• Journal of the Korean Society for information Management
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• v.25 no.1
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• pp.19-41
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• 2008

Cue words and phrases of critical sentences, Paradigms knowing the critical information between sentences, Rules extracting the sentences contained critical information and producing the critical sentences were made to construct the critical abstract of scholar journals in the web environment. The ontology aided to accomplish above works were designed, to manage and operate the cue words and phrases in documents and the symptoms related to Purpose, Method, Result, and Conclusion sentences. The results of performance test remarked to improve the advancement of extraction and production rules and the reinforcement of ontology's relationship.

• Cross-Cultural Studies
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• v.19
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• pp.389-409
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• 2010

Chinese is a topic-prominent language, so when we learn Chinese we should know the discourse function of the Chinese language. Most of the Korean student think Chinese sentences should appear in the order of S-V-O and they always make mistakes when they use Chinese. I think Korean is very similar with Chinese in the discourse function. Hence, in this paper, I try to find a method of teaching Chinese topic sentence. It does so by comparing Chinese with Korean in the light of discourse function. I think when Korean student know how to use Korean topic sentence to explain the discourse functions of the Chinese language, they will not make similar mistakes. With this understanding in mind, chapter 2 tries to show various topic sentences to prove that 'topic' is very important in Chinese sentences. This is why we say Chinese is a topic-prominent language. In chapter 3, I analysis the sentences that students made, and highlight the reasons why they made mistake. The result lies in the reason whereby they always think Chinese should appear in the order of S-V-O. They do not understand why some sentences appear in the order of O-(S)V or S-O-V. It show that they do not know what is topic sentence and do not know how to make topic sentences. Sometime I have them translate them into Korean, but they also make Korean sentences like in the order of Chinese S-V-O. Therefore, I think, under this circumstance, to let them to translate and to speak in Korean in topic sentence, get some feelings about Chinese topic sentences, and tell and make Chinese topic sentences are naturally critical in their training.

• Journal of the Korean earth science society
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• v.21 no.4
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• pp.469-478
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• 2000

The abstracts written in Korean presented at the Fall Meeting of the Korean Earth Science Society held at the Kangwon National University in October, 1999 were reviewed. They are dotted with foreign expressions and obscure wordings as well as difficult expressions and very long sentences. The foreign expressions are those originated from Japanese, English, and Chinese expressions and words. Several suggestions are made to increase the ability to write good abstracts and articles in Korean on the earth sciences. They include reading many books on natural sciences for general readers, writing sentences not exceeding 20 words, critical reading by professor or colleagues, and open mind to accept their criticisms. The authors should pay attention not to commit various errors shown in Table 2 in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.51-55
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• 2001

With the rapid growth of the World Wide Web and electronic information services, information is becoming available on-Line at an incredible rate. One result is the oft-decried information overload. No one has time to read everything, yet we often have to make critical decisions based on what we are able to assimilate. The technology of automatic text summarization is becoming indispensable for dealing with this problem. Text summarization is the process of distilling the most important information from a source to produce an abridged version for a particular user or task. Information retrieval(IR) is the task of searching a set of documents for some query-relevant documents. On the other hand, text summarization is considered to be the task of searching a document, a set of sentences, for some topic-relevant sentences. In this paper, we show that document information, that is more reliable and suitable for query, using document length normalization of which is gained through information retrieval . Experimental results of this system in newspaper articles show that document length normalization method superior to other methods use query itself.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.549-561
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• 2022

In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

• Korean Journal of Cognitive Science
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• v.17 no.2
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• pp.75-102
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• 2006

