• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• Journal of Information Management
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• v.40 no.1
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• pp.217-234
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• 2009

In computer-based virtual lab, a bioscience researcher who wants to obtain bio information first uses a biodiversity-related database to retrieve information on species, ecology and distribution of an organism. The researcher also needs to access gene/protein databases such as GenBank or PDB to find information on the organism's genetic sequence and protein structure. Furthermore, the researcher should search for academic papers containing the information on the organism so that his research is based on comprehensive and accurate information. This series of activities often undermines research efficiency as it takes a lot of time and causes inconvenience on the part of researchers. To solve such inconvenience, we analyzed various methods for integrated search and chosen schema integration. In addition, we analyzed each databases and extracted metadata for designing schema integration. This paper introduces a biological information retrieval system(BIRS) using schema integration and it's interface that will increase research efficiency for bioscience.

• ETRI Journal
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• v.24 no.1
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• pp.23-30
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• 2002

MPEG-7 Visual Standard specifies a set of descriptors that can be used to measure similarity in images or video. Among them, the Edge Histogram Descriptor describes edge distribution with a histogram based on local edge distribution in an image. Since the Edge Histogram Descriptor recommended for the MPEG-7 standard represents only local edge distribution in the image, the matching performance for image retrieval may not be satisfactory. This paper proposes the use of global and semi-local edge histograms generated directly from the local histogram bins to increase the matching performance. Then, the global, semi-global, and local histograms of images are combined to measure the image similarity and are compared with the MPEG-7 descriptor of the local-only histogram. Since we exploit the absolute location of the edge in the image as well as its global composition, the proposed matching method can retrieve semantically similar images. Experiments on MPEG-7 test images show that the proposed method yields better retrieval performance by an amount of 0.04 in ANMRR, which shows a significant difference in visual inspection.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.122-129
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• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.93-100
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• 2001

This paper illustrates a prototyping framework of the documentation-standards retrieval system via the data mining approach for enhancing software development quality. We first present an approach for designing a retrieval algorithm based on data mining, with the three basic technologies of machine learning, statistics and database management, applied to this system to speed up the searching time and increase the fitness. This approach derives from the observation that data mining can discover unsuspected relationships among elements in large databases. This observation suggests that data mining can be used to elicit new knowledge about the design of a subject system and that it can be applied to large legacy systems for efficiency. Finally, software development quality will be improved at the same time when the project managers retrieving for the documentation standards.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.79-87
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• 2007

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using exist ing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.

• International Journal of Contents
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• v.5 no.3
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• pp.40-49
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• 2009

While numerous studies have suggested the significance of uncertainty during the process of information-seeking, less research has investigated user uncertainty in the actual search process using a real system. This study investigated user perceptions of uncertainty in the process of the selection of information retrieval system in the real information-seeking process. Considering the role of commercial Web search engines as supplementary tools for traditional bibliographic databases in academic research environments, this study analyzed the selection behavior of scholarly researchers, who use such search tools for their academic study. The researchers were limited to the discipline of science in order to understand user perceptions in this field. The findings revealed various dimensions, types, and incidents of uncertainty. Variations appeared in different incidents of uncertainty relating to the unique characteristics of the subjects' information-seeking context. The identification of three principal origins of uncertainty based on the different types of uncertainty generated implications to improve information systems and services.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.273-277
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• 2007

Ubiquitous computing environment accelerates the advent of the IT Ecosystem. In the coming generation, a massive number of ubiquitous devices and services are converged into an ultra-large-scale system. In this context, high degrees of complexity and organization change the paradigm of knowledge and its management levels. The objective of this paper is to explore the Knowledge Management Systems in view of demands in ultra-large-scale systems. We introduce motivation for Next-Generation (NG) usage and their upcoming requirements. The possible applications will be discussed, and summary of different techniques are conducted. The tools and techniques that allow KMS to operate as "Vital Success Enabler" to achieve organizational benefits will be examined. Potential future directions for research are highlighted: these include advances in knowledge capture, storage / retrieval and sharing techniques, in particular with the surrounding role of information technology.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.137-140
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• 1996

In order to solve the specific problems in system, the implementing of knowledge base suitable to the system architecture has to be expressed and leads to the resoning of the new facts. Not only the simple knowledge based on the bivalent logic but also the representation and acqusition of knowledge related to vague and imprecise linguistic variable is necessary to the knowledge in the real world,i.e the knowledge of which facts and rules are composed. In this point of view, this survey implements the inference and retrieval of the fuzzy linguistic variables so that it can process the ambiguous information which appears the imprecision of the linguistic boundary.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.