This study focuses on reviewing the concepts, roles, meanings, and values ascribed to females and femininity as observable in Daesoon thought and in Feminist theory. Especially with regards to the process of achieving gender equality through the resolution of grievance for females in Daesoon thought, the study draws positive and desirable roles within this practice by specifically examining good deeds performed by females and practical roles that females play. By doing so, this study finds a way to go from the world of mutual contention to the world of resolving grievances that have arisen due to the oppression of yin and the encouragement of yang. First wave feminism can be summarized as the inclination for equality. In Daesoon thought concerning this and from standpoint of females, the most ideal image of woman is one of a female Perfected Being who is unified with Dao and has thereby achieved perfection of her humanity apart from gender. In the Later World (Hucheon), people can get results based on their hard work regardless of gender. The enlightenment of Dao is such that it is not important to distinguish between males and females. Both of them can be 'unified with dao'. Therefore, despite the similarity, the concepts of equality in first wave feminism and the resolution of grievance for women have differences in terms of their ideal vision of equality. The representative claim in second wave feminism is 'consideration' and, in this context, 'consideration' has pronounced feminine characteristics. In Daesoon thought, this sense of 'consideration' is related to the concept of 'Jamojijeong', a term that refers to motherly affection. However, it is not simply a virtue of females and mothers, but rather the value of 'Yin (pronounced in Sino-Korean as 'Eum')' called 'Eumdeok (hidden virtue)'. Jamojijeong means that people should behave in a modest way and this helps them achieve their aims. It is also closely related with 'femininity' in the sense of Eum. One of processes spreading it socially is to propagate virtue (Podeok) and if harmony is achieved through it, then 'right yin and right yang' emerge as the precondition by which Pyeong Do (Pacification of Tao) can be realized. Furthermore, because the aspect of Pyeong is a cosmic process, it has distinct differences from the social aims of feminism and the worldly aims of other numerous ideologies. In proceeding from the Former World (Seoncheon), an era of mutual contention, to the Later World, an era of mutual beneficence, it is essential to emphasize the connection between 'harmony (Hwa)' and 'propagating virtue' as the starting point from which the perspective of Daesoon thought aiming at the principle of 'Pyeong' and 'Hwa' emerges. Herein one can discover that the realization of Daesoon thought is based on the vitalization of the feminine value of 'Jamojijeong'.
Gangneung farm song is important for the ritualistic labortheatricals. Especially, in the theatrical process program, the songsof weeding, such as Haksan Odokkteggi and Ssadae, were alsoincluded to represent the agricultural ritualistic prayer for goodharvest. The use of Gangneung farm song is attractive in termsofthe circumstances. There is no chance of success as a plan simplyfor local events. As a comprehensive art, Gangneung farmsongshould simultaneously revitalize locality, representability andglobality. In this context, three directions are suggested dependingon the development progress. The second direction to the thirddirection are mainly oriented toward government-local authoritycentered support, but, in particular, the third direction should aimtobe an open archive in which the public and the contents prosumercan participate. In the production of the traditional content, OSMUmust be endlessly recreated and spread through 'diversity' and'interrelationships'. The contents utilization was discussed based on the transmissiondetails and analysis evidence of Gangneung Haksan Odokttegi. Thediversification of the way of performing farm song and the folk songs that can induce interest were proposed. Furthermore, basedon the fact that 12 songs classified into 8 work types, there-creation of the contents that focus on the playful aspect of theperforming arts was also proposed. In addition to suggestingthedesirable discourse of the performance groups, the experienceprogram development, education, public relations andcommunication reinforcement based on the narrating principlesoffarm songs, and the development and execution of farmsongprograms based on the tradition and the event demands wereproposed. While mentioning the necessity of value creation, thevitality of performing arts skills that put emotion, imagination, fun, sympathy, and etc. on the original form and the model of farmsongs should be supplemented to Gangneung Haksan Odokttegi. The independent transmission aspect of Gangneung Arirangisalso positive. There are difficulties of reduction of traditionalitydueto the designation, standardized transmission, lack of developmentof voluntary performances, and demonstration-centeredtransmission. Narrowly, we focused on the education andvitalization directions in terms of the capacity building of theconservation council itself. By embodying the essential value of theagricultural literature that farm songs possess, it can bringimpression of all worlds, all lives, communication and sharing, anddraw inspiration from the humanistic view of the world andemotion. The reconstitution of agricultural heritage, theconstruction of a storytelling linked with the concrete objects suchas Beomil National Preceptor, Gulsansa, FlagpoleSupport(Dangganjiju), Seokcheon, Hakbawi rock, and etc., andtheestablishment of fusion type farm song museum were proposed. In terms of culture industry, we requested active support fromtheinstitutions including local governments and various farmsongstorytelling creation projects.
Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used