have given high scores, and the three sub areas of basic literacy, learning environment, and academic characteristics Specific characteristics are derived.

In the occupational environment test through the work environment preference database 130, a predetermined weight is given to the answer of the graduate student, and the resulting numerical value is derived.

In other words, the reactions of graduate students by each major can be summarized as follows: preference of subjects (high school subject preference database) required for studying in each department, existing literacy and intellectual ability (academic relevance database) necessary for studying, Preference (occupational environment database) is derived. When the derived numerical values are ranked according to each department, the degree of conformity of each major can be derived according to each question of subject preference, department suitability, and environmental preference, and the aggregate of data including the result of the four tests thus obtained, Is the database 150.

The standard comparison database 160 according to the present invention is used for securing the reliability of the tester database 150. The standard comparison database 160 according to the present invention is used to normalize the tester database 150, ), And finally the database is used. 'Normalization' can be interpreted in various ways in the IT field. However, the meaning of the normalization in the present invention is that, in order to reduce errors in the numerical value due to extreme answers, a series of calculations And a predetermined weight is given to prevent a difference from other majors due to the simple summation of the scores according to the answers. For example, the job environment preference checking database 130 may include a plurality of jobs, The score of the graduate student is calculated by multiplying the weighted value by the predetermined weight, and then the weight is given through a known method, for example, the AHP method, thereby reducing the error range with other majors, The way to calculate the unique ranking of job types by calculating the results .

The questionnaire evaluation module 210 according to the present invention may be configured such that the subject who is the actual middle and high school student who is the subject of the examination of the department is sequentially and in accordance with the program set on the online web site etc. supported by the system according to the present invention, It performs the function of checking the whole questionnaire by scoring. The questionnaire evaluation module 210 may be applied to both the department selection tests according to the four databases or may be divided into a pair comparison module 230 for testing the series preference database 140 to be specialized.

The questionnaire evaluation function according to the questionnaire evaluation module 210 provides a basis for the subject to derive his / her own preference as a numerical value.

The numerical comparison calculation module 220 according to the present invention compares numerical values derived by the subjects responding to each questionnaire and numerical values of graduate students constituted by respective departments of the standard comparison database 160, And regenerates the numerical value. Specifically, the comparative processing method for regenerating the numerical value having the characteristic of the subject is a process of multiplying the numerical value of the subject and the numerical value of the graduate student in the standard comparison database 160 for the corresponding questionnaire, and additionally, And so on.

To illustrate the process of multiplying the numerical value of the graduate student in the standard comparison database 160 with the numerical value of the subject, "Korean language course is helpful in studying my major." The response of the Korean language students to the question "The answer is totally the same" was answered by the Korean language students. The response of the students of the electronic engineering students was 2 points ("Almost not") and the test subjects' If the answer is 5, the student's score for the Korean language course is 5 * 7 = 35, and the score for the degree of conformity for the department of electronics is 5 * 2 = 10. And the student's response (the numerical value derived from the answer), the compliance of the whole department with each question is derived / displayed as the final numerical value of the subject.

The reason for calculating the new regeneration value by multiplying the figure derived by the graduate student and the figure derived by the subject without directly using the figure derived by the subject is that when the figure of the subject is subtly varied according to each subject, Since it is difficult to select priorities or there may be an error in the process of selecting the actual department, it is necessary to multiply the numerical values of these initial subjects by the graduate students again so that the error range of the final numerical value In order to obtain a more accurate preference as well as a reduction.

In addition, the Department of Fit Assessment can provide supplementary explanations for questionnaires with low numerical values, ie, supplemental explanations provide more detailed comprehension of the subject, The background and requirements for the two surveys are compared to the two highest-scoring graduate students who have the highest scores in the sub-categories such as basic literacy, learning environment, and academic characteristics. To give supplementary explanations. These supplementary explanations may be included in the final selection results.

In addition, in the occupational environment preference test, it is also possible to derive numerical values using the DHP (Delphic Hierarchy Process) method, which can reflect the objective aspects and the opinions of the experts in order to prioritize the numerical values of the subjects and the graduate students over AHP Do. In addition, in the occupational environment preference test, weights are given to the values checked by the subjects, and the values obtained by multiplying the values by the numerical values and the weights are summed and then normalized to provide a basis for calculating the rank of the job type It is possible.

Until now, the module configuration and processing method for the selection of the subjects of the QFD applicants has been described. In contrast, the sequence preference test according to the sequence preference database 140 is performed through an analytic hierarchy process (AHP) And a system according to the present invention provides a pair comparison module 230 for this process.

