CN112651862A - Student academic development direction planning method, device, equipment and readable storage medium - Google Patents
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Abstract
The invention relates to the technical field of student occupation planning, in particular to a student academic development direction planning method, device, equipment and readable storage medium. According to the method and the device, the students answer the closed questions to obtain the first keywords and the second keywords, the first recommended occupation is obtained through the first keywords, the second recommended occupation is obtained through the second keywords, the first recommended occupation and the second recommended occupation are fused, and the development directions of the student academic industry can be recommended more accurately. The first keywords are interest keywords, the second keywords are character keywords, and the interest factors and the character factors of the students can be comprehensively considered, so that the development direction of the academic industry of the students can be comprehensively planned.
Description
Technical Field
The invention relates to the technical field of student occupation planning, in particular to a student academic development direction planning method, device, equipment and readable storage medium.
Background
In present education, different academic development directions are formulated according to different conditions of students, so that education according to the situation is facilitated, the learning enthusiasm of the students can be improved, and the learning effect of the students can also be improved. However, how to accurately plan the academic development direction of students is a difficult problem.
Disclosure of Invention
The invention aims to provide a student academic development direction planning method, a student academic development direction planning device and a readable storage medium, so as to solve the problems.
In one aspect, an embodiment of the present application provides a student academic development direction planning method, where the method includes:
sending the first questionnaire to a user interaction interface;
obtaining first answers of students to each first question in the first questionnaire, and obtaining first keywords corresponding to each first answer;
finding out a first recommended occupation corresponding to each first keyword;
sending the second questionnaire to the user interaction interface;
obtaining second answers of the students to each second question in the second questionnaires, and obtaining second keywords corresponding to each second answer;
finding out a second recommended occupation corresponding to each second keyword;
and obtaining a recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
Optionally, before sending the questions in the first questionnaire to the user interaction interface, the method includes:
acquiring first data, wherein the first data comprises a first word bank, a second word bank and a career bank, the first word bank comprises a plurality of first keywords, the second word bank comprises a plurality of second keywords, and the career bank comprises a plurality of careers;
according to big data statistics, establishing a first corresponding relation between each first keyword and one or more professions, wherein in the first corresponding relation, the profession corresponding to the first keyword is suitable for the profession of the first keyword;
according to big data statistics, establishing a second corresponding relation between each second keyword and one or more professions, wherein in the second corresponding relation, the profession corresponding to the first keyword is suitable for the profession of the second keyword;
obtaining second data, the second data comprising a question for answering to a student, the question being a closed question, the question comprising a first question and a second question;
establishing a third corresponding relation between each answer of the first question and one first keyword; establishing a fourth corresponding relation between each answer of the second question and one second keyword;
and transmitting the first corresponding relation, the second corresponding relation, the third corresponding relation and the fourth corresponding relation to a database for storage.
Optionally, after the transmitting the first corresponding relationship, the second corresponding relationship, the third corresponding relationship, and the fourth corresponding relationship to a database for storage, the method further includes:
according to big data statistics, establishing a fifth corresponding relation between each first keyword and one or more professions, wherein in the fifth corresponding relation, the profession corresponding to the first keyword is a profession unsuitable for the first keyword;
according to big data statistics, establishing a sixth corresponding relation between each second keyword and one or more professions, wherein in the sixth corresponding relation, the profession corresponding to the first keyword is a profession unsuitable for the second keyword;
and transmitting the fifth corresponding relation and the sixth corresponding relation to a database for storage.
Optionally, the obtaining a first answer of the student to each first question in the first questionnaire, and obtaining a first keyword corresponding to each first answer includes:
obtaining the answer of the student to the first question in the first questionnaire, and recording the answer as a third answer;
acquiring a third corresponding relation, wherein the third corresponding relation comprises a corresponding relation between the third answer and the first keyword;
finding out a first keyword corresponding to the third answer according to the third corresponding relation;
finding out a second first question according to the first keyword, wherein the second first question is a first question with answers including the third answer;
sending the second one of the first questions to a user interaction interface;
repeating the method, finding out odd first questions which are first question groups, wherein the odd first questions can obtain odd first keywords from the first question groups, counting all the obtained first keywords from the first question groups, and selecting the first keyword with the most frequency as the first keyword finally selected from the first question groups.
Optionally, the finding out odd number of first questions, where the odd number of first questions is a first question group, where the odd number of first keywords are available in the first question group, counting all the obtained first keywords in the first question group, and selecting the first keyword with the highest frequency of occurrence as the first keyword finally selected by the first question group, further includes:
and repeating the method to select the finally selected first key words of the plurality of first question groups.
Optionally, the obtaining a second answer of the student to each second question in the second questionnaire, and obtaining a second keyword corresponding to each second answer include:
obtaining the answer of the student to the first second question in the second questionnaire, and recording the answer as a fourth answer;
acquiring a fourth corresponding relation, wherein the fourth corresponding relation comprises a corresponding relation between the fourth answer and a second keyword;
finding out a first second keyword corresponding to the fourth answer according to the fourth corresponding relation;
finding out a second question according to the first second keyword, wherein the second question is a second question with answers including the fourth answer;
sending the second one of the second questions to a user interaction interface;
and repeating the method to find out odd second problems which are second problem groups, wherein the second problem groups can obtain odd second keywords, counting all the obtained second keywords in the second problem groups, and selecting the second keyword with the most frequency as the finally selected second keyword of the second problem groups.
