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KR-20260062405-A - Educational Institution Recommendation System

KR20260062405AKR 20260062405 AKR20260062405 AKR 20260062405AKR-20260062405-A

Abstract

The educational institution recommendation system includes a communication unit that communicates with an external device, a control unit that stores evaluation scores for each of multiple educational institutions for each of multiple items including the student's disposition, personality, learning level, home location, and teacher preference, and, when a parent inputs data including the child's disposition, personality, learning level, home location, and teacher preference, analyzes the input data using an artificial intelligence model, assigns weights to each item of the analyzed data based on the analysis results, and transmits information on recommended educational institutions to the parent's terminal based on the similarity between the weighted data and the evaluation scores of multiple educational institutions.

Inventors

  • 석경아

Assignees

  • 석경아

Dates

Publication Date
20260507
Application Date
20241029

Claims (10)

  1. In the educational institution recommendation system, A communication unit that communicates with an external device; and An educational institution recommendation system characterized by including a control unit that stores evaluation scores for each of multiple educational institutions for each of multiple items including the student's disposition, personality, learning level, home location, and teacher preference, and when a parent inputs data including the child's disposition, personality, learning level, home location, and teacher preference, analyzes the input data using an artificial intelligence model, assigns weights to each item of the analyzed data based on the analysis results, and transmits information on recommended educational institutions to a parent's terminal based on the similarity between the weighted data and the evaluation scores of the multiple educational institutions.
  2. In Article 1, The above control unit is, An educational institution recommendation system characterized by storing the sum of evaluation scores of each of multiple educational institutions for each of the aforementioned multiple items according to the recommendation score range of the student being trained, calculating a recommendation score based on the set priority when a parent sets a priority score between 1 and 5 points for each item, and recommending the corresponding educational institution corresponding to the calculated recommendation score.
  3. In Article 2, An educational institution recommendation system characterized by the above-mentioned control unit calculating the recommendation score using the following formula. S=Wp*P + Wc*C + Wl*L + Wd*D + Wt*T S: Recommendation Score P: Preference C: Character L: Learning Level D: House Location (Distance) T: Teacher Preference (Teacher) Wp, Wc, Wl, Wd, Wt: Weights of each item based on the set priority
  4. In Paragraph 3, An educational institution recommendation system characterized by the following formula for calculating the weight of each item based on the set priority in the above control unit. Weight of each item based on set priority = 1 + 1 / set priority
  5. In Article 1, The above control unit is, An educational institution recommendation system characterized by storing multiple response solutions corresponding to multiple tendencies of the aforementioned parents and officials of the aforementioned multiple educational institutions, providing a consultation chat window upon a request from at least one of the aforementioned parents and officials of the aforementioned multiple educational institutions, analyzing the content of the provided consultation chat window to identify the tendencies of each of the aforementioned parents and officials of the aforementioned multiple educational institutions, and providing a response solution corresponding to the identified tendencies to each of the aforementioned parents and officials of the aforementioned multiple educational institutions.
  6. Regarding the method of recommending educational institutions, A step of storing evaluation scores from each of multiple educational institutions for each of multiple items including the trainee's disposition, personality, learning level, home location, and teacher preference; A step in which parents input data including the child's disposition, personality, learning level, home location, and teacher preference; A step of analyzing input data using an artificial intelligence model; A step of assigning weights to each item of the analyzed data based on the analysis results; and A method for recommending educational institutions characterized by including the step of transmitting information on recommended educational institutions to a parent terminal based on the similarity between weighted data and the evaluation scores of the plurality of educational institutions.
  7. In Article 6, A step of storing the sum of evaluation scores of each of the multiple educational institutions for each of the above multiple items according to the recommendation score ranges of the trainee; A step in which parents set a priority score between 1 and 5 for each item; A step of calculating a recommendation score based on the set priority; A method for recommending educational institutions characterized by including a step of recommending an educational institution corresponding to a calculated recommendation score.
  8. In Article 7, The method for recommending educational institutions is characterized by the step of calculating the recommendation score using the following formula. S=Wp*P + Wc*C + Wl*L + Wd*D + Wt*T S: Recommendation Score P: Preference C: Character L: Learning Level D: House Location (Distance) T: Teacher Preference (Teacher) Wp, Wc, Wl, Wd, Wt: Weights of each item based on the set priority
  9. In Article 8, An educational institution recommendation method characterized by the following formula for calculating the weight of each item based on the priority set above. Weight of each item based on set priority = 1 + 1 / set priority
  10. In Article 6, A step of storing multiple response solutions corresponding to multiple tendencies of the aforementioned parents and officials of the aforementioned multiple educational institutions; A step of providing a consultation chat window in response to a request from at least one of the aforementioned parents and officials of the aforementioned multiple educational institutions; A step of analyzing the content of the provided consultation chat window to identify the tendencies of each of the aforementioned parents and the relevant officials of the aforementioned multiple educational institutions; and A method for recommending educational institutions characterized by including the step of providing a response solution corresponding to the identified tendencies to each of the aforementioned parents and officials of the aforementioned multiple educational institutions.

