• Journal for History of Mathematics
• /
• v.20 no.3
• /
• pp.91-104
• /
• 2007

In this paper we study the method to estimate weights of the elementary mathematics achievement factors to get reference index which improves elementary mathematics teaching. For it, we discuss not only a synopsis of AHP but also write out pairwise comparison matrix through statistical survey and estimate weights by eigenvector method.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.18 no.3
• /
• pp.92-98
• /
• 2010

The AHP methodology compares criteria, or alternatives with respect to a criterion, in a natural, pairwise mode. AHP has been applied in a wide variety of applications multi objective decision making being just one. If a group of expert with different aspect, they need some way to revise expert group. We proposed the concatenation of expert to survey the AHP pairwise question for multi-attribute decision making. In this paper, we suggest a way to revise the expert's priorities in hierarch using concept of different group opinion.

• The Journal of Information Systems
• /
• v.29 no.3
• /
• pp.237-251
• /
• 2020

Purpose The research was studied the hierarchical Hangul emotion index by organizing all the emotions which SNS users are thinking. As a preliminary study by the researcher, the English-based Plutchick (1980)'s emotional standard was reinterpreted in Korean, and a hashtag with implicit meaning on SNS was studied. To build a multidimensional emotion dictionary and classify three-dimensional emotions, an emotion seed was selected for the composition of seven emotion sets, and an emotion word dictionary was constructed by collecting SNS hashtags derived from each emotion seed. We also want to explore the priority of each Hangul emotion index. Design/methodology/approach In the process of transforming the matrix through the vector process of words constituting the sentence, weights were extracted using TF-IDF (Term Frequency Inverse Document Frequency), and the dimension reduction technique of the matrix in the emotion set was NMF (Nonnegative Matrix Factorization) algorithm. The emotional dimension was solved by using the characteristic value of the emotional word. The cosine distance algorithm was used to measure the distance between vectors by measuring the similarity of emotion words in the emotion set. Findings Customer needs analysis is a force to read changes in emotions, and Korean emotion word research is the customer's needs. In addition, the ranking of the emotion words within the emotion set will be a special criterion for reading the depth of the emotion. The sentiment index study of this research believes that by providing companies with effective information for emotional marketing, new business opportunities will be expanded and valued. In addition, if the emotion dictionary is eventually connected to the emotional DNA of the product, it will be possible to define the "emotional DNA", which is a set of emotions that the product should have.