Optionally, the finding out odd second questions, where the odd second questions are a second question group, where the second question group may obtain odd second keywords, counting all the obtained second keywords in the second question group, and selecting the second keyword with the highest frequency of occurrence as the finally selected second keyword in the second question group, further includes:
and repeating the method to select the finally selected second keywords of the plurality of second question groups.
Optionally, the finding out the first recommended occupation corresponding to each of the first keywords includes:
acquiring a first corresponding relation, wherein the first corresponding relation comprises a corresponding relation between each first keyword and one or more professions, and in the first corresponding relation, the profession corresponding to the first keyword is a profession suitable for the first keyword;
and finding out a first recommended occupation corresponding to each first keyword according to the first corresponding relation.
Optionally, the finding out the second recommended occupation corresponding to each of the second keywords includes:
acquiring a second corresponding relation, wherein the second corresponding relation comprises a corresponding relation between each second keyword and one or more professions, and in the second corresponding relation, the profession corresponding to the second keyword is a profession suitable for the second keyword;
and finding out a second recommended occupation corresponding to each second keyword according to the second corresponding relation.
Optionally, the obtaining of the recommended student academic development direction according to the first recommended occupation and the second recommended occupation comprises:
acquiring the first recommended occupation of each first keyword; each of the first recommended professions comprises one or more professions;
acquiring each first keyword and a fifth corresponding relation, wherein the fifth corresponding relation comprises the corresponding relation between the first keyword and the part of the first keyword which is not suitable for occupation;
taking and combining the careers in each first recommended career to obtain a first career set;
finding out a first non-recommended occupation of each first keyword according to the fifth corresponding relation; each of the first non-recommended professions comprises one or more professions; taking and combining each first non-recommended occupation to obtain a second occupation set;
combining and intersecting the first career set and the second career set, recording as a first intersection, judging whether the first intersection is empty, and if the first intersection is not empty, deleting careers in the first intersection from the first recommended careers;
acquiring the second recommended occupation of each second keyword; each of the second recommended professions comprises one or more professions;
acquiring each second keyword and a sixth corresponding relation, wherein the sixth corresponding relation comprises the corresponding relation between the second keyword and the part of the second keyword which is not suitable for occupation;
taking and combining the careers in each second recommended career to obtain a third career set;
finding out a second non-recommended occupation of each second keyword according to the sixth corresponding relation; each of the second non-recommended professions comprises one or more professions; taking a union set of each second non-recommended occupation to obtain a fourth occupation set;
and combining and intersecting the third career set and the fourth career set, recording as a second intersection, judging whether the second intersection is empty, and if the second intersection is not empty, deleting careers in the second intersection from the second recommended career.
Optionally, the obtaining of the recommended student academic development direction according to the first recommended occupation and the second recommended occupation includes:
counting all first careers in each first recommended career, marking the number of each first career, and recording as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
taking and combining each first occupation to obtain a first occupation set; taking and combining each second occupation to obtain a second occupation set;
combining and intersecting the first career set and the second career set, and judging whether the first career set and the second career set are intersected or not;
and if the first occupation set and the second occupation set have an intersection, respectively adding the first marks and the second marks of the occupation in the intersection, and taking the occupation with the maximum mark value after the addition as the recommended development direction of the student academic industry.
Optionally, after the intersection is taken between the first career set and the second career set, and whether there is an intersection between the first career set and the second career set is determined, the method further includes:
and if the first occupation set and the second occupation set are not intersected, sequencing the numerical value of each first mark and the numerical value of each second mark, and selecting the occupation with the maximum marked numerical value as the recommended development direction of the student academic industry.
In a second aspect, an embodiment of the present application provides a student academic development direction planning apparatus, where the apparatus includes:
the first sending module is used for sending the first questionnaire to the user interaction interface;
the first obtaining module is used for obtaining first answers of students to each first question in the first questionnaire and obtaining first keywords corresponding to each first answer;
the first calculation module is used for finding out a first recommended occupation corresponding to each first keyword;
the second sending module is used for sending the second questionnaire to the user interaction interface;
the second obtaining module is used for obtaining second answers of the students to each second question in the second questionnaire and obtaining second keywords corresponding to each second answer;
the second calculation module is used for finding out a second recommended occupation corresponding to each second keyword;
and the third calculation module is used for obtaining the recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
Optionally, the student academic development direction planning apparatus further includes:
the third acquisition module is used for acquiring first data, wherein the first data comprises a first word stock, a second word stock and a vocational stock, the first word stock comprises a plurality of first keywords, the second word stock comprises a plurality of second keywords, and the vocational stock comprises a plurality of vocational services;
a fourth calculation module, configured to establish a first correspondence between each first keyword and one or more professions according to big data statistics, where in the first correspondence, a profession corresponding to the first keyword is a profession suitable for the first keyword;
a fifth calculation module, configured to establish a second correspondence between each second keyword and one or more professions according to big data statistics, where in the second correspondence, a profession corresponding to the first keyword is a profession suitable for the second keyword;
a fourth obtaining module, configured to obtain second data, where the second data includes a question for answering to a student, the question is a closed question, and the question includes a first question and a second question;
a sixth calculation module, configured to establish a third correspondence between each answer to the first question and one of the first keywords; establishing a fourth corresponding relation between each answer of the second question and one second keyword;
and the third sending module is used for transmitting the first corresponding relation, the second corresponding relation, the third corresponding relation and the fourth corresponding relation to a database for storage.