The paired comparison module 230 according to the present invention supports the construction of a time series of exposure of each question, such as a questionnaire evaluation module, in which a specific exposure And to provide the subjects with the ability to derive the relative preferences of each college and university major goal.

The hierarchical analysis method (AHP) is a method of capturing the knowledge, experience, and intuition of the evaluator through a pair comparison between the elements constituting the hierarchical structure of the decision making. It lists all the elements constituting the faced decision problem In this paper, we propose a new method for estimating the weight of elements in a hierarchical structure, and then compare the elements of the hierarchy with each other one by one. The result of the comparison is obtained by using the vector method of linear algebra. When we multiply the weights of the elements by the upper layer and the lower layer, the final weight of the decision solution is obtained and a series of decisions are made in the conclusion.

The paired comparison module 230 according to the present invention collects the answers to the questionnaire to the subject in such a hierarchical analysis method (AHP), for example, The next step is to estimate the relative preference through the derived values, and specifically to measure how much each college is preferred or not according to the high and low values according to each figure. For example, on the left side of the questionnaire window, the question "I like to watch soccer games" is displayed, and on the right side, "I like to watch basketball games" When you want to quantify this, "1 - the left side is very good, 2 - the left side is generally good, 3 - the left side is slightly better, 4 - similar, 5- the right side is slightly better, , The right side is very good, and the right side is very good. "Thus, the subject is allowed to select one of the answers.

The priority processing module 240 selects a predetermined number of classes, for example, five classes, each of which has the highest score for each test, based on the values obtained according to the functions of the respective modules based on the four different databases. Is accomplished by the function of.

In other words, the priority processing module 240 according to the present invention divides numerical values of the examinations obtained according to each of the four databases 110, 120, 130 and 140 into sheets for each department, And then sorting the sheet-processed data from the highest ranking to the lowest ranking by each department, thereby providing a function of extracting the highest number of the highest number of data, that is, extracting five departments in order of higher numbers .

The priority processing module 240 analyzes the results of each examination based on the four databases and displays the graphs and the description of each test on each of the upper classes (the most suitable class for the subject) and the lower classes (the most inappropriate class for the subject ) And the ability to present specific explanations.

Here, the system according to the present invention additionally provides a consistency check module 260. The consistency check module 260 determines whether or not the consistency check module 260 is in the high and low range of the error range, It provides a function that can check whether there is consistency by dividing into five levels from A grade to E grade.

In other words, for example, if the Department of Korean Language and Literature leads to the Department of Priority, and if the Department of Physics is selected as a priority department, it is predicted that the student does not respond to each question in a satisfactory manner. In this paper, we propose a method to detect the difference between two sequences. First, we examine whether the differences are different. If the different sequences are derived for each result, (For example, in the Department of Korean Language and Literature, etc.), it is judged that the degree of error is insignificant, so that information such as major subjects or characteristics of each department is exposed in detail, This information will help you to understand your own If you do not, you will be able to give advice.

Finally, the department selection module 250 compares the values derived from the four databases 110, 120, 130 and 140 according to the present invention, evaluates the relative importance according to the four types of tests, applies the predetermined weight The resultant result is taken as the final numerical value, and finally the function and the department of the subject are selected.

In order to apply the weights, the department selection module 250 first performs a comparison operation with the answer values of each questionnaire through the expert group database 170. The expert group database 170 is formed of a pool of talented persons or experts of each major by each major, and a questionnaire is surveyed to each of the four databases 110, 120, 130 and 140 to obtain answers Which is the normalized data. That is, it can be understood that it is an extension of the standard comparison database 160 obtained for the graduate students of each major described above.

The department selection module 250 compares the numerical values of the four different types of tests with those of the expert group database 170 and normalizes them. For example, Compared to the results of the three tests, the result of unreliable numerical values is corrected, and the sum of the numerical values is averaged.

For the final department selection, the department selection module (250) can also provide a supplementary explanation for each department priority, which can be processed in a graph or a graph and displayed for easy viewing by the subject.

The department selection system according to the present invention includes a contents management module 270, a virtual competition rate estimation module 280, a mobile communication module 290 and a mobile terminal 300 as shown in FIG. 1, (300), not only can the department selection result information be confirmed, but also various additional services can be executed.

The contents management module 270 collects and manages publicity contents related to the school and department, collects and stores school publicity contents and department publicity contents from each university, and periodically updates collected publicity contents of the school and contents of the department .

