• Korean Journal of Oriental Medicine
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• v.16 no.1
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• pp.69-84
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• 2010

It is the well-known truth that processing of raw information is needed to a certain extent during information search. Especially for Oriental Medical information, it becomes much clearer that even more complex processing is necessary. As a means of reducing such complexity, this study suggests a way to understand effectively the organic relationships among information found on the interface. In this process, 'knowledge-based archaeological' method has been used. A new concept of interface observed by this research is the study of a system which contains realistically considered knowledge-based archaeological and historical specificity. These models are organized so that search results could be materialized in different tree-structured interface models, which can help one understand the relationships among wanted search results at one glance and confirm the details of those results via mouse click. Strength of the vertical tree structure resides in its capability of suggesting its users clear historical relationship between separate Oriental medical information. The horizontal tree structure enables deeper understanding of sectional interrelationship of searched information. The strength of the prescription tree structure is that it helps one understand the lineage of prescriptions, as Oriental medicinal treatment is often summarized into changes in prescriptions.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2786-2796
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• 1998

Extraction of interesting and general knowledge from large spatial database is an important task in the development of geographical information system and knowledge-base systems. In this paper, we propose a spatial data mining system using generalization method; In this system, we extend an existing generalization mining and design a rulebase to support deriving new spatial knowledge. For this purpose, we propose an interleaved method which integrates spatial data dominated and nonspatial data dominated mining and construct a rulebase to extract topological relationship between spatial objects.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.171-183
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• 2020

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.716-730
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• 2017

In this paper, we propose a transliteration approach based on semantic information (i.e., language origin and gender) which are automatically learnt from the person name, aiming to transliterate the person name of Uyghur into Chinese. The proposed approach integrates semantic scores (i.e., performance on language origin and gender detection) with general transliteration model and generates the semantic knowledge-based model which can produce the best candidate transliteration results. In the experiment, we use the datasets which contain the person names of different language origins: Uyghur and Chinese. The results show that the proposed semantic transliteration model substantially outperforms the general transliteration model and greatly improves the mean reciprocal rank (MRR) performance on two datasets, as well as aids in developing more efficient transliteration for named entities.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.55-66
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• 2023

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

• Journal of Korean Library and Information Science Society
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• v.31 no.2
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• pp.63-91
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• 2000

In ths study, I proposed the need for strengthening the information analysis function of research library whch is in charge of knowledge control in a company based on knowledge management. In the operating steps of information management for a company, 1 studed about providmg analyzed dormation at the level of a professional in various forms through intranet within a company after processing and analyzing the collected raw lnformation to make customized lnformation according to the need of each group, rather than passively providing information as required by users. By establishmg the senior decision-making person within the company as the core user in contrast with information s e ~ c e spr ovided in large libraries, ths will give us a new position as lnformation manager, who can accomplish tlie corporate goal. Also, I proposed the details for becoming a pioneer in knowledge management system.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.65-73
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• 2010

This study offered lexical knowledge acquisition model of unsupervised learning method in order to overcome limitation of lexical knowledge hand building manual of supervised learning method for research of natural language processing. The offered model obtains the lexical knowledge from the lexical entry which was given by inputting through the process of vectorization, clustering, lexical knowledge acquisition automatically. In the process of obtaining the lexical knowledge acquisition of model, some parts of lexical knowledge dictionary which changes in the number of lexical knowledge and characteristics of lexical knowledge appeared by parameter changes were shown. The experimental results show that is possibility of automatic building of Machine-readable dictionary, because observed to the number of lexical class information cluster collected constant. also building of lexical ditionary including left-morphosyntactic information and right-morphosyntactic information is reflected korean characteristic.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11b
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• pp.1269-1272
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• 2002

현재 세계적인 이동통신 업체들은 대부분 XHTML Basic 을 수용하여 새로운 브라우저들은 WAP 프로토콜을 배제하고 TCP/IP 기반의 통신을 지원하는 경향을 나타내고 있다. 본 논문에서는 이러한 기술 추세를 반영하여 WAP 2.0 을 지원하는 PalmOS 용 XHTML 브라우저를 개발하였다. 본 브라우저의 특성은 이식성을 높이면서 휴대용 단말기의 자원 제약을 극복하기 위하여 이미지 변환 프락시를 활용하는 방식을 채택한 점이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.47-50
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• 2004

본 논문은 대량의 데이터를 처리하는 전염병에 관한 역학조사에 대한 과정을 KDD(Knowledge Discovery in Database)와 데이터마이닝 기법을 이용해서 의료 전문인들의 지식을 데이터베이스화하여 데이터 선정, 정제, 보강, 예측과 빠른 데이터 검출을 하도록 하였다. 그리고 각 바이러스의 동향은 데이터마이닝을 활용하므로 일부분만의 데이터를 산출하지 않고 전체적인 동향을 산출, 예측하도록 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.503-504
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• 2024

미래사회는 데이터 활용이 곧 경쟁력으로 이를 해결하기 위한 방안으로 이슈 기술에 대한 IP(지적 재산) 정보를 수집하여 키워드와 특허분류를 이용하여 클러스터링한 결과물을 정보시스템으로 구축하는 지식플랫폼을 체계화하는 연구이다. 연구 대상은 바이오화학 산업으로 한정하고 성장성, 산업성, 영향력, 융합성을 적용하여 후보군 물질명을 도출, 관련된 특허정보를 클러스터링하는 지식플랫폼을 타 산업분야에서도 적용할 수 있도록 확장성을 고려하여 설계하였다.