• The Journal of Korean Association of Computer Education
• /
• v.9 no.3
• /
• pp.121-128
• /
• 2006

This study suggested the new e-learning systems based on agent to provide an adaptable learning. In Semantic Web environment, to develop an ontology and an intelligent agent is essential for an adaptable e-learning systems. Especially, to develop a reasoning engine using analysis of learning content and learners' information can offer an effective e-learning system. Therefore, we developed an applying model to an adaptable e-learning systems and the various ontologies for Semantic Web environment. Moreover, we analyzed and developed ontologies within the framework of learning domain, a learner and interface. Further, we implemented an intelligent e-learning for applying an agent's reasoning. Through this system proposed, we suggested the new e-learning systems model for Semantic Web environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.645-646
• /
• 2018

Recently, the concept of machine learning has been introduced as a decision making method through data processing. Machine learning uses the results of running based on existing data as a means of decision making. The data generated by the development of technology is vast. This data is called big data. It is important to extract the necessary data from these data. In this paper, we propose a method for extracting related data for constructing an ontology through machine learning. The results of machine learning can be given a relationship from a semantic perspective. it can be added to the ontology to support relationships depending on the needs of the application.

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

• Journal of Digital Convergence
• /
• v.3 no.1
• /
• pp.183-194
• /
• 2005

This study is aimed at building up an Ontology to solve the discrepancy of terminologies between teachers and students by showing, through Ontology, the knowledge for diagnosis of underachieving students. Also this study makes it possible to infer the diagnosis based on information of these underachieving students. In addition, while a general Underachieving Students diagnosis system shows special diagnosis, this Ontology system helps users obtain correct concepts through this knowledge based system, and suggest building an Ontology to extend unclear conceptual knowledge to clearer ones.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.04a
• /
• pp.1058-1061
• /
• 2010

시맨틱 웹 서비스 기술의 성공을 보장하기 위해서는 품질 좋은 온톨로지의 사용이 필수적이다. 하지만 온톨로지 사용의 중요성에도 불구하고 현재 웹 서비스를 위한 온톨로지는 거의 존재하지 않으며 이들의 구축도 쉬운 일이 아니다. 이러한 문제는 오늘날 웹 서비스의 확산과 발전을 가로막는 큰 저해요인이 되고 있다. 본 논문에서는 웹 서비스를 개발할 때 자동 생성되는 WSDL 문서만 가지고 항목 간 숨어있는 시맨틱 정보를 찾아내어 온톨로지를 자동 구축하고, 이를 활용한 (반)자동화된 웹 서비스 발견 및 조합 시스템을 구현하는 것이다.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.10
• /
• pp.137-143
• /
• 2012

The learners using learning content through the smart devices can access to the Internet from anytime and anywhere. However, with the rapid increase of learning content on the Web, it will be time-consuming for learners to find contents they really want to and need to study. Therefore, e-learning systems should not only provide flexible content delivery, but support adaptive harmonizing fusion content. The harmonizing fusion content it is a very important in fusion e-learning service. The representative method to provide synchronization between fusion content is a provide absolute time value between of the contents. However, this method is occurs a problem transferring time delay. Also, to enter an absolute time value for the duration of the each content is several problems arise. In this paper introduces a new smart e-smart service support the harmonizing media based technology to create synchronized learning presentation.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.5
• /
• pp.133-141
• /
• 2008

Social Web is turning current Web into social platform for knowing people and sharing information. This paper takes major social tagging systems as examples, namely delicious, flickr and youtube, to analyze the social phenomena in the Social Web in order to identify the way of mediating and linking social data. A simple Tag Ontology (TO) is proposed to integrate different social tagging data and mediate and link with other related social metadata. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tag ontology is also suggested as an applying field.

• The KIPS Transactions:PartD
• /
• v.12D no.4 s.100
• /
• pp.627-636
• /
• 2005

The Intelligent Web Service is proposed for the purpose of automatic discovery, invocation, composition, inter-operation, execution monitoring and recovery web service through the Semantic Web and the Agent technology. To accomplish this Intelligent Web Service, the Ontology is a necessity for reasoning and processing the knowledge by the computer. However, creating service ontology, for the intelligent web service, has two problems not only consuming a lot of time and cost depended on heuristic of service developer, but also being hard to be mapping completely between service and service ontology. Moreover, the markup language to describe the service ontology is currently hard to be learned by the service developer In a short time. This paper proposes the efficient way of designing and creating the service ontology using MDA methodology. This proposed solution reuses the creating model in terms of desiEninE and constructing Web Service Model using UML based on MDA. After converting the Platform-Independent Web Service Model to the dependent model of OWL-S which is a Service Ontology description language, it converts to OWL-S Service Ontology using XMI. This proposed solution has profits, oneis able to be easily constructed the Service Ontology by Service Developers, the other is enable to be created the both service and Service Ontology from one model. Moreover, it can be effective to reduce the time and cost as creating Service Ontology automatically from a model, and calmly dealt with a change of outer environment like as the platform change. This paper cites an instance for the validity of designing Web Service model and creating the Service Ontology, and validates whether the created Service Ontology is valid or not.

• Journal of Digital Convergence
• /
• v.10 no.6
• /
• pp.275-281
• /
• 2012

This research proposes the method to develop the recommendation system of automobile parts using task ontology technology. The proposed intelligent recommendation system is designed to learn the assembly process of automobile parts and the automobile parts are composed by ontology method for the recommendation of the parts. Using hierarchical taxonomy based on is-a relationship, the relationship between each part that makes up automotive engine was set. Each part has each different weighted value according to the knowledge of automobile experts. The weighted value is created by the number of selection that the users of the automobile recommendation system select while using the system and the final value calculated by the multiplication of the weighted value, which is recorded within the system. As a result, the users can easily identify which factor in which part is important by the output in the order of the priority. The intelligent recommendation system for automobile parts is a system to inform of the assembly, the usage and the importance of automobile parts without any specialized knowledge by expressing the parts that are closely related with the applicable parts when selecting any part on the basis of the generated data for the automobile parts that are difficult to access by users.

• Journal of The Korean Association of Information Education
• /
• v.9 no.2
• /
• pp.257-270
• /
• 2005

Researchers of humane studies including philosophy acquire knowledge from understanding of their texts. They spent a lot time and efforts to retrieve, read and understand many texts relevant to their research fields using a metadata-based text retrieval system. In this paper, we develop a philosophy ontology that enables researchers to retrieve knowledge in the content of texts of philosophy. Our philosophy ontology includes concepts and their hierarchical and associative relationships defined by philosophy researchers. We propose a methodology for constructing text-based ontology comprised of three phases and fourteen steps. This methodology may be used to construct another ontologies for learning. Also, we introduce a case study for applying our philosophy ontology to acquire and interchange knowledge of philosophy between a professor and students during philosophy classes.