In addition, the stored department and publicity contents can be retrieved on the basis of the set specific region, and can be provided to the subject through the mobile terminal 300. [

The virtual competition rate estimation module 280 is connected to the class selection module 250 to estimate an expected competition rate of a priority class of the department selection result and the virtual competition rate estimation module 280 according to the present invention 12 includes a department inquiry unit 281, a virtual competitive rate calculating unit 282, a peripheral area calculating unit 283, and a grade-by-grade calculating unit 284, as shown in FIG.

The department inquiry unit 281 inquires the subject selected by the subject according to the subject selection result information, and the virtual competition rate calculation unit 282 calculates the virtual competition rate based on the region selected by the subject, And calculate the virtual competition rate according to the expected number of students entering the school.

The virtual competition rate according to the present invention is information that can be used as interesting information to check how much a department and aptitude are.

The peripheral area calculating unit 283 calculates and provides the virtual competitive rate of the surrounding area in addition to the area set by the subject, and the grade-specific calculating unit 284 calculates and provides the virtual competitive rate of the subjects selected for the same subject for each grade level .

The mobile communication module 290 is connected to the department selection module 250 and transmits at least one of the department selection result information, publicity contents, and department related additional services to the mobile terminal 300.

The mobile terminal 300 confirms the department and selection result information and the department-related supplementary service transmitted from the mobile communication module 290, executes the department-related supplementary service, and the mobile terminal 300 according to the present invention The mobile terminal includes a mobile display unit 310, a site connection unit 320, a cluster meeting unit 330, and a virtual competitive rate inquiry unit 340, as shown in FIG.

The mobile display unit 310 displays the department selection result information of the subject and displays the departmental advertisement related contents of the school corresponding to the department selection result information within the local radius set on the basis of the current location or the specific location, (320) connects the relevant school site and the site related to the department according to the department selection result information so that the user can immediately access the entrance information or the department related information of the school.

The cluster meeting unit 330 generates cluster meeting information in which a plurality of subjects selected by the same department are grouped by a predetermined number within a predetermined radius of the current location based or specific location basis, As shown in FIG. 14, includes a friend recommending unit 331, a cluster meeting generating unit 332, and a meeting information providing unit 333.

The friend recommending unit 331 provides a recommendable friend list to a subject having the same department selection result as the subject within the local radius set on the basis of the current location based or specific location, Ask the cluster members to approve the friends registered as friends in the cluster.

In addition, the meeting information providing unit 333 provides the meeting schedule information of the subjects having the same department selection result within the local radius set on the basis of the current location basis or the specific location, and can share them among the subjects set as the cluster meeting Provide information about the department.

FIG. 15 is a flowchart illustrating a schematic operation flow according to the use of a mobile terminal according to the present invention. In the mobile communication module 290, at least one of the department selection result information, the publicity content information, To the external mobile terminal (S10), and the transferred department-related information and additional service information are displayed on the mobile display unit 310 (S20).

Next, the mobile terminal 300 confirms the transmitted department, selection result information, department related service, and executes the department related supplementary service (S30).

In step S30, the department-related supplementary service can create a cluster meeting between the subjects who execute the publicized contents of the school or the department selected by the subject, the service to access the school and the site of the department, And a service that can inquire the calculated virtual competition rate can be provided.

FIG. 16 is a flowchart showing a detailed flow when executing a service capable of creating a cluster meeting between subjects who have the same department selection result in step S30. In this embodiment, (S31) of providing, as a recommendation friend list, the subjects having the same department selection result as the subject within the local radius set on the basis of the current location basis or the specific location, and using the cluster meeting generation unit 332, A step S33 of requesting cluster cluster approval for the subjects registered as friends in the list is performed.

Next, the step S35 of checking whether or not the requested subjects have approved the cluster meeting is performed. If it is confirmed that the subjects have approved the cluster meeting, the meeting information providing unit 333 is used to set the department information (S37) of sharing the set meeting schedule information.

In step S30, when executing the virtual competitive rate inquiry service, a step of inquiring the expected competitive rate concerning the priority class of the department selection result estimated by the virtual competitive rate estimation module using the virtual competitive rate inquiry module is performed according to the additional service Various embodiments may be configured.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the invention.