Optionally, the student academic development direction planning apparatus further includes:
a seventh calculation module, configured to establish a fifth correspondence between each first keyword and one or more professions according to big data statistics, where in the fifth correspondence, a profession corresponding to the first keyword is a profession unsuitable for the first keyword;
the eighth calculation module is configured to establish a sixth correspondence between each second keyword and one or more professions according to big data statistics, where in the sixth correspondence, a profession corresponding to the first keyword is a profession unsuitable for the second keyword;
and the fourth sending module is used for transmitting the fifth corresponding relation and the sixth corresponding relation to a database for storage.
Optionally, the first obtaining module includes:
the first acquisition unit is used for acquiring answers of the students to a first question in the first questionnaire, and recording the answers as third answers;
a second obtaining unit, configured to obtain a third corresponding relationship, where the third corresponding relationship includes a corresponding relationship between the third answer and the first keyword;
the first calculating unit is used for finding out a first keyword corresponding to the third answer according to the third corresponding relation;
a second calculating unit, configured to find a second first question according to the first keyword, where the second first question is a first question whose answer includes the third answer;
the first sending unit is used for sending the second first question to a user interaction interface;
and the third calculation unit is used for repeatedly using the units to find out odd first questions, wherein the odd first questions are first question groups, the first question groups can obtain odd first keywords, all the first keywords obtained in the first question groups are counted, and the first keyword with the most frequency of occurrence is selected as the first keyword finally selected by the first question groups.
Optionally, the first obtaining module further includes:
and a fourth calculating unit for selecting the finally selected first keyword of the plurality of first question groups by repeatedly using the units.
Optionally, the second obtaining module includes:
the third acquisition unit is used for acquiring answers of the students to the first second question in the second questionnaire, and recording the answers as fourth answers;
a fourth obtaining unit, configured to obtain a fourth corresponding relationship, where the fourth corresponding relationship includes a corresponding relationship between the fourth answer and a second keyword;
a fifth calculating unit, configured to find a first second keyword corresponding to the fourth answer according to the fourth corresponding relationship;
a sixth calculating unit, configured to find a second question according to the first second keyword, where the second question is a second question whose answer includes the fourth answer;
the second sending unit is used for sending the second question to a user interaction interface;
and the seventh calculating unit is used for repeatedly using the units to find out odd second problems, wherein the odd second problems are second problem groups, the second problem groups can obtain odd second keywords, all the obtained second keywords in the second problem groups are counted, and the second keyword with the most frequency is selected as the finally selected second keyword of the second problem group.
Optionally, the second obtaining module further includes:
and an eighth calculating unit, configured to select the finally selected second keyword of the plurality of second question groups by repeatedly using the units.
Optionally, the first computing module includes:
a fifth obtaining unit, configured to obtain a first corresponding relationship, where the first corresponding relationship includes a corresponding relationship between each first keyword and one or more professions, and in the first corresponding relationship, a profession corresponding to the first keyword is a profession suitable for the first keyword;
and the ninth calculation unit is used for finding out the first recommended occupation corresponding to each first keyword according to the first corresponding relation.
Optionally, the second computing module includes:
a sixth obtaining unit, configured to obtain a second corresponding relationship, where the second corresponding relationship includes a corresponding relationship between each second keyword and one or more professions, and in the second corresponding relationship, a profession corresponding to the second keyword is a profession suitable for the second keyword;
and the tenth calculating unit is used for finding out a second recommended occupation corresponding to each second keyword according to the second corresponding relation.
Optionally, the student academic development direction planning apparatus further includes:
a fifth obtaining module, configured to obtain the first recommended occupation of each first keyword; each of the first recommended professions comprises one or more professions;
a sixth obtaining module, configured to obtain each first keyword and a fifth corresponding relationship, where the fifth corresponding relationship includes a corresponding relationship between the first keyword and an inappropriate career of the first keyword;
the ninth calculation module is used for taking a union set of the careers in each first recommended career to obtain a first career set;
a tenth calculation module, configured to find out, according to the fifth correspondence, a first unplanned occupation of each first keyword; each of the first non-recommended professions comprises one or more professions; taking and combining each first non-recommended occupation to obtain a second occupation set;
an eleventh calculation module, configured to obtain an intersection from the first career set and the second career set, record the intersection as a first intersection, determine whether the first intersection is empty, and delete careers in the first intersection from the first recommended career if the first intersection is not empty;
a seventh obtaining module, configured to obtain the second recommended occupation of each second keyword; each of the second recommended professions comprises one or more professions;
an eighth obtaining module, configured to obtain each second keyword and a sixth corresponding relationship, where the sixth corresponding relationship includes a corresponding relationship between the second keyword and an inappropriate career of the second keyword;
a twelfth calculation module, configured to merge the careers in each of the second recommended careers to obtain a third career set;
a thirteenth calculating module, configured to find out a second unpinned occupation of each second keyword according to the sixth correspondence; each of the second non-recommended professions comprises one or more professions; taking a union set of each second non-recommended occupation to obtain a fourth occupation set;
and a fourteenth calculation module, configured to collect an intersection of the third career set and the fourth career set, record the intersection as a second intersection, determine whether the second intersection is empty, and delete careers in the second intersection from the second recommended career if the second intersection is not empty.
