• Journal of the Korean Society for Library and Information Science
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• v.39 no.4
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• pp.139-161
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• 2005

This study aims to suggest a strategic alliance between libraries and publishers in Korea. When it considers the linear distribution channel of current publications and the entity and a butterfly effect of knowledge communication crisis, the publishers as production agency and the library as consuming subject must search a strategic cooperative plans. In order to achieve this goal, the study analysed the four issues(fixed book prices, library infrastructure, book and library supply policy of government, legal deposit system) which is important.

• Science of Emotion and Sensibility
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• v.4 no.2
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• pp.1-13
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• 2001

Emotion-Specific Physiology may still remain to bean elusive entity even to many of the proponents and seekers, but an ever-growing body of experimental evidence sheds much brighter prospects for the future researches in that direction. Once such Emotion-Physiology pairs are identified, there exist a high hope that some Sense-Friendly Features that are causally related, or highly correlated, to each pair may be identifiable in the nature or man-made objects. On the premise that certain emotions, if and when engendered by a consumer good, may be conducive to an urge “to own or to identify oneself with the product”, presented here is a model of Sensory Engineering that is oriented objectively towards identifying the Emotion-Specific Physiology in order to have the Sense-Friendly Features reproduced in product designs. Relevant and complementary concepts and some suggested procedures in implementing the proposed model are offered.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.458-460
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• 2023

가공식품이라는 특정 도메인에서는 기존 검색엔진에서 많이 활용되는 BM25 만을 가지고 최저가 검색하는 데는 어려움이 있다. 본 논문에서는 BM25 외에도 검색의 정확성을 높이기 위해 HuggingFace 에 공개되어 있는 KoELECTRA 를 활용하여 개체명 인식(Named Entity Recognition 과 이진 분류모델(Binary Classification)을 Fine-tuning 하고 BM25 와 연계하여 구축한 검색시스템을 제안한다. 기존의 BM25 대비 성능 평가를 통해 효과를 검증하였다.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.1
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• pp.1-5
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• 2023

Littoral cell angiomas are rare vascular tumors of the spleen. Because of their rarity, unclear etiopathogenesis, and association with other malignancies, these tumors can pose diagnostic and therapeutic challenges. Due to paucity of published literature on this entity often limited to case reports, relevant data on this topic were procured and synthesized with the aid of a comprehensive Medline search in addition to oncologic, pathologic, radiologic, and surgical literature review on littoral cell angiomas. This article provides an in-depth review into postulated etiopathogenesis, pathology, clinical manifestations, associated malignancies, and prognostic features of littoral cell angiomas.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Digital Contents Society
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• v.11 no.3
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• pp.375-383
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• 2010

In developing question-answering (QA) systems, it is hard to analyze natural language questions syntactically and semantically and to find exact answers to given query questions. In order to avoid these difficulties, we propose a new style of question-answering system that automatically generate natural language queries and can allow to search queries fit for given keywords. The key idea behind generating natural queries is that after significant sentences within text documents are applied to the named entity recognition technique, we can generate a natural query (interrogative sentence) for each named entity (such as person, location, and time). The natural query is divided into two types: simple type and sentence structure type. With the large database of question-answer pairs, the system can easily obtain natural queries and their corresponding answers for given keywords. The most important issue is how to generate meaningful queries which can present unambiguous answers. To this end, we propose two principles to decide which declarative sentences can be the sources of natural queries and a pattern-based method for generating meaningful queries from the selected sentences.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.35-42
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• 2013

The purpose of this research is to systematize safety management for practical application through analysis and review of several safety standards currently in force among the statutes and rules regarding various safety accidents. Accordingly, the safety standard systems of Japan, US, and Germany were examined and a KOSAM entity relationship diagram (ERD) was drawn based on the ontology system. The ERD consists of the safety standard scope, safety management statute, safety management standard, safety management subjects, causes of safety accidents, and safety management organization entities. Next, each entity was assigned a code and finally a KOSAM safety management condition search screen was designed based on the ERD. This research is expected to bring an overall improvement in safety standard management and operation through safety standard DB construction and the execution of safety management system development.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.321-343
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• 2016

This study aimed to design a semi-automatic web-based pilot system 1) to build a Korean novel geo-name, 2) to update the database using automatic geo-name extraction for a scalable database, and 3) to retrieve/visualize the usage of an old geo-name on the map. In particular, the problem of extracting novel geo-names, which are currently obsolete, is difficult to solve because obtaining a corpus used for training dataset is burden. To build a corpus for training data, an admin tool, HTML crawler and parser in Python, crawled geo-names and usages from a vocabulary dictionary for Korean New Novel enough to train a named entity tagger for extracting even novel geo-names not shown up in a training corpus. By means of a training corpus and an automatic extraction tool, the geo-name database was made scalable. In addition, the system can visualize the geo-name on the map. The work of study also designed, implemented the prototype and empirically verified the validity of the pilot system. Lastly, items to be improved have also been addressed.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.179-186
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• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Archives of Plastic Surgery
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• v.50 no.6
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• pp.550-556
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• 2023

Blunt breast trauma occurs in 2% of blunt chest injuries. This study aimed to evaluate the evidence on breast reconstruction after blunt trauma associated with the use of a seat belt. Also, we describe the first case of breast reconstruction using the Ribeiro technique. In November 2022, a systematic search of MEDLINE, EMBASE, and Google Scholar databases was conducted. The literature was screened independently by two reviewers, and the data was extracted. Our search terms included breast, mammoplasty, blunt injury, and seat belts. In addition, we present the case of a woman with a left breast deformity and her reconstruction using the inferior Ribeiro flap technique. Six articles were included. All included studies were published between 2010 and 2021. The studies recruited seven patients. According to the Teo and Song classification, seven class 2b cases were reported. In five cases a breast reduction was performed in the deformed breast with different types of pedicles (three superomedial flaps, one lower flap, one superior flap). Only one case presented complications. The case here presented was a type 2b breast deformity in which the lower Ribeiro pedicle was used successfully without complications during follow-up. Until now there has been no consensus on reconstructive treatment due to the rarity of this entity. However, we must consider surgical treatment individually for each patient. We believe that the Ribeiro technique is a feasible and safe alternative in the treatment of posttraumatic breast deformities, offering very good long-term results.