• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.441-443
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• 2021

Sentence or text similarity is a measure of the degree of similarity between two sentences. Techniques for measuring text similarity include Jacquard similarity, cosine similarity, Euclidean similarity, and Manhattan similarity. Currently, the cosine similarity technique is most often used, but since this is an analysis according to the occurrence or frequency of a word in a sentence, the analysis on the semantic relationship is insufficient. Therefore, we try to improve the efficiency of analysis on the similarity of sentences by giving relations between words using ontology and including semantic similarity when extracting words that are commonly included in two sentences.

• The Transactions of the Korea Information Processing Society
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• 제5권5호
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• pp.1185-1203
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• 1998

When the class is added of deleted in object-oriented system, restructuring of class hierarchy is needed which enables new relationship with classes. But existing system requires much additional analysis costs because it is difficult to know the meaning between parent class and child class. This paper presents the updates method based on semantic modification through new relationship classification method. This method measures the similarity of classes and based on it's relationship, this method restructures class hierarchy by classifying not-equality, part-of, equality, inclusion, subset relation. This method can minimize the probability of meaning error for classes when the class hierarchy is changed. Also this enhances the reusability and understandability through various graphic and text processing.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.1137-1144
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• 2009

Creativity, the ability to produce through imaginative skill, is pursued by all designers. However, originality does not refer to absolute novelty. In this age, information is shared and disseminated. Creation of works is an activity to re-establish all shared information and reorganize relationship among things. Therefore, a new design is a product of reorganization rather than originality. Moreover, designers can generate ideas different from each other because they individually espouse different system of knowledge. From such perspective, a very important task of designers is to explore methods of expanding design thinking that can enhance the ability to new connection among things in the process of assimilation and modification. The task can be carried out by identifying characteristics and limits of their unique system of knowledge. Therefore, it is necessary to seek methods of expanding design thinking for efficient cognitive activities. In explaining human knowledge, this study applied semantic network, a method used in cognitive science for creating structure, and the method of expanding design thought was proposed by corresponding method of design conceptualization. By organizing, categorizing, and flexibly combining and modifying the methods of design thinking conceptualization and expansion generated by this study, strengths of each method were enhanced and limits of each method were overcome to enable more effective design thinking. In this study, the method of expansion was used when connecting of nodes cannot be sustained after using each method of conceptualization. By avoiding unique method of thinking through diversification and vitalization of conditional points, efficient design thinking was achieved. The value of this study lies in the fact that the proposed method of expanding thinking using the mechanism of network enhances the ability to establish new connections in the process of assimilation and modification.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 2부
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• pp.30-35
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• 2008

The purpose of this study is to analyze and define user's emotional satisfaction factors to the PC OS GUI image. The study is to investigate the relationship between PC OS GUI Image and Sensitive Vocabula교 based on user's emotional preference. 47 user preferred sensitive words are collected by the initial survey. Through the similarity test, 47 words are narrowed down to 20 comprehend words. The semantic differential methods is used in the final survey with 5 step questionnaire. From this process, user preferred the GUI design that is vocabularized as Clear, Easy, Safety, Stability. Additionally, the result shows that the image of Clear is related to Safety and the image of Easy is related to Stability. The result of the study could be used in design PC OS GUI as base data.

• The Journal of the Korea Contents Association
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• 제11권3호
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• pp.73-83
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• 2011

The question answering system shows the answers that are input by other users for user's question. In spite of many researches to try to enhance the satisfaction level of answers for user question, there is a essential limitation. So, the question answering system provides users with the method of recommendation of another questions that can satisfy user's intention with high probability as an auxiliary function. The method using the fuzzy relational product operator was proposed for recommending the questions that can includes largely the contents of the user's question. The fuzzy relational product operator is composed of the Kleene-Dienes operator to measure the implication degree by contents between two questions. However, Kleene-Dienes operator is not fit to be the right operator for finding a question answers pair that semantically includes a user question, because it was not designed for the purpose of finding the degree of semantic inclusion between two documents. We present a novel fuzzy implication operator that is designed for the purpose of finding question answer pairs by considering implication relation. The new operator calculates a degree that the question semantically implies the other question. We show the experimental results that the probability that users are satisfied with the searched results is increased when the proposed operator is used for recommending of question answering system.