Optionally, the third computing module comprises:
an eleventh calculating unit, configured to count all the first careers in each of the first recommended careers, mark the number of each of the first careers, and record the number as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
a twelfth calculating unit, configured to merge each of the first careers to obtain a first career set; taking and combining each second occupation to obtain a second occupation set;
a thirteenth calculating unit, configured to join the first career set and the second career set to form an intersection, and determine whether the first career set and the second career set intersect;
and if the first occupation set and the second occupation set have an intersection, adding the first marks and the second marks of the occupation in the intersection respectively, and taking the occupation with the maximum mark value after the addition as the recommended student academic development direction.
Optionally, the third computing module further comprises:
and the fifteenth calculation unit is used for sorting the numerical value of each first mark and the numerical value of each second mark if the first occupation set and the second occupation set are not intersected, and selecting the occupation with the maximum numerical value as the recommended student academic development direction.
In a third aspect, an embodiment of the present application provides a student academic development direction planning apparatus, where the apparatus includes a memory and a processor, and the memory is used for storing a computer program; the processor is used for realizing the steps of the student academic development direction planning method when executing the computer program.
In a fourth aspect, the present application provides a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the student academic development direction planning method.
The invention has the beneficial effects that:
according to the method and the device, the students answer the closed questions to obtain the first keywords and the second keywords, the first recommended occupation is obtained through the first keywords, the second recommended occupation is obtained through the second keywords, the first recommended occupation and the second recommended occupation are fused, and the development directions of the student academic industry can be recommended more accurately. The first keywords are interest keywords, the second keywords are character keywords, and the interest factors and the character factors of the students can be comprehensively considered, so that the development direction of the academic industry of the students can be comprehensively planned.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic flow chart of a method for planning development direction of student academic aptitude in an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a development direction planning apparatus for student academic aptitude in the embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a development direction planning apparatus for student academic aptitude in an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a first obtaining module according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a second obtaining module according to an embodiment of the present invention;
FIG. 6 is a block diagram of a first computing module according to an embodiment of the present invention;
FIG. 7 is a block diagram of a second computing module according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a third computing module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers or letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example 1
As shown in fig. 1, the present embodiment provides a method for planning development directions of student academic aptitude, which includes step S100, step S200, step S300, step S400, step S500, step S600 and step S700.
S100, sending the first questionnaire to a user interaction interface;
s200, obtaining first answers of students to each first question in the first questionnaire, and obtaining first keywords corresponding to each first answer;
s300, finding out a first recommended occupation corresponding to each first keyword;
s400, sending the second questionnaire to a user interaction interface;
s500, obtaining second answers of the students to each second question in the second questionnaire, and obtaining second keywords corresponding to each second answer;
s600, finding out a second recommended occupation corresponding to each second keyword;
and S700, obtaining a recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
The first keyword may be a keyword representing an interest, and the second keyword may be a keyword representing a character.
In a specific embodiment of the present disclosure, the method may further include step S10, step S20, step S30, step S40, step S50, and step S60.
S10, acquiring first data, wherein the first data comprises a first word bank, a second word bank and a career bank, the first word bank comprises a plurality of first keywords, the second word bank comprises a plurality of second keywords, and the career bank comprises a plurality of careers;
s20, establishing a first corresponding relation between each first keyword and one or more professions according to big data statistics, wherein in the first corresponding relation, the professions corresponding to the first keywords are professions suitable for the first keywords;
s30, establishing a second corresponding relation between each second keyword and one or more professions according to big data statistics, wherein in the second corresponding relation, the profession corresponding to the first keyword is suitable for the profession of the second keyword;
s40, obtaining second data, wherein the second data comprises questions used for answering to students, the questions are closed questions, and the questions comprise first questions and second questions;
s50, establishing a third corresponding relation between each answer of the first question and one first keyword; establishing a fourth corresponding relation between each answer of the second question and one second keyword;
and S60, transmitting the first corresponding relation, the second corresponding relation, the third corresponding relation and the fourth corresponding relation to a database for storage.
Optionally, the method may further include step S70, step S80, and step S90.
S70, establishing a fifth corresponding relation between each first keyword and one or more professions according to big data statistics, wherein in the fifth corresponding relation, the profession corresponding to the first keyword is a profession unsuitable for the first keyword;
s80, establishing a sixth corresponding relation between each second keyword and one or more professions according to big data statistics, wherein in the sixth corresponding relation, the profession corresponding to the first keyword is a profession unsuitable for the second keyword;
and S90, transmitting the fifth corresponding relation and the sixth corresponding relation to a database for storage.
In a specific embodiment of the present disclosure, the step S200 may include a step S201, a step S202, a step S203, a step S204, a step S205, and a step S206.
Step S201, obtaining answers of students to a first question in the first questionnaire, and recording the answers as third answers;
s202, acquiring a third corresponding relation, wherein the third corresponding relation comprises the corresponding relation between the third answer and the first keyword;
s203, finding out a first keyword corresponding to the third answer according to the third corresponding relation;
step S204, finding out a second first question according to the first keyword, wherein the second first question is a first question with answers including the third answer;
s205, sending the second first question to a user interaction interface;
step S206, repeating the steps S201 to S205, finding out odd first problems, wherein the odd first problems are first problem groups, odd first keywords can be obtained from the first problem groups, counting all the obtained first keywords in the first problem groups, and selecting the first keyword with the most frequency as the first keyword finally selected by the first problem groups.
In a specific embodiment of the present disclosure, the step S200 may further include a step S207.
And step S207, repeating the steps S201 to S206, and selecting the finally selected first keywords of the plurality of first question groups.
