• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.678-689
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• 2000

This paper describes an automatic summarization approach that constructs a summary by extracting sentences that are likely to represent the main theme of a document. As a way of selecting summary sentences, the system uses a model that takes into account lexical and statistical information obtained from a document corpus. As such, the system consists of two parts: the training part and the summarization part. The former processes sentences that have been manually tagged for summary sentences and extracts necessary statistical information of various kinds, and the latter uses the information to calculate the likelihood that a given sentence is to be included in the summary. There are at least three unique aspects of this research. First of all, the system uses a text component identification model to categorize sentences into one of the text components. This allows us to eliminate parts of text that are not likely to contain summary sentences. Second, although our statistically-based model stems from an existing one developed for English texts, it applies the framework to individual features separately and computes the final score for each sentence by combining the pieces of evidence using the Dempster-Shafer combination rule. Third, not only were new features introduced but also all the features were tested for their effectiveness in the summarization framework.

• Korean journal of communication and information
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• v.61
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• pp.159-179
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• 2013

This study aims to consider the criteria and signification of 'aging' constructed in media in Korean society that has entered aging society. For the purpose, this study analyzed KBS the representative TV health programs. According to the result, designs the measurable indexes of aging to rank the casts. And it emphasizes to the casts that cannot reach a certain level the support from medical experts or advanced medical technology. With such characteristics of individual text, this paper found the ideological codes of the health programs. They contrast the elderly who have achieved successful aging from those that have not. They define the aged who have not practiced self-management or medical control to prevent aging properly as failure and also make fun of them. They draw aging that was not regarded as some kind of disease in the past into the area of medicine. Besides, the medicalization of aging regarded as an object for treatment may come to strengthen the control of medical experts and also individualize social issues.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.127-132
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• 2016

Several methods have been proposed to apply artificial neural networks to text compression in the past. However, the networks and targets are both limited to the small size due to hardware capability in the past. Modern GPUs have much better calculation capability than CPUs in an order of magnitude now, even though CPUs have become faster. It becomes possible now to train greater and complex neural networks in a shorter time. This paper proposed a method to transform the distribution of original data with a probabilistic neural predictor. Experiments were performed on a feedforward neural network and a recurrent neural network with gated-recurrent units. The recurrent neural network model outperformed feedforward network in compression rate and prediction accuracy.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.711-716
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• 2014

With the gradual increase of interest in plagiarism and intelligent file content search, the demand for similarity measuring between two sentences is increasing. There is a lot of researches for sentence similarity measurement methods in various directions such as n-gram, edit-distance and LSA. However, these methods have their own advantages and disadvantages. In this paper, we propose a new sentence similarity measurement method approaching from another direction. The proposed method uses the set-based POI data search that improves search performance compared to the existing hard matching method when data includes the inverse, omission, insertion and revision of characters. Using this method, we are able to measure the similarity between two sentences more accurately and more quickly. We modified the data loading and text search algorithm of the set-based POI data search. We also added a word operation algorithm and a similarity measure between two sentences expressed as a percentage. From the experimental results, we observe that our sentence similarity measurement method shows better performance than n-gram and the set-based POI data search.

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.537-545
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• 2016

Demand for text arranged in a circular shape is increasing as devices with round display such as smart watches are now being actively released. Data visualization field is receiving a lot of attention as the era of big data evolves. However, current web standard does not support the drawing of circular text. Therefore, the objective of this study was to extend CSS3 specifications to have circular text layout in web documents. In addition, we implemented a preprocessor so that contents made with CSS3 extensions could be shown in existing browsers. To confirm the wide expression range of CSS3 extension, we prepared some sample contents and analyzed them.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.157-165
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• 2018

The purpose of this study is to investigate the effectiveness of general use of English literary works. It will be helpful for both general English learners and college students majoring English Education in ESL or EFL context. English literature is very useful pedagogical tool in the language class due to its unique valuable characteristics including authenticity, cultural and linguistic value, and personal enrichment, which impact on fostering English ability of EFL students. For this reason, it is unavoidable to develop a theory and practice regarding using English literature as an educational resource for college students in Korea. In this study several considerations will be discussed in terms of selection of the literary works to be applied for language learning purpose in the classrooms of universities in Korea. Such attentions will include fours skills of English such as reading, writing, listening and speaking. Finally, some effects and implications of using literary text as a pedagogical tool in the EFL language classrooms will be discussed.

• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.62-70
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• 2000

In usual language models(LMs), the probability has been estimated by selecting highly frequent words from a large text side database. However, in case of adopting LMs in a specific task, it is unnecessary to using the general method; constructing it from a large size tent, considering the various kinds of cost. In this paper, we propose a construction method of LMs using a small size text database in order to be used in specific tasks. The proposed method is efficient in increasing the low frequent words by applying same sentences iteratively, for it will robust the occurrence probability of words as well. We carried out continuous speech recognition(CSR) experiments on 200 sentences uttered by 3 speakers using LMs by iterative teaming(IL) in a air flight reservation task. The results indicated that the performance of CSR, using an IL applied LMs, shows an 20.4% increased recognition accuracy compared to those without it. This system, using the IL method, also shows an average of 13.4% higher recognition accuracy than the previous one, which uses context-free grammar(CFG), implying the effectiveness of it.

• Cartoon and Animation Studies
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• s.44
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• pp.285-306
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• 2016

With the increase use of smartphones, users can consume contents such as webtoon, webnovel and TV drama directly provided by the producers. In this Direct-to-Consumer era, webdrama services from the portal websites are increasing rapidly. Webdramas such as , , and can be analyzed in real time using responses such as unique users, likes, and comments. The analyses used in this research were Social Media Big Data Mining Method and Opinion Mining Method. Specific key words from webdrama can be extracted and viewers positive, neutral or negative emotion can be predicted from the words. The analyses of popular webdramas showed that the established K-Pop Idol member appearance and servicing portal site greatly influence the views, traffics, comments, and likes. Also, 'Mobile TV' proved the effectiveness as another platform other than television. Mobile targeted contents and robust business models still to be developed and identified. Overcoming these few tasks, Korea will be proven to be a webdrama content powerhouse.

• Journal of The Korean Association of Information Education
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• v.16 no.2
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• pp.255-263
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• 2012

Early algorithm education is very important in order to nurture excellent S/W developers in an information society. However a algorithm learning is a great challenge to elementary school students since understanding what a computer algorithm written in a static text format meant to do is difficult. It is expected that a student can easily visualize a algorithm through animations. In this study, we evaluate the pedagogical effectiveness of algorithm visualizations in teaching the fundamental data structures and algorithms in elementary schools. Thus we defined a new measure called 'Algorithm Visualization Factor(AVF)' and developed both text-oriented and animation-oriented PPTs of algorithm education elements, that is, Stack, Queue, Bubble Sort, Heap Sort, BDF, and DFS. We have conducted experiments and evaluations on diverse students groups. Extensive experiment results show that the average score of the student groups using animation-orirented PPT is greater(22%) than the one of the student groups using text-orirented PPT.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.