• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.202-214
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• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.19-30
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• 2012

The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.247-260
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• 2003

To share and standardize information, especially in the database environments, MDR (Metadata Registry) can be used to integrate various heterogeneous databases within a particular domain. But due to the discrepancies of data element representation between organizations, global information integration is not so easy. And users who are searching integrated information on the Web have limitation to obtain schema information for the underlying source databases. To solve those problems, in this paper, we present a 3-layered Information Integration System (LI2S) based on MDRs and Ontology. The purpose of proposed architecture is to define information integration model, which combine both of the nature of MDRs standard specification and functionality of ontology for the concept and relation. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent information integration architecture. Ontology is used as for a role of semantic network from which it extracts concept from the user query and the establishment of relationship between MDRs for the data element. (MDR and Knowledge Base are used as for the solution of discrepancies of data element representation between MDRs. Based on this architectural concept, LI2S was designed and implemented.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.469-478
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• 2003

Internet information search engines using web robots visit servers conneted to the Internet periodically or non-periodically. They extract and classify data collected according to their own method and construct their database, which are the basis of web information search engines. There procedure are repeated very frequently on the Web. Many search engine sites operate this processing strategically to become popular interneet portal sites which provede users ways how to information on the web. Web search engine contacts to thousands of thousands web servers and maintains its existed databases and navigates to get data about newly connected web servers. But these jobs are decided and conducted by search engines. They run web robots to collect data from web servers without knowledge on the states of web servers. Each search engine issues lots of requests and receives responses from web servers. This is one cause to increase internet traffic on the web. If each web server notify web robots about summary on its public documents and then each web robot runs collecting operations using this summary to the corresponding documents on the web servers, the unnecessary internet traffic is eliminated and also the accuracy of data on search engines will become higher. And the processing overhead concerned with web related jobs on web servers and search engines will become lower. In this paper, a monitoring system on the web server is designed and implemented, which monitors states of documents on the web server and summarizes changes of modified documents and sends the summary information to web robots which want to get documents from the web server. And an efficient web robot on the web search engine is also designed and implemented, which uses the notified summary and gets corresponding documents from the web servers and extracts index and updates its databases.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.253-266
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• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

• Koreanishche Zeitschrift fur Deutsche Sprachwissenschaft
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• v.1
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• pp.313-348
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• 1999

이 논문은 독일어의 겹자음회피현상을 설명함에 있어 어휘음운론에서의 분석이 보이는 문제들을 지적하고, 이 문제들이 제약에 바탕을 둔 이론에서는 어떻게 해결될 수 있는가를 보인다. 제약들간의 상호작용에서 특히 중요한 역할을 하는 것이 단일형태실현제약 (Uniform Exponence)으로서, 이 제약을 통해 독일어 동사의 현재시제, 단수, 2인칭 형태와 3인칭형태에서 나타나는 겹자음회피현상이 동사의 어형변화표 (Verbparadigma)와 밀접한 관련이 있음을 알 수 있다. 이는 규칙들을 통해 2인칭과 3인칭의 올바른 형태를 각각 개별적으로 찾아내는 어휘음운론의 분석과는 근본적으로 다르다. 왜냐하면 어휘음운론의 분석에 따를 때, 예를 들어 3인칭 동사 arbeitet에서 Schwa 모음의 삽입은 겹자음회피를 위해 일어난다고 설명되지만 겹자음이 없음에도 불구하고 Schwa 모음이 마찬가지로 삽입되는 2인칭동사 arbeitest는 설명되지 않기 때문이다. 이런 분석에서는 2인칭 형태와 3인칭 형태가 서로 아무런 관련 없이 각기 따로 존재하게된다. 이에 반해 단일형태제약은 이 두개의 형태를 동시에 비교하므로, 동사 굴절형태에서 마치 불필요한 것으로 보이는 모음삽입이나 자음탈락의 원인에 대해 이론적인 근거를 제시할 수 있다. 즉 2인칭 형태와 3인칭 형태는 보다 상위의 제약들이 막지 않는 한 서로 최대한 비슷한 형태를 가지려고 한다. 이 논문은 겹자음 회피를 위한 수단으로서 모음삽입이나 자음탈락은 오로지 이를 통해 동사의 어형변화표가 좋아질 때만 가능하다는 것을 보여줌으로써 규칙이론이 포착하지 못하고 있는 중요한 일반화를 제시하고 있다. 단일형태 실현제약의 중요성은 접두사 in- 과 un- 이 어간과 결합할 때 보이는 대조를 통해서도 확인된다. 여기서도 어휘음운론의 다층어휘부 구조에 의한 설명이 갖는 문제점이 제약들간의 상호작용을 통해 해결될 수 있음을 알 수 있다.VII-1 및 VII-2공의 3600 m 하부층은 건성 가스 생성 단계에까지 도달한 것으로 나타났다. JDZ VII-1, VII-2 시추공의 3500 m 하위 구간의 올리고세 퇴적층에서 유기물 함량 및 수소 지수가 급격히 감소하는 것은 매몰 심도가 깊어지면서 유기물이 열 분해되어 이미 탄화수소를 생성한 것으로 해석된다. JDZ VII-1 및 VII-2 시추공의 가스징후 및 길소나이트 (gilsonite)는 탄화수소가 생성되어 이동한 흔적을 시사한다.을 해석할 수 있음을 보여주는 것으로 평가된다. 다만 PLAYMAKER2가 보다 신뢰할 만한 퇴적환경 해석을 위한 전문가 시스템으로 구축되기 위해서는 향후 많은 퇴적학 전문가들이 추가로 참여하여 기존 규칙들을 재검증하고 새로운 규칙들을 첨가함으로써 보디 세련된 지식베이스를 개발하여야 할 것으로 판단된다.이며 세 개의 산소가 이루는 평면에서 $1.68{\AA}$ 소다라이트내로 이동하여 위치한다. 32개의 $Tl^{+}$ 이온은 결정학적 자리 II에 존재하고 있으며 산소와의 결합거리를 $2.70(1){\AA}$을 유지하면서 큰 동공속으로 $1.48{\AA}$ 이동하여 위치한다. 약 18개의 $Tl^+$ 이온은 결정학적 자리III에, 또 다른 10개의 $Tl^+$ 이온은 결정학적 자리III'에 존재하고 골조 산소와 각각 $2.86(2){\AA},\;2.96(4){\AA}$의 결합거리를 이룬다.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.39-57
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• 2004