In a specific embodiment of the present disclosure, the step S500 may include a step S501, a step S502, a step S503, a step S504, a step S505, and a step S506.
Step S501, obtaining answers of the students to a first second question in the second questionnaire, and recording the answers as fourth answers;
s502, obtaining a fourth corresponding relation, wherein the fourth corresponding relation comprises a corresponding relation between the fourth answer and a second keyword;
step S503, finding out a first second keyword corresponding to the fourth answer according to the fourth corresponding relation;
step S504, finding out a second question according to the first second keyword, wherein the second question is a second question with answers including the fourth answer;
step S505, sending the second question to a user interaction interface;
step S506, repeating the steps S501 to S505, finding out odd second problems, wherein the odd second problems are second problem groups, odd second keywords can be obtained from the second problem groups, counting all the obtained second keywords in the second problem groups, and selecting the second keyword with the most frequency as the finally selected second keyword of the second problem group.
In a specific embodiment of the present disclosure, the step S500 may further include a step S507.
And step S207, repeating the steps S501 to S506, and selecting the finally selected second keywords of the plurality of second question groups.
In a specific embodiment of the present disclosure, the step S300 may include a step S301 and a step S302.
Step S301, obtaining a first corresponding relation, wherein the first corresponding relation comprises a corresponding relation between each first keyword and one or more professions, and in the first corresponding relation, the profession corresponding to the first keyword is a profession suitable for the first keyword;
step S302, finding out a first recommended occupation corresponding to each first keyword according to the first corresponding relation.
In a specific embodiment of the present disclosure, the step S600 may include a step S601 and a step S602.
S601, obtaining a second corresponding relation, wherein the second corresponding relation comprises a corresponding relation between each second keyword and one or more professions, and in the second corresponding relation, the profession corresponding to the second keyword is a profession suitable for the second keyword;
step S602, according to the second corresponding relation, finding out a second recommended occupation corresponding to each second keyword.
In a specific embodiment of the present disclosure, before the step S700, a step S610, a step S611, a step S612, a step S613, a step S614, a step S615, a step S616, a step S617, a step S618, and a step S619 may be further included.
Step S610, acquiring the first recommended occupation of each first keyword; each of the first recommended professions comprises one or more professions;
s611, acquiring each first keyword and a fifth corresponding relation, wherein the fifth corresponding relation comprises the corresponding relation between the first keyword and the corresponding relation which is not suitable for occupation;
step S612, taking a union set of careers in each first recommended career to obtain a first career set;
step S613, finding out a first non-recommended occupation of each first keyword according to the fifth corresponding relation; each of the first non-recommended professions comprises one or more professions; taking and combining each first non-recommended occupation to obtain a second occupation set;
step S614, an intersection is taken from the first career set and the second career set, the intersection is recorded as a first intersection, whether the first intersection is empty or not is judged, and if the first intersection is not empty, careers in the first intersection are deleted from the first recommended careers;
s615, acquiring the second recommended occupation of each second keyword; each of the second recommended professions comprises one or more professions;
s616, acquiring each second keyword and a sixth corresponding relation, wherein the sixth corresponding relation comprises the corresponding relation between the second keywords and the sites which are not suitable for occupation;
step S617, taking a union set of careers in each second recommended career to obtain a third career set;
step 618, finding out a second unplanned occupation of each second keyword according to the sixth corresponding relation; each of the second non-recommended professions comprises one or more professions; taking a union set of each second non-recommended occupation to obtain a fourth occupation set;
step S619, an intersection is taken from the third career set and the fourth career set, the intersection is recorded as a second intersection, whether the second intersection is empty or not is judged, and if the second intersection is not empty, careers in the second intersection are deleted from the second recommended careers.
In a specific embodiment of the present disclosure, the step S700 may include steps S731, S732, S733, and S734:
step S731, counting all first careers in each first recommended career, marking the number of each first career as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
s732, taking a union set of each first occupation to obtain a first occupation set; taking and combining each second occupation to obtain a second occupation set;
step S733, combining the first occupation set and the second occupation set to obtain an intersection, and judging whether the first occupation set and the second occupation set have the intersection;
step S734, if the first occupation set and the second occupation set have an intersection, adding the first marks and the second marks of the occupation in the intersection respectively, and taking the occupation with the largest added mark value as a recommended student academic development direction.
In a specific embodiment of the present disclosure, the step S700 may further include a step S735.
And S735. if the first occupation set and the second occupation set are not intersected, sequencing the numerical value of each first mark and the numerical value of each second mark, and selecting the occupation with the maximum mark numerical value as the recommended student academic development direction.
Example 2
As shown in fig. 2, the present embodiment provides a device for planning development directions of student academic aptitude, which includes a first sending module 701, a first obtaining module 702, a first calculating module 703, a second sending module 704, a second obtaining module 705, a second calculating module 706, and a third calculating module 707.
