• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.124-129
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• 2006

This parer presents a method of ranking translation word selection for Korean verbs based on lexical knowledge contained in a bilingual Korean-English dictionary and WordNet that are easily obtainable knowledge resources. We focus on deciding which translation of the target word is the most appropriate using the measure of semantic relatedness through the 45 extended relations between possible translations of target word and some indicative clue words that play a role of predicate-arguments in source language text. In order to reduce the weight of application of possibly unwanted senses, we rank the possible word senses for each translation word by measuring semantic similarity between the translation word and its near synonyms. We report an average accuracy of $51\%$ with ten Korean ambiguous verbs. The evaluation suggests that our approach outperforms the default baseline performance and previous works.

• Korean Journal of Environmental Biology
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• v.35 no.3
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• pp.329-334
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• 2017

A marine ulvalean species (Chlorophyta) was collected from Imgok, which is located on the eastern coast of Korea. This species is morphologically characterized by distromatic, filiform to strap compressed or tubular thallus. Many branches were found near the base, but lacked proliferations. Cells were longitudinally aligned in the younger part of the branch and were disordered in the older part of the branch. A cap-like parietal chloroplast with one or two pyrenoids was contained in each cell. In a phylogenetic tree based on ITS and rbcL sequences, this species was nested in the same clade as Ulva torta and U. clathratioides from Australia, but formed a sister clade to U. torta from Japan. However, the genetic divergence between them was included in an intraspecific variation range within Ulva. This finding suggests that U. clathratioides should be reduced to a synonym of U. torta. Accordingly, the Korean alga was identified as U. torta based on the morphological and molecular data. This investigation is the first record of U. torta in the Korean marine algal flora.

• ALGAE
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• v.31 no.2
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• pp.105-115
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• 2016

The genus Pterosiphonia includes twenty-one currently described species of red algae that occur in temperate to tropical regions of the Atlantic and Pacific Oceans. Pterosiphonia spinifera was originally described as Polysiphonia spinifera from Peru and later transferred to Pterosiphonia. Pterosiphonia spinifera has been reported from Peru as Pterosiphonia pennata, which was originally described from the Mediterranean Sea. Recently, Pterosiphonia arenosa was described based on specimens of P. pennata from Korea. We collected P. spinifera along the coast of Peru and P. arenosa near the type locality in Korea. We compared them with the isotype specimens of P. arenosa using both morphological and molecular data. Our morphological observations and our phylogenetic analysis of rbcL sequences demonstrate that P. spinifera and P. arenosa are conspecific and indicate that P. arenosa is a later synonym of P. spinifera. Our study confirms the wide occurrence of P. spinifera in the western and eastern Pacific Ocean.

• Journal of the korean academy of Pediatric Dentistry
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• v.37 no.4
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• pp.532-536
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• 2010

Hidden caries is a subtype of the occlusal pit and fissure caries type and is defined as a dentinal caries lesion near the occlusal surface of the tooth seen on a radiograph. In visual examination, the occlusal enamel is seen intact or is minimally perforated. Covert caries, Occlult caries or Fluoride syndrome are used as synonym. The percentage of occlusal dentin lesions that are clinically undetected ranges from 1.4-50%. Little is known about the mechanisms involved in the development of hidden caries. But it is thought that extensive use of topical fluoride or the special bacteriological profile has been a major factor. This case report is about detection and treatment of hidden caries of two children who visited the department of pediatric dentistry, Yonsei University Dental Hospital. The color of caries dentin found in hidden caries lesion is lighter than cavity forming caries, which makes it more difficult to detect caries by visual examination. Therefore diagnosis of hidden caries is often accomplished after clinical sign is recognized by patients. The use of advanced caries detection aids such as Diagnodent.. with periodic radiographic examination is seemed to be helpful for early detection of hidden caries.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.433-442
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• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.