Many dairy producers periodically receive information about their bulk tank milk with reference to bulk tank somatic cell counts, standard plate counts, and preliminary incubation counts. This information, when collected over a period of time, in combination with bulk tank mastitis culture reports can become a significant knowledge base. Several guidelines have been proposed to interpret farm bulk tank milk bacterial counts. However many of the suggested interpretive criteria lack validation, and provide little insight to the interrelationship between different groups of bacteria found in bulk tank milk. Also the linguistic terms describing bulk tank milk quality or herd management status are rather vague or fuzzy such as excellent, good or unsatisfactory. The objective of this paper was to develop a set of fuzzy descriptors to evaluate bulk tank milk quality and herd's milking practice based on bulk tank milk microbiology test results. Thus, fuzzy logic based reasoning methodologies were developed based on fuzzy inference engine. Input parameters were bulk tank somatic cell counts, standard plate counts, preliminary incubation counts, laboratory pasteurization counts, non agalactiae-Streptococci and Streptococci like organisms, and Staphylococcus aureus. Based on the input data, bulk tank milk quality was classified as excellent, good, milk cooling problem, cleaning problem, environmental mastitis, or mixed with mastitis and cleaning problems. The results from fuzzy reasoning would provide a reference regarding a good management practice for milk producers, dairy health consultants, and veterinarians.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.207-217
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• 2010

It is taken a violent fall of the international stocks market that was an American Subprime Mortgage Situation. The loss rate of individual investor judged than foreigner and institution by bigger thing. Therefore, further scientific and mechanical investment is needed at the stock investment using Internet HTS. This dissertation is stocks profit rate analysis which uses individual engine foreigner Knowledge Base HTS at the Bear Period the Bear Wave Period the Bull Period the Bull Wave Period. Knowledge Based e-friend HTS was Installed. HTS does composite stock exchange index in actuality stock trading and engine's fund earning rate, yield that is abroad comparative analysis using trend line that is HTS tool, MACD, Bollinger Bands, Stochastic slow's function. Usually, each subjects suppose that deal 5 stocks, and comparative study of the profit(loss)rate of the down to earth falling rate and rising rate, by comparing the earning rate of 5 Small capital stocks with 5 medium capital stocks and 5 Large capital stocks during the bear period, the bear wave period, the bull period, the bull wave period has meaning at the making research of the financial IT field.