A first sending module 701, configured to send the first questionnaire to a user interaction interface;
a first obtaining module 702, configured to obtain a first answer to each first question in the first questionnaire from the student, and obtain a first keyword corresponding to each first answer;
a first calculation module 703, configured to find out a first recommended occupation corresponding to each first keyword;
a second sending module 704, configured to send the second questionnaire to the user interaction interface;
a second obtaining module 705, configured to obtain a second answer to each second question in the second questionnaire by the student, and obtain a second keyword corresponding to each second answer;
a second calculating module 706, configured to find a second recommended occupation corresponding to each second keyword;
and the third calculation module 707 is configured to obtain a recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
In a specific embodiment of the present disclosure, the student academic development direction planning apparatus may further include:
a third obtaining module 708, configured to obtain first data, where the first data includes a first lexicon, a second lexicon, and a vocational lexicon, the first lexicon includes a plurality of first keywords, the second lexicon includes a plurality of second keywords, and the vocational lexicon includes a plurality of vocational voca;
a fourth calculating module 709, configured to establish a first corresponding relationship between each first keyword and one or more professions according to big data statistics, where in the first corresponding relationship, a profession corresponding to the first keyword is a profession suitable for the first keyword;
a fifth calculating module 710, configured to establish a second correspondence between each second keyword and one or more professions according to big data statistics, where in the second correspondence, a profession corresponding to the first keyword is a profession suitable for the second keyword;
a fourth obtaining module 711, configured to obtain second data, where the second data includes a question for answering to a student, the question is a closed question, and the question includes a first question and a second question;
a sixth calculating module 712, configured to establish a third corresponding relationship between each answer of the first question and one first keyword; establishing a fourth corresponding relation between each answer of the second question and one second keyword;
a third sending module 713, configured to transmit the first corresponding relationship, the second corresponding relationship, the third corresponding relationship, and the fourth corresponding relationship to a database for storage.
In a specific embodiment of the present disclosure, the student academic development direction planning apparatus may further include:
a seventh calculating module 714, configured to establish a fifth corresponding relationship between each first keyword and one or more professions according to big data statistics, where in the fifth corresponding relationship, a profession corresponding to the first keyword is a profession unsuitable for the first keyword;
an eighth calculating module 715, configured to establish a sixth corresponding relationship between each second keyword and one or more professions according to big data statistics, where in the sixth corresponding relationship, a profession corresponding to the first keyword is a profession unsuitable for the second keyword;
a fourth sending module 716, configured to transmit the fifth corresponding relationship and the sixth corresponding relationship to a database for storage.
In a specific embodiment of the present disclosure, as shown in fig. 4, the first obtaining module 702 includes:
a first obtaining unit 7021, configured to obtain an answer to a first question in the first questionnaire from the student, and record the answer as a third answer;
a second obtaining unit 7022, configured to obtain a third corresponding relationship, where the third corresponding relationship includes a corresponding relationship between the third answer and the first keyword;
a first calculating unit 7023, configured to find a first keyword corresponding to the third answer according to the third corresponding relationship;
a second calculating unit 7024, configured to find a second first question according to the first keyword, where the second first question is a first question whose answer includes the third answer;
a first sending unit 7025, configured to send the second first question to a user interaction interface;
a third calculating unit 7026, configured to repeatedly use the above units, find out odd first questions, where the odd first questions are a first question group, where the odd first keywords are obtained from the first question group, perform statistics on all the obtained first keywords in the first question group, and select the first keyword with the highest frequency of occurrence as the first keyword finally selected by the first question group.
In a specific embodiment of the present disclosure, the first obtaining module further includes:
a fourth calculating unit 7027 is configured to select the finally selected first keyword of the plurality of first question groups by repeatedly using the above units.
In a specific embodiment of the present disclosure, as shown in fig. 5, the second obtaining module 705 includes:
a third obtaining unit 7051, configured to obtain an answer to the first second question in the second questionnaire from the student, and record the answer as a fourth answer;
a fourth obtaining unit 7052, configured to obtain a fourth corresponding relationship, where the fourth corresponding relationship includes a corresponding relationship between the fourth answer and the second keyword;
a fifth calculating unit 7053, configured to find out a first second keyword corresponding to the fourth answer according to the fourth corresponding relationship;
a sixth calculating unit 7054, configured to find a second question according to the first second keyword, where the second question is a second question whose answer includes the fourth answer;
a second sending unit 7055, configured to send the second question to a user interaction interface;
a seventh calculating unit 7056, configured to repeatedly use the above units, find out odd second questions, where the odd second questions are a second question group, where the second question group may obtain odd second keywords, perform statistics on all the obtained second keywords in the second question group, and select a second keyword that occurs most frequently as a second keyword finally selected by the second question group.
In a specific embodiment of the present disclosure, the second obtaining module 705 further includes:
an eighth calculating unit 7057 is configured to select the finally selected second keyword of the plurality of second question groups by repeatedly using the units.
In a specific embodiment of the present disclosure, as shown in fig. 6, the first calculating module 703 includes:
a fifth obtaining unit 7031, configured to obtain a first corresponding relationship, where the first corresponding relationship includes a corresponding relationship between each first keyword and one or more professions, and in the first corresponding relationship, a profession corresponding to the first keyword is a profession suitable for the first keyword;
a ninth calculating unit 7032, configured to find out, according to the first corresponding relationship, a first recommended occupation corresponding to each of the first keywords.
In a specific embodiment of the present disclosure, as shown in fig. 7, the second calculating module 706 includes:
a sixth obtaining unit 7061, configured to obtain a second corresponding relationship, where the second corresponding relationship includes a corresponding relationship between each second keyword and one or more professions, and in the second corresponding relationship, a profession corresponding to the second keyword is a profession suitable for the second keyword;
a tenth calculating unit 7062 is configured to find out, according to the second correspondence, a second recommended occupation corresponding to each second keyword.