Description

Educational Institution Recommendation System The present invention relates to an educational institution recommendation system, and more specifically, to an educational institution recommendation system that recommends an educational institution suitable for a child using multiple data. Generally, parents gather a great deal of information from an early age to provide their children with an education tailored to their needs. After obtaining and verifying information about educational institutions from other parents, they select an institution for their child to attend. While parents use various criteria to choose an educational institution, they tend to judge based on which institution provides the best education. However, the selection of such educational institutions may result in adaptation depending on the child's temperament and personality, or conversely, a transfer to another institution due to a lack of adaptation. Furthermore, while there are institutions that assess a child's learning level and provide education according to grade, it is difficult to find such institutions when the child is young. In addition, there are cases where an institution matching the child's temperament and learning level is found but is located far from home, making commuting very difficult. There is also a problem in that the child's temperament and personality may conflict with those of the teacher, yet this is not taken into consideration. Figure 1 is an overall control block diagram of an educational institution recommendation system according to the present invention. FIG. 2 is a flowchart of a first embodiment of an educational institution recommendation method according to the present invention. Figure 3 is a flowchart of the second embodiment of the educational institution recommendation method. Figure 4 is a flowchart of the third embodiment of the educational institution recommendation method. Hereinafter, an educational institution recommendation system (1) according to a preferred embodiment of the present invention will be described in detail with reference to the attached drawings. Figure 1 is an overall control block diagram of an educational institution recommendation system (1) according to the present invention. The educational institution recommendation system (1) includes a communication unit (10) and a control unit (20). The communication unit (10) communicates with an external device. The communication unit (10) can perform wireless communication, and the wireless communication includes at least one of infrared communication, RF, Zigbee, and Bluetooth. The communication unit (10) receives a video signal and transmits it to the control unit (20) to be described later, and can be implemented in various ways corresponding to the specifications of the received video signal and the implementation form of the user terminal. For example, the communication unit (10) can wirelessly receive an RF (radio frequency) signal transmitted from a broadcasting station (not shown), or receive a video signal according to composite video, component video, super video, SCART, HDMI (high definition multimedia interface) specifications, etc. via a wired connection. If the video signal is a broadcast signal, the communication unit (10) may include a tuner that tunes the broadcast signal by channel. The control unit (20) includes a data input module (21), a data analysis module (22), a weighting module (23), and an educational institution recommendation module (24). Parents can input data including the child's disposition, personality, learning level, home location, and teacher preference through the data input module (21). The data analysis module (22) can analyze input data using an artificial intelligence model. The weighting module (23) can assign weights to each item of the analyzed data based on the analysis results of the data analysis module (22). The educational institution recommendation module (24) can produce recommended educational institutions based on the similarity between weighted data and the evaluation scores of multiple educational institutions. Through the data input module (21), data analysis module (22), weight assignment module (23), and educational institution recommendation module (24), the control unit (20) stores evaluation scores for each of multiple educational institutions for each of multiple items including the student's disposition, personality, learning level, home location, and teacher preference. When a parent inputs data including the child's disposition, personality, learning level, home location, and teacher preference, the input data is analyzed using an artificial intelligence model. Based on the analysis results, weights are assigned to each item of the analyzed data, and information on recommended educational institutions is transmitted to the parent terminal (2) based on the similarity between the weighted data and the evaluation scores of multiple educational institutions. The c