Jumong is a legendary figure in Korean mythology.He is depicted as a genius archer,a brilliant mind with horses,a god who rules the rivers and the sky.Jumong is a mythical character who is believed to be of divine des...Jumong is a legendary figure in Korean mythology.He is depicted as a genius archer,a brilliant mind with horses,a god who rules the rivers and the sky.Jumong is a mythical character who is believed to be of divine descent and to possess superhuman abilities that humans cannot match.The myth of Jumong is a very competitive content that can compete on a global scale.However,in order for it to be successful,it is necessary to be able to reinterpret our mythology to suit the times and reproduce it culturally.To this end,the realistic globalization of Korean classical literature should commence with the genre of Korean mythology.This paper presents the educational significance of the Jumong myth as a teaching-learning model,via STEAM(science,technology,engineering,arts,and mathematics),on the theme of Korean mythology.As we enter the era of artificial intelligence(AI)through the 4th Industrial Revolution,the most appropriate teaching and learning method,the convergence class,will provide an opportunity for students living in modern times to discover the cultural archetypes that allow them to recognise themselves as individuals and us as a collective,and to find the roots of the myth to positively renew their identity.Furthermore,it is my hope that they will rediscover and appreciate the representative work of Korean mythology,Gojomong,the eponymous story of Goguryeo.展开更多
When dealing with the ratings from users,traditional collaborative filtering algorithms do not consider the credibility of rating data,which affects the accuracy of similarity.To address this issue,the paper proposes ...When dealing with the ratings from users,traditional collaborative filtering algorithms do not consider the credibility of rating data,which affects the accuracy of similarity.To address this issue,the paper proposes an improved algorithm based on classification and user trust.It firstly classifies all the ratings by the categories of items.And then,for each category,it evaluates the trustworthy degree of each user on the category and imposes the degree on the ratings of the user.Finally,the algorithm explores the similarities between users,finds the nearest neighbors,and makes recommendations within each category.Simulations show that the improved algorithm outperforms the traditional collaborative filtering algorithms and enhances the accuracy of recommendation.展开更多
基金support of the Korea University of Education and Training Center for Convergence Education(2019-2022).
文摘Jumong is a legendary figure in Korean mythology.He is depicted as a genius archer,a brilliant mind with horses,a god who rules the rivers and the sky.Jumong is a mythical character who is believed to be of divine descent and to possess superhuman abilities that humans cannot match.The myth of Jumong is a very competitive content that can compete on a global scale.However,in order for it to be successful,it is necessary to be able to reinterpret our mythology to suit the times and reproduce it culturally.To this end,the realistic globalization of Korean classical literature should commence with the genre of Korean mythology.This paper presents the educational significance of the Jumong myth as a teaching-learning model,via STEAM(science,technology,engineering,arts,and mathematics),on the theme of Korean mythology.As we enter the era of artificial intelligence(AI)through the 4th Industrial Revolution,the most appropriate teaching and learning method,the convergence class,will provide an opportunity for students living in modern times to discover the cultural archetypes that allow them to recognise themselves as individuals and us as a collective,and to find the roots of the myth to positively renew their identity.Furthermore,it is my hope that they will rediscover and appreciate the representative work of Korean mythology,Gojomong,the eponymous story of Goguryeo.
基金supported by Phase 4,Software Engineering(Software Service Engineering)under Grant No.XXKZD1301
文摘When dealing with the ratings from users,traditional collaborative filtering algorithms do not consider the credibility of rating data,which affects the accuracy of similarity.To address this issue,the paper proposes an improved algorithm based on classification and user trust.It firstly classifies all the ratings by the categories of items.And then,for each category,it evaluates the trustworthy degree of each user on the category and imposes the degree on the ratings of the user.Finally,the algorithm explores the similarities between users,finds the nearest neighbors,and makes recommendations within each category.Simulations show that the improved algorithm outperforms the traditional collaborative filtering algorithms and enhances the accuracy of recommendation.