In a specific embodiment of the present disclosure, the student academic development direction planning apparatus further includes:
a fifth obtaining module 717, configured to obtain the first recommended occupation of each of the first keywords; each of the first recommended professions comprises one or more professions;
a sixth obtaining module 718, configured to obtain each of the first keywords and a fifth corresponding relationship, where the fifth corresponding relationship includes a corresponding relationship between the first keyword and an inappropriate career thereof;
a ninth calculation module 719, configured to merge the careers in each of the first recommended careers to obtain a first career set;
a tenth calculating module 720, configured to find out the first unpinned occupation of each first keyword according to the fifth corresponding relationship; each of the first non-recommended professions comprises one or more professions; taking and combining each first non-recommended occupation to obtain a second occupation set;
an eleventh calculating module 721, configured to obtain an intersection from the first career set and the second career set, record the intersection as a first intersection, determine whether the first intersection is empty, and if the first intersection is not empty, delete careers in the first intersection from the first recommended career;
a seventh obtaining module 722, configured to obtain the second recommended occupation of each of the second keywords; each of the second recommended professions comprises one or more professions;
an eighth obtaining module 723, configured to obtain each of the second keywords and a sixth corresponding relationship, where the sixth corresponding relationship includes a corresponding relationship between the second keyword and an inappropriate career thereof;
a twelfth calculating module 724, configured to merge the careers in each of the second recommended careers to obtain a third career set;
a thirteenth calculating module 725, configured to find out, according to the sixth correspondence, a second unpinned occupation of each second keyword; each of the second non-recommended professions comprises one or more professions; taking a union set of each second non-recommended occupation to obtain a fourth occupation set;
a fourteenth calculating module 726, configured to collect an intersection of the third career set and the fourth career set, record the intersection as a second intersection, determine whether the second intersection is empty, and if the second intersection is not empty, delete careers in the second intersection from the second recommended career.
In an embodiment of the present disclosure, the third calculation module 707 shown in fig. 8 includes:
an eleventh calculating unit 7071, configured to count all the first careers in each of the first recommended careers, mark the number of each of the first careers, and record the number as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
a twelfth calculating unit 7072, configured to merge each of the first careers to obtain a first career set; taking and combining each second occupation to obtain a second occupation set;
a thirteenth calculating unit 7073, configured to join and intersect the first career set and the second career set, and determine whether the first career set and the second career set intersect;
a fourteenth calculating unit 7074 is configured to, if the first occupation set and the second occupation set have an intersection, add the first and second marks of the occupation in the intersection, and use the occupation with the largest added mark value as the recommended academic development direction of the student.
In a specific embodiment of the present disclosure, the third calculating module 707 further includes:
a fifteenth calculating unit 7075, configured to, if the first occupation set and the second occupation set do not intersect, sort the numerical value of each first marker and the numerical value of each second marker, and select the occupation with the largest numerical value as the recommended student academic development direction.
It should be noted that, regarding the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated herein.
Example 3
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a student academic development direction planning device, and the student academic development direction planning device described below and the student academic development direction planning method described above may be referred to in correspondence with each other.
Fig. 3 is a block diagram illustrating a student industry development direction planning apparatus 800, according to an example embodiment. As shown in fig. 3, the student industry development direction planning apparatus 800 may include: a processor 801, a memory 802. The student academic development direction planning apparatus 800 may further include one or more of a multimedia component 803, an input/output (I/O) interface 804, and a communication component 805.
The processor 801 is configured to control the overall operation of the student academic development direction planning apparatus 800, so as to complete all or part of the steps in the student academic development direction planning method. The memory 802 is used to store various types of data to support the operation of the student industry development direction planning device 800, which may include, for example, instructions for any application or method operating on the student industry development direction planning device 800, as well as application-related data such as contact data, messaging, pictures, audio, video, and the like. The Memory 802 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia components 803 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 802 or transmitted through the communication component 805. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the student industry development direction planning device 800 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding Communication component 805 may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the student industry development direction planning apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the student industry development direction planning method.
In another exemplary embodiment, there is also provided a computer readable storage medium including program instructions which, when executed by a processor, implement the steps of the student academic development direction planning method described above. For example, the computer readable storage medium may be the memory 802 described above that includes program instructions executable by the processor 801 of the student industry development direction planning apparatus 800 to perform the student industry development direction planning method described above.
Example 4
Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium, and a readable storage medium described below and a student academic development direction planning method described above may be referred to in correspondence.
A readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the student academic development direction planning method of the above-described method embodiment.
The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various other readable storage media capable of storing program codes.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A student academic development direction planning method is characterized by comprising the following steps:
sending the first questionnaire to a user interaction interface;
obtaining first answers of students to each first question in the first questionnaire, and obtaining first keywords corresponding to each first answer;
finding out a first recommended occupation corresponding to each first keyword;
sending the second questionnaire to the user interaction interface;
obtaining second answers of the students to each second question in the second questionnaires, and obtaining second keywords corresponding to each second answer;
finding out a second recommended occupation corresponding to each second keyword;
and obtaining a recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
2. The student academic development direction planning method according to claim 1, wherein the obtaining of the first answer of the student to each first question in the first questionnaire and the obtaining of the first keyword corresponding to each first answer comprise:
obtaining the answer of the student to the first question in the first questionnaire, and recording the answer as a third answer;
acquiring a third corresponding relation, wherein the third corresponding relation comprises a corresponding relation between the third answer and the first keyword;
finding out a first keyword corresponding to the third answer according to the third corresponding relation;
finding out a second first question according to the first keyword, wherein the second first question is a first question with answers including the third answer;
sending the second one of the first questions to a user interaction interface;
repeating the method, finding out odd first questions which are first question groups, wherein the odd first questions can obtain odd first keywords from the first question groups, counting all the obtained first keywords from the first question groups, and selecting the first keyword with the most frequency as the first keyword finally selected from the first question groups.
