• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제12권3호
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• pp.65-74
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• 2017

There have been questions how entrepreneurs think, act and why individuals become entrepreneurs. The trait-based explanation of entrepreneurial activities has been main stream. However, the trait-based theory has been criticized because it assumes that entrepreneurial traits are inherited, stable and enduring over time. This research accepts the cognitive theory to see how entrepreneurs learn or accept others' values, how entrepreneurial perceptions of opportunity impact entrepreneurial actions and how individuals acquire the social legitimation of the formation of entrepreneurial activities. In order to capture the attitudes, activities and motivations of people who are involved in entrepreneurial activities, the author uses the GEM Korea 2016 data. The data from the Global Entrepreneurship Monitor(GEM) has been well known for the data to capture individuals early-stage entrepreneurial activities. This paper used the sample from the APS(Adult Population Survey) of the GEM which was completed by a representative sample of two thousand adults in Korea by the qualified survey vendor, with strict procedures and oversight by the GEM central data team. The hypotheses are tested with logit regression analysis to estimate the probability of the influence of perceptual variables such as individual perception in social learning, the opportunity recognition in the environment, and social legitimation in the entrepreneurial activities. Based on the results, individuals tend to have high entrepreneurial activities if individuals have high self-efficacy. Also, the existence of role models around the entrepreneurs encourages the individuals involve in entrepreneurial activities more however the perception of opportunity in the environment is not strongly associated with entrepreneurial activities. The media exposure of successful entrepreneurs is more important than others' perception of entrepreneurs on the desirable career option or respect from communities. This paper can contribute to the cognitive processes, particular perception about oneself, as well as perception which is impacted by a community or a society.

• Journal of Intelligence and Information Systems
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• 제20권3호
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of Intelligence and Information Systems
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• 제25권2호
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• pp.141-166
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• 2019

Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

• Journal of The Korean Association For Science Education
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• 제37권2호
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• pp.359-370
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• 2017

The purpose of this study is to explore the changes caused by using smart technology in school science inquiry. For this, we investigated 12 elementary school teachers' perceptions by using an open-ended questionnaire, group discussions, classroom discussions, and participant interviews. The results of this study indicate that the introduction of technology into classroom inquiry can open up the various possibilities and can cause additional burdens as well. First, teachers explained that smart technology can expand the opportunities to observe natural phenomena such as constellations and changing phases of the moon. However, some teachers insisted that, sometimes, learning how to use new devices disrupts students' concentration on the inquiry process itself. Second, teachers introduced the way of digital measurement using smart phone sensors in inquiry activities. They said that digital measurement is useful in terms of the reduction of errors and of the simplicity to measure. However, other teachers insisted that using new devices in classroom inquiry can entail additional variables and confuse the students' focus of inquiry. Communication about inquiry process can also be improved by using digital media. However, some teachers emphasized that they always talked about both the purpose of using SNS and online etiquettes with their students before using SNS. Based on these results, we discussed the necessity of additional analysis on the various ways of using digital devices depending on teachers' perceptions, the types of digital competency required in science inquiry using smart technology, and the features of norms shaped in inquiry activities using smart technology.

• Journal of Science Education
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• 제33권1호
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• pp.111-121
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• 2009

The purpose of this research is to survey elementary pre-service teachers' in understand the legal Units, focusing on seven basic unit such a 'm', 'm2', 'L', 'kg', 'K', 'cd', 's'. This study specifically investigates whether the students understand the legal units. The subjects were 1096 students from the University of Education in Jinju, Gyeongnam. Data was collected through a questionnaire which was designed by this research and checked by authority, and the frequency and percentage of responses to each question were obtained and analysed. The survey was the legal units on interesting, using the experience of confusing and understanding of elementary pre-service teachers. The Korea Government is regulating using traditional measures such as 'pyeong' or 'don' in commercial transactions change to adopt the metric system for as a subsidiary the first of July, 2007. The interesting of the legal units dose not exceed a positive answer to the question 52.1%. Their were answered that the experience of the confused of 60.1% in the life. How to do efforts for the settle down of the legal units that answered broadcasting>in class>a campaign>study and training by an academic year in oder. Findings show regardless of academic year, gender and from the department of liberal arts or the science department all the students knew very well that 'm' '$m^2$', 'L', 'kg' are included in the legal units, compared to the others low percentage of 'K', 'cd' and 's' the legal units. In case of time(s), women has correct answered 2.7 times than man. In case of academic year, except for the third-year students was not to exceed 50%. In case of from the department of liberal arts or the science department contrary to one's expectations increase of 50% or more correct answer while half the students scored in science. The elementary pre-service teachers are seems to thinking separate the legal units with their in university life. Also elementary pre-service teachers are the lack of interest on society. Their should be for settle down of the legal units through learning to class in university, newspapers, strengthen publicity activities of broadcast media's further more by maintenance efforts of the government.

• Journal of Nutrition and Health
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• 제55권1호
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• pp.21-35
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• 2022

The recommended meal composition allows the general people to organize meals using the number of intakes of foods from each of six food groups (grains, meat·fish·eggs·beans, vegetables, fruits, milk·dairy products and oils·sugars) to meet Dietary Reference Intakes for Koreans (KDRIs) without calculating complex nutritional values. Through an integrated analysis of data from the 6th to 7th Korean National Health and Nutrition Examination Surveys (2013-2018), representative foods for each food group were selected, and the amounts of representative foods per person were derived based on energy. Based on the EER by age and gender from the KDRIs, a total of 12 kinds of diets were suggested by differentiating meal compositions by age (aged 1-2, 3-5, 6-11, 12-18, 19-64, 65-74 and ≥ 75 years) and gender. The 2020 Food Balance Wheel included the 6th food group of oils and sugars to raise public awareness and avoid confusion in the practical utilization of the model by industries or individuals in reducing the consistent increasing intakes of oils and sugars. To promote the everyday use of the Food Balance Wheel and recommended meal compositions among the general public, the poster of the Food Balance Wheel was created in five languages (Korean, English, Japanese, Vietnamese and Chinese) along with card news. A survey was conducted to provide a basis for categorizing nutritional problems by life cycles and developing customized web-based messages to the public. Based on survey results two types of card news were produced for the general public and youth. Additionally, the educational program was developed through a series of processes, such as prioritization of educational topics, setting educational goals for each stage, creation of a detailed educational system chart and teaching-learning plans for the development of educational materials and media.

• Journal of Distribution Research
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• 제15권4호
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• pp.61-85
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• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown