• Journal of the Korean Chemical Society
• /
• v.57 no.3
• /
• pp.398-404
• /
• 2013

In this study, the analogies in the chemistry domain of middle school science textbooks developed under the 2007 revised National Curriculum were analyzed. A total of 235 analogies were found in 27 middle school science textbooks analysed, which means that one analogy per 10 pages was used on average. The number of analogies found in each textbook considerably varied depending on both publishing company and chemistry domain. Functional analogies, verbal and pictorial analogies, analogies with abstract target and concrete analog, enriched analogies, everyday contexts analogies, student-centered analogies, and analogies with low systematicity were frequently used. On presenting the analogies in the textbooks, the term analogy and description about the limitations of the analogies were rarely mentioned. In comparison with the analogies in the science textbooks developed under the 7th National Curriculum, the frequency of analogies per page was increased. There were positive changes in the aspects of representation, extent of mapping and artificiality. No differences, however, were found in the patterns of the other aspects.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.11
• /
• pp.8030-8036
• /
• 2015

This study is to explore the effect of figure and color informations on assessing expressed emotions in drawings. A pilot study was conducted to explore emotional responses to achromatic drawing stimuli. The main experiment explored emotional responses to chromatic drawing stimuli. Each experiment has a number of 50, 56 participants separately, and responses included joy, depression, and anger according to appraisal-potency-activity dimensions. As results, achromatic drawing stimuli with their texture and rhythm produced specific emotions in high rates. Moreover, response rates of specific emotions were lower when colors added, or emotional responses were changed with colors. The significance of this study can be found in the fact that it dealt with colors combined with shape, unlike the previous studies, and that the experiments were conducted under more controlled conditions in terms of stimulus presentation and response management.

• Journal of KIISE:Software and Applications
• /
• v.27 no.4
• /
• pp.448-462
• /
• 2000

Coordinate constructions in natural language pose a number of difficulties to natural language processing units, due to the increased complexity of syntactic analysis, the syntactic ambiguity of the involved lexical items, and the apparent deletion of predicates in various places. In this paper, we address the syntactic characteristics of the coordinate constructions in Korean from the viewpoint of constructing a competence grammar, and present a version of combinatory categorial grammar for the analysis of coordinate constructions in Korean. We also show how to utilize a unified lexicon in the proposed grammar formalism in deriving the sentential semantics and associated information structures as well, in order to capture the discourse functions of coordinate constructions in Korean. The presented analysis conforms to the common wisdom that coordinate constructions are utilized in language not simply to reduce multiple sentences to a single sentence, but also to convey the information of contrast. Finally, we provide an analysis of sample corpora for the frequency of coordinate constructions in Korean and discuss some problematic cases.

• School Mathematics
• /
• v.16 no.2
• /
• pp.303-315
• /
• 2014

Even though the variety of expressions are dealt with in Korean elementary mathematics, the systematization of the subject matter of expressions is still insufficient. This is basically due to the failure of revealing clearly the identity of expressions dealt with in elementary mathematics. In this paper, as a groundwork to improve this situation, after the classification of signs as elements constituting expressions, in a position to consider elementary mathematics using transitional signs such as ${\square}$, ${\triangle}$, etc and words or phrases in expressions, expressions were defined and classified based on that classification of signs. It can be presented as the conclusion that the following four judgements which helps to promote the systematization of the subject matter of expressions are possible through this definition and classifications. First, by clarifying the identity of the expressions, any mathematical clauses or sentences can be determined whether those are expressions or not. Second, Forms of expressions can be identified. Third, the subject matter of expressions can be identified systematically. Fourth, the hierarchy of the subject matter of expressions can be identified.

• Proceedings of the Korea Contents Association Conference
• /
• 2008.05a
• /
• pp.43-48
• /
• 2008

And this study intends to discuss especially the one using emotional filter among various information processing methods. The existing music recommendation service on the web has a weak point that it makes the user feel bored by recommending songs only with similar feeling of the same genre, because music is classified by tune, melody, atmosphere and genre before recommendation. The service using emotion filter, suggested in this study, recommends the song and lyrics appropriate to the current emotional state of the user by abstracting emotional words that could reflect the sensitivity of human and then search the words within lyrics to match in order to overcome the weak point of the existing service. This study starts where the current emotional status for the user is being input. As for the range to choose, there are the seven representatives of emotion which are, love, separation, joy, sorrow-gloom, happiness-lonesome, and anger. As the service receives input of user's emotion, it matches the emotional words appropriate for the emotion input with the lyrics, and ranks the lyrics in the order of priority, so that it recommends the song and it lyrics to the user.

• Journal of Information Technology and Architecture
• /
• v.9 no.3
• /
• pp.333-344
• /
• 2012

This paper proposes a system which recommends movies using information from social network services containing personal interest and taste. Method for establishing data is as follows. The system gathers movies' information from web sites and user's information from social network services such as Facebook and twitter. The data from social network services is categorized into six steps of emotion level for more accurate processing following users' emotional states. Gathered data will be established into vector space model which is ideal for analyzing and deducing the information with the system which is suggested in this paper. The existing similarity measurement method for movie recommendation is presentation of vector information about emotion level and similarity measuring method on the coordinates using Cosine measure. The deducing method suggested in this paper is two-phase arithmetic operation as follows. First, using general cosine measurement, the system establishes movies list. Second, using similarity measurement, system decides recommendable movie list by vector operation from the coordinates. After Comparative Experimental Study on the previous recommendation systems and new one, it turned out the new system from this study is more helpful than existing systems.

• Journal of KIISE:Computing Practices and Letters
• /
• v.10 no.6
• /
• pp.529-536
• /
• 2004

The main idea of this paper is to combine position information in sentence and query type classification to make the documents ranking to query more accessible. First, the use of conceptual graphs for the representation of document contents In information retrieval is discussed. The method is based on well-known strategies of text comparison, such as Dice Coefficient, with position-based weighted term. Second, we introduce a method for learning query type classification that improves the ability to retrieve answers to questions from Question Answering system. Proposed methods employ naive bayes classification in machine learning fields. And, we used a collection of approximately 30,000 question-answer pairs for training, obtained from Frequently Asked Question(FAQ) files on various subjects. The evaluation on a set of queries from international TREC-9 question answering track shows that the method with machine learning outperforms the underline other systems in TREC-9 (0.29 for mean reciprocal rank and 55.1% for precision).

• The Korean Journal of Archival Studies
• /
• no.33
• /
• pp.3-37
• /
• 2012

This article will examine the community archive movement, exploring its roots, its variety and the present developments. It will identify limitations of archival principles in managing community records, particularly on the many gaps and insufficiencies for dealing with historically marginalized groups in the contemporary archival infrastructure. Introducing paradigm shifts in the understanding of the role of archives, the author examines new challenges and opportunities of archival community on community archives.

• Database Research
• /
• v.34 no.3
• /
• pp.3-13
• /
• 2018

Text classification is one of the text mining technologies that classifies a given textual document into its appropriate categories and is used in various fields such as spam email detection, news classification, question answering, emotional analysis, and chat bot. In general, the text classification system utilizes machine learning algorithms, and among a number of algorithms, naïve Bayes and support vector machine, which are suitable for text data, are known to have reasonable performance. Recently, with the development of deep learning technology, several researches on applying deep neural networks such as recurrent neural networks (RNN) and convolutional neural networks (CNN) have been introduced to improve the performance of text classification system. However, the current text classification techniques have not yet reached the perfect level of text classification. This paper focuses on the fact that the text data is expressed as a vector only with the word dimensions, which impairs the semantic information inherent in the text, and proposes a neural network architecture based upon the semantic tensor space model.

• Cross-Cultural Studies
• /
• v.42
• /
• pp.241-260
• /
• 2016

The purpose of this article is to represent the types of advertising in the modern Russian language as 'Play of Words' (игра слов). The causal reason for this phenomenon is studied from the result of certain characteristics of advertising. The definition and characteristics of the language of the advertisement are analyzed in achieving the goal, as these factors reveal how language is used to maximize the effectiveness of the advertising. Academic research is needed in the collaborative fields of linguistics, psychology, economics, sociology, marketing, literature, art, and music. Modern advertisement is mixed with semiotic objects that consist of display, sound, and texts. While this study is not complete, the acknowledgement of the phenomenon 'Play of Words' between the creators of advertising and the consumer is undeniable. On one hand, advertising is recognized by linguists as the main factor that destroys the literary language. It represents the distortion of a standard language norm, as opposed to formal linguistic means used in advertising. In this research, we pay attention to the frequent use of foreign language borrowings and incorrect representation of foreign words, slang and jargon, that occur in misspelled usage of literary norms. The features that are revealed in this article are helpful to understand the purpose of advertising.