3. The student academic development direction planning method according to claim 1, wherein the obtaining of the second answer of the student to each second question in the second questionnaire and the obtaining of the second keyword corresponding to each second answer comprise:
obtaining the answer of the student to the first second question in the second questionnaire, and recording the answer as a fourth answer;
acquiring a fourth corresponding relation, wherein the fourth corresponding relation comprises a corresponding relation between the fourth answer and a second keyword;
finding out a first second keyword corresponding to the fourth answer according to the fourth corresponding relation;
finding out a second question according to the first second keyword, wherein the second question is a second question with answers including the fourth answer;
sending the second one of the second questions to a user interaction interface;
and repeating the method to find out odd second problems which are second problem groups, wherein the second problem groups can obtain odd second keywords, counting all the obtained second keywords in the second problem groups, and selecting the second keyword with the most frequency as the finally selected second keyword of the second problem groups.
4. The student industry development direction planning method of claim 1, wherein the obtaining of the recommended student industry development direction according to the first recommended occupation and the second recommended occupation comprises:
counting all first careers in each first recommended career, marking the number of each first career, and recording as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
taking and combining each first occupation to obtain a first occupation set; taking and combining each second occupation to obtain a second occupation set;
combining and intersecting the first career set and the second career set, and judging whether the first career set and the second career set are intersected or not;
and if the first occupation set and the second occupation set have an intersection, respectively adding the first marks and the second marks of the occupation in the intersection, and taking the occupation with the maximum mark value after the addition as the recommended development direction of the student academic industry.
5. The utility model provides a student's academic development direction planning device which characterized in that includes:
the first sending module is used for sending the first questionnaire to the user interaction interface;
the first obtaining module is used for obtaining first answers of students to each first question in the first questionnaire and obtaining first keywords corresponding to each first answer;
the first calculation module is used for finding out a first recommended occupation corresponding to each first keyword;
the second sending module is used for sending the second questionnaire to the user interaction interface;
the second obtaining module is used for obtaining second answers of the students to each second question in the second questionnaire and obtaining second keywords corresponding to each second answer;
the second calculation module is used for finding out a second recommended occupation corresponding to each second keyword;
and the third calculation module is used for obtaining the recommended student academic development direction according to the first recommended occupation and the second recommended occupation.
6. The student's academic development direction planning apparatus of claim 1, wherein the first acquisition module comprises:
the first acquisition unit is used for acquiring answers of the students to a first question in the first questionnaire, and recording the answers as third answers;
a second obtaining unit, configured to obtain a third corresponding relationship, where the third corresponding relationship includes a corresponding relationship between the third answer and the first keyword;
the first calculating unit is used for finding out a first keyword corresponding to the third answer according to the third corresponding relation;
a second calculating unit, configured to find a second first question according to the first keyword, where the second first question is a first question whose answer includes the third answer;
the first sending unit is used for sending the second first question to a user interaction interface;
and the third calculation unit is used for repeatedly using the units to find out odd first questions, wherein the odd first questions are first question groups, the first question groups can obtain odd first keywords, all the first keywords obtained in the first question groups are counted, and the first keyword with the most frequency of occurrence is selected as the first keyword finally selected by the first question groups.
7. The student's academic development direction planning apparatus of claim 1, wherein the second acquisition module comprises:
the third acquisition unit is used for acquiring answers of the students to the first second question in the second questionnaire, and recording the answers as fourth answers;
a fourth obtaining unit, configured to obtain a fourth corresponding relationship, where the fourth corresponding relationship includes a corresponding relationship between the fourth answer and a second keyword;
a fifth calculating unit, configured to find a first second keyword corresponding to the fourth answer according to the fourth corresponding relationship;
a sixth calculating unit, configured to find a second question according to the first second keyword, where the second question is a second question whose answer includes the fourth answer;
the second sending unit is used for sending the second question to a user interaction interface;
and the seventh calculating unit is used for repeatedly using the units to find out odd second problems, wherein the odd second problems are second problem groups, the second problem groups can obtain odd second keywords, all the obtained second keywords in the second problem groups are counted, and the second keyword with the most frequency is selected as the finally selected second keyword of the second problem group.
8. The student's academic development direction planning apparatus according to claim 1, wherein the third calculation module comprises:
an eleventh calculating unit, configured to count all the first careers in each of the first recommended careers, mark the number of each of the first careers, and record the number as a first mark; counting all second occupations in each second recommended occupation, marking the number of each second occupation, and marking as a second mark;
a twelfth calculating unit, configured to merge each of the first careers to obtain a first career set; taking and combining each second occupation to obtain a second occupation set;
a thirteenth calculating unit, configured to join the first career set and the second career set to form an intersection, and determine whether the first career set and the second career set intersect;
and if the first occupation set and the second occupation set have an intersection, adding the first marks and the second marks of the occupation in the intersection respectively, and taking the occupation with the maximum mark value after the addition as the recommended student academic development direction.
9. A student academic development direction planning apparatus, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the student academic development direction planning method according to any one of claims 1 to 4 when executing the computer program.
10. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when executed by a processor, carries out the steps of the student academic development direction planning method according to any one of claims 1 to 4.
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