• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.101-104
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• 2002

본 문서에서는 사용자 적합성 피드백을 적용한 멀티미디어검색 기법을 제안한다. 적합성 피드백은 멀티미디어검색에 있어 사용자가 요구하는 정보를 반영할 수 있어 영상의 검색 효율을 높일 수 있다. 이 실험에서는 긍정적 피드백과 부정적 피드백을 함께 사용하였다. 실험결과, 적합성 피드백을 이용하면 적은 횟수의 반복검색으로 우수한 결과를 얻을 수 있음을 알 수 있다.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.548-566
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• 2013

The availability of technology and the abundance of experts in universities create an ample opportunity to provide a venue that allows a knowledge seeker to easily connect with and request advice from university experts. On the other hand, outsourcing provides opportunities and remains one of the emerging trends in organizations, and can very clearly observed in the Philippines. This paper describes the development of a reliable web-based approach to Knowledge Product Outsourcing (KPO) services in the Silliman Online University Learning system. The system is called an "e-Knowledge Box."It integrates Web 2.0 technologies and mechanisms, such as instant messaging, private messaging, document forwarding, video conferencing, online payments, net meetings, and social collaboration together into one system. Among the tools used are WAMP Server 2.0, PHP, BlabIM, Wordpress 3.0, Video Whisper, Red5, Adobe Dreamweaver CS4, and Virtual Box. The proposed system is integrated with the search engine in URLs, Web feeds, email links, social bookmarking, search engine sitemaps, and Web Analytics Direct Visitor Reports. The site demonstrates great web usability and has an excellent rating in functionality, language and content, online help and user guides, system and user feedback, consistency, and architectural and visual clarity. Likewise, the site was was rated as being very good for the following items: navigation navigation, user control, and error prevention and correction.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1615-1617
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• 2015

웹을 통한 데이터 공유에 대한 관심의 증가로 RDF 트리플 형태의 데이터가 폭발적으로 증가하고 있다. 대용량 RDF 데이터를 저장하고 빠른 SPARQL 질의 처리를 지원하는 트리플 저장소의 개발이 중요하다. 아파치 프로젝트 중 하나인 Jena-TDB는 가장 잘 알려진 오픈소스 트리플 저장소 중 하나로서 Jena 프레임워크 기반으로 구현됐다. 하지만 Jena-TDB 의 경우 단일 컴퓨터에서 작동하기 때문에 대용량 RDF 데이터를 다룰 수 없다는 문제점이 있다. 본 논문에서는 MongoDB를 활용한 Jena 프레임워크 기반의 트리플 저장소인 Jena-MongoDB를 제안한다. Jena 프레임워크를 사용했기 때문에 기존 Jena-TDB와 동일한 인터페이스로 사용할 수 있고 최신 표준 SPARQL 문법도 지원한다. 또한 MongoDB를 사용했기 때문에 분산환경에서도 작동할 수 있다. 대용량 LUBM 데이터셋에 대한 SPARQL 질의 처리 실험결과 Jena-MongoDB가 Jena-TDB 보다 빠른 질의 응답 속도를 보여줬다.

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.1-8
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• 2008

This study examined an instruction method for the improvement of information processing abilities in elementary school students. Current elementary students are required to develop information processing abilities to create new knowledge from this information flooded age; however, there is a shortage of instruction strategies for these information processing abilities. This research proposes a method for information processing ability based Barrow's problem-based learning model, and was applied to real elementary students. Students developed an improved ability to create new knowledge and to present relationships with information through the process of problem solving. This study performed experimental research by comparing pre- and post-tests for twenty-three fifth grade elementary students over the course of eight months. This study produced a remarkable improvement in information selection, information reliability, information classification, information analysis, information comparison, and information internalization.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.59-60
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• 2013

Infobutton is an important concept from long time in use and much has been done with respect to its standardization and context supplementation. The concept is to create contextual links to information resources from within the information systems usually health information systems. The need which has been realized by the authors of this paper is the augmentation of Infobuttons from the level of only information links to the level of knowledge links. The authors proposed the concept of knowledge links named as "Knowledgebuttons" which complements the concept Infobuttons. It adds further capabilities of getting knowledge to the users instead of just connectivity to information resources. The better representation of the information retrieved with Infobuttons is the first and foundation step to achieve the goal of getting knowledge. This paper discusses about the concept and applicability of Knowledgebuttons in health information systems. It is envisioned that this concept will add to the overall quality of patient care. Both physicians and patients can benefit from this technique as per their needs. Physicians can help in patient diagnosis and treatment critical decisions while patients can educate them to know more about their health conditions by studying the right knowledge at right time. Knowledgebuttons are able to create a true learning environment for the users while using health information systems.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.161-171
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• 1999

Query language has been widely used as a convenient tool to obtain information from a database. However, users demand more intelligent query processing systems that can understand the intent of an imprecise query and provide additional useful information as well as exact answers. This paper introduces a meta-database and presents a query processing mechanism that supports a variety of intelligent queries in a consistent and integrated way. The meta-database extracts data abstraction knowledge from an underlying database on the basis of a multilevel knowledge representation framework KAH. In cooperation with the underlying database, the meta-database supports four types of intelligent queries that provide approximately or conceptually equal answers as well as exact ones.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.31-35
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• 2015

The IoE service process for maximizing efficiency of information storage and utilization classifies in step five which are interconnected, data collection, storage, organize, analyze, and share. Two key processing elements are store and forward. Keeping the useful knowledge in safe location is "store processing", and utilization of stored useful knowledge is defined as "forward processing" during the IoE service process. Where, past experience data can tell us how to prepare the future utilization. That is, past experience is organized store processing, and preparation for the future is shared forward processing through analysis. To maximize the utilization and storage of information effectively, the various methodologies for IoE service process propose and research in this paper.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Asia pacific journal of information systems
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• v.14 no.2
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• pp.115-130
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• 2004

This paper proposes how to build an expert profile database in KMS, which provides the information of expertise that each expert possesses in the organization. To manage tacit knowledge in a knowledge management system, recent researches in this field have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise so that users can contact them for help. In this paper, we develop a framework to automate expert classification using a text categorization technique called Vector Space Model, through which an expert database composed of all the compiled profile information is built. This approach minimizes the maintenance cost of manual expert profiling while eliminating the possibility of incorrectness and obsolescence resulted from subjective manual processing. Also, we define the structure of expertise so that we can implement the expert classification framework to build an expert database in KMS. The developed prototype system, "Knowledge Portal for Researchers in Science and Technology," is introduced to show the applicability of the proposed framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1396-1412
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• 2023

Conversation modeling is an important and challenging task in the field of natural language processing because it is a key component promoting the development of automated humanmachine conversation. Most recent research concerning conversation modeling focuses only on the current utterance (considered as the current question) to generate a response, and thus fails to capture the conversation's logic from its beginning. Some studies concatenate the current question with previous conversation sentences and use it as input for response generation. Another approach is to use an encoder to store all previous utterances. Each time a new question is encountered, the encoder is updated and used to generate the response. Our approach in this paper differs from previous studies in that we explicitly separate the encoding of the question from the encoding of its context. This results in different encoding models for the question and the context, capturing the specificity of each. In this way, we have access to the entire context when generating the response. To this end, we propose a deep neural network-based model, called the Context Model, to encode previous utterances' information and combine it with the current question. This approach satisfies the need for context information while keeping the different roles of the current question and its context separate while generating a response. We investigate two approaches for representing the context: Long short-term memory and Convolutional neural network. Experiments show that our Context Model outperforms a baseline model on both ConvAI2 Dataset and a collected dataset of conversational English.