110: subject preference database 210: question evaluation module
120: Department of Mathematics Database 220: Numerical Computation Module
130: Occupational Environment Preference Database 230: Pair Comparison Module
140: sequence preference database 240: priority processing module
150: Tester Database 250: Course Selection Module
160: Standard comparison database 260: Consistency check module
170: Expert Group Database 270: Content Management Module
280: virtual competition rate estimation module 281:
282: virtual competition rate calculating unit 283: peripheral area calculating unit
284: Grade-specific calculation unit 290: Mobile communication module
300: mobile terminal 310: mobile display
320: Site connection part 330: Cluster meeting part
331: Friend recommendation unit 332: Cluster meeting generation unit
333: Meeting information providing unit 340: Virtual competition rate inquiry unit

Claims (10)

In the department selection system including subject preference database, department suitability database, occupational environment preference database, family preference database, standard comparison database, question evaluation module, pair comparison module, numerical comparison calculation module, priority processing module and department selection module ,
A content management module for collecting and managing public relations contents related to the school and department;
A mobile communication module connected to the department selection module and transmitting at least any one of department selection result information, publicity contents, and department related additional services to an external mobile terminal;
And a mobile terminal for confirming the department selection result information and the department related supplementary service transmitted from the mobile communication module and executing the additional service related to the department.
The method according to claim 1,
The mobile terminal comprises:
A mobile display unit for displaying the department selection result information and displaying the contents related to the department of the school which coincides with the department selection result information within the local radius set on the basis of the current location based or specific location,
And a site linking unit for linking the school site and site related to the site according to the site selection result information.
3. The method of claim 2,
The mobile terminal comprises:
Further comprising a cluster meeting unit for generating cluster meeting information in which a plurality of subjects selected by the same department are grouped into a certain number of units within a predetermined radius of the current location based or specific location basis.
The method of claim 3,
The cluster meeting unit,
A friend recommending unit for providing a recommendable friend list to a subject who has the same department selection result as the subject within a local radius set on the basis of a current location or a specific location;
A cluster meeting generating unit for requesting approval of the cluster meeting for the subjects registered as friends in the recommended friend list and
And a meeting information providing unit for providing meeting information of subjects having the same department selection result within a local radius set based on the current location based or specific location.
The method according to claim 1,
And a virtual competition rate estimation module connected to the department selection module and estimating an expected competition rate of a priority department of the department selection result.
6. The method of claim 5,
Wherein the virtual competitive rate estimation module comprises:
A department inquiry department for inquiring the subject selected by the subject according to the result of the subject selection result;
A virtual competition rate calculating unit for calculating the virtual competition rate according to the expected number of students for each school by inquiring the number of subjects matching the result of the above-mentioned department selection based on the region set by the subject;
And a peripheral area calculating unit for calculating and providing virtual competition rates of surrounding areas other than the area set by the subject,
And a grade-based calculation unit for calculating the virtual competition rate of the subject by the grade level.
A database of a plurality of questionnaires for subject preference test, departmental fitness test, job environment preference test, and family preference test, and determining a predetermined numerical value according to an answer to each questionnaire; Generating a standard comparison database by normalizing numerical values obtained by executing a predetermined number of graduate students per each major; Performing a test on a subject to obtain a numerical value of each subject of the questionnaire; Comparing the numerical value of the subject and the numerical value of the graduate student, and deriving the final numerical value of the subject according to the type by the QFD (Quality Function Development) method through the predetermined weighting; Deriving the final numerical value of the subject by assigning predetermined weights to the numerical values obtained through the pair comparison of each question through the AHP (Analytic Hierarchy Process) method in the sequence preference test, and extracting a predetermined number of preferred subjects; Selecting a final department by summing and comparing the final numerical values,
(a) transmitting at least any one or more of the department selection result information, the publicity content information, and the department related service information to the external mobile terminal using the mobile communication module; and
(b) checking the transferred department and selection result information and the department related supplementary service using the mobile terminal, and executing the supplementary service related to the department.
8. The method of claim 7,
The step (b)
(b-1) a step of generating cluster meeting information in which a number of subjects selected by the same department within a predetermined radius of the current location-based or specific location basis are grouped by a certain number of units using the cluster meeting unit Method selection method.
9. The method of claim 8,
Wherein the step (b-1)
(b-1-1) providing, as a recommendation friend list, a subject having the same department selection result as the subject within a local radius set on the basis of the current location or the specific location, using the friend recommending unit; and
(b-1-2) requesting approval of a cluster meeting for the subjects registered as friends in the recommended friend list by using the cluster meeting generating unit.
8. The method of claim 7,
The step (b)
and (b-2) using the virtual competitive rate inquiry unit to inquire the expected competitive rate of the prioritized department of the department selection result estimated by the virtual competitive rate estimation module.

Images