Three experiments were conducted using a verification task to examine good and poor readers' generation of causal inferences(with because sentences) and contrastive inferences(with although sentences). The unfamiliar, critical verification statement was either explicitly mentioned or was implied. In Experiment 1, both good and poor readers responded accurately to the critical statement, suggesting that both groups had the linguistic knowledge necessary to the required inferences. Differences were found, however, in the groups' verification latencies. Poor, but not good, readers responded faster to explicit than to implicit verification statements for both because and although sentences. In Experiment 2, poor readers were induced to generate causal inferences for the because experimental sentences by including fillers that were apparently counterfactual unless a causal inference was made. In Experiment 3, poor readers were induced to generate contrastive inferences for the although sentences by including fillers that could only be resolved by making a contrastive inference. Verification latencies for the critical statements showed that poor readers made causal inferences in Experiment 2 and contrastive inferences in Experiment 3 doting comprehension. These results were discussed in terms of context effect: Specific encoding operations performed on anomaly backgrounded in another passage would form part of the context that guides the ongoing activity in processing potentially relevant subsequent text.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.303-310
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• 2011

In this study, we employ CPM-GOMS analysis for explaining physical and cognitive processes and for quantitatively predicting when users are typing Korean text messages on mobile phones using both hands. First, we observe the behaviors of 10 subjects, when the subjects enter keypads with both hands. Then, basing upon MHP, we categorize the behaviors into perceptual, cognitive, motor operators, and then we analyze those operators. After that, we use the critical paths to model two task sentences. Also, we used Fitts' law method which was applied many times to predict text entering time on mobile phone to compare with the results of our CPM-GOMS model. We followed Lee's (2008) method that is well suited for text entry task using both hands and calculate total task time for each task sentences. For the sake of comparison between the actual data and the results predicted from our CPM-GOMS model, we empirically tested 10 subjects and concluded that there were no significant differences between the predicted values and the actual data. With the CPM-GOMS model, we can observe the human information processes composed on the physical and cognitive processes. Also we verified that the CPM-GOMS model can be well applied to predict the users' performance when they input text messages on mobile phones using both hands by comparing the predicted total task time with the real execution time.

• Journal of Korean Critical Care Nursing
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• v.11 no.1
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• pp.1-14
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• 2018

Purpose : As the intensive care unit (ICU) survival rate increases, interest in the lives of ICU survivors has also been increasing. The purpose of this study was to identify the sentiment of ICU survivors. Method : The author analyzed the quotations from previous qualitative studies related to ICU survivors; a total of 1,074 sentences comprising 429 quotations from 25 relevant studies were analyzed. A word cloud created in the R program was utilized to identify the most frequent adjectives used, and sentiment and emotional scores were calculated using the Artificial Intelligence (AI) program. Results : The 10 adjectives that appeared the most in the quotations were 'difficult', 'different', 'normal', 'able', 'hard', 'bad', 'ill', 'better', 'weak', and 'afraid', in order of decreasing occurrence. The mean sentiment score was negative ($-.31{\pm}.23$), and the three emotions with the highest score were 'sadness'($.52{\pm}.13$), 'joy'($.35{\pm}.22$), and 'fear'($.30{\pm}.25$). Conclusion : The natural language processing of AI used in this study is a relatively new method. As such, it is necessary to refine the methodology through repeated research in various nursing fields. In addition, further studies on nursing interventions that improve the coherency of ICU memory of survivors and familial support for the ICU survivors are needed.

• International Journal of Contents
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• v.10 no.4
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• pp.30-37
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• 2014

The current study was conducted to examine the temporal and spatial activation sequences related to morphosyntactic, semantic and orthographic-lexical sentences, focusing on the morphological-orthographic and lexical-semantic deviation processes in Korean language processing. The Event-related Potentials (ERPs) of 15 healthy students were adopted to explore the processing of head-final critical words in a sentential plausibility task. Specifically, it was examined whether the ERP-pattern to orthographic-lexical violation might show linear precedence over other processes, or the presence of additivity across combined processing components. For the morphosyntactic violation, fronto-central LAN followed by P600 was found, while semantic violation elicited N400, as expected. Activation of P600 was distributed in the left frontal and central sites, while N400 appeared even in frontal sites other than the centro-parietal areas. Most importantly, the orthographic-lexical violation process revealed by earlier N2 with fronto-central activity was shown to be complexes of morphological and semantic functions from the same critical word. The present study suggests that there is a linear precedence over the morphological deviation and its lexical semantic processing based on the immediate possibility of lexical information, followed by sentential semantics. Finally, late syntactic integration processes were completed, showing different topographic activation in order of importance of ongoing sentential information.