• Korean Journal of Cognitive Science
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• 제30권1호
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• pp.31-50
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• 2019

The present study is designed to investigate the effect of perceptive, emotional and semantic distinctiveness on retrieval-induced forgetting(RIF). Experiment 1 was designed to construct a category and category list for RIF experimental paradigm and to investigate the effects of perceptual distinctness on retrieval-induced forgetting. It was used for the list consisting of the six categories and six words in each category list. In controlled conditions, all the stimuli were presented in black and Gothic. In contrast, perceptual distinctiveness conditions, half of the category list were presented in red and Gungseoche. RIF was observed in all conditions. Experiment 2 was designed to investigate the effects of semantic and emotional distinctiveness on retrieval-induced forgetting. In neutral conditions, adjectives related to items were added. In the emotional distinctiveness condition, half of the items in the category were manipulated in such a way as to add the negative adjectives. In the semantic distinctiveness condition, half of the items in the category were manipulated in such a way as to add the inappropriate adjective. As a result, RIF occurred in the neutral condition, but RIF did not occur in both the emotional discrimination condition and the semantic discrimination. These results suggest the possibility that the RIF will not occur when the distinctiveness occurs within a categorical relationship.

• Journal of Intelligence and Information Systems
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• 제28권1호
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of Educational Research in Mathematics
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• 제25권4호
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• pp.525-547
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• 2015

This study analyzed the written texts of textbook and the teacher's discourse explaining 'the relationship between quadratic functions and quadratic equations' in the 9th grade high school mathematics class. Data consisted of the lecture recordings and the textbooks were analyzed based on the Halliday's systemic functional linguistics. According to the results, the written texts of the textbook used lexico-grammatical strategies such as generalization using hyponomy of meanings, mathematical objectification through nominalization and materialization of meaning through change in themes to compose mathematical concepts. The textbook generalized from an example in the description of formulating mathematical concepts, and in this process the organizational interactions of discourse-semantic level and lexico-grammartical level appeared. On the other hand, the teacher's doscourse appeared the change in transitivity and the addition of the reasons and the process. Also the teacher used explanation process of formulating the relationship between quadratic functions and quadratic equations. The linguistic characteristics of the teacher were linguistic implication and omission of lexemes due to contextual ommission. And there was no use of structural lexico-grammatical resources that influence the discourse-semantic level. This results provide a new framework for analyzing mathematical discourse, and suggest the lexico-grammatical strategies that can be used to explain mathematical concepts by teachers in math classrooms.

• The Research Journal of the Costume Culture
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• 제12권3호
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• pp.369-378
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• 2004

The objectives of this study were to measure the preference and purchase intention on Korean traditional motifs and to investigate the relationship among preference, purchase intention, and sensibility. The subjects consisted of 217 male and 351 female US undergraduate students. The experimental materials used in this study were 48 stimuli and a questionnaire, composed of 7-point semantic differential scales of 17 bi-polar adjectives. The data were analyzed by ANOVA, Duncan's multiple range test, Regression, and t-test. The major findings were as follows; First, interpretation type and application object had significant effects on the preference, while category and interpretation type had significant effects on the purchase intension. The application of Korean traditional motifs for pattern design was preferred to their application for clothing design. Decorative type was found to be more related to the preference and purchase intention than the other interpretation types of realistic, stylized and abstract types. The purchase intention on crain motif was lower than the other categories of lotus and cloud motifs. Second, in overall, the preference on Korean traditional motifs was higher than purchase intention. Third, the preference and purchase intention were affected mainly by 'Quality' image, a component of sensibility, followed by 'Cheerfulness' image, but not affected by 'Simplicity' and 'Modernity' image.

• KIEAE Journal
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• 제13권4호
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• pp.87-94
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• 2013

This Study, as a Eco-Friendly Design Process of Office for sustainable design, aims to develop a sustainable design process by letting the designers easily approach the concept of Eco-Friendly Design Process and applying this to Eco-Friendly Design Process when the designers perform design. Through a review on simulation, a research was made on the seriousness of environmental problems and control that was caused by design, Environmentally friendly design, sustainability, and sustainable design's background and definition were studied. In order to develop a Eco-Friendly Design Process, an existing review from Building Energy Simulation that proposed about energy environmentally friendly design element and sustainable design element's semantic similarities were restructured as sustainable design element comparative analysis. Restructured sustainable design elements and the relationship between sustainable design elements and the relationship of each product developmental process levels were analyzed. Finally, through clustering, sustainable design guideline were developed. This Eco-Friendly Design Process is expected to be applied to as one of the methods in solving the global environmental issues in design practice.