• Journal of KIISE
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• v.45 no.2
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• pp.113-125
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• 2018

Recently, with the advent of the Big Data era, we have gained the capability of acquiring vast amounts of knowledge from various fields. The collected knowledge is expressed by well-formed formula and in particular, OWL, a standard language of ontology, is a typical form of well-formed formula. The symbolic reasoning is actively being studied using large amounts of ontology data for extracting intrinsic information. However, most studies of this reasoning support the restricted rule expression based on Description Logic and they have limited applicability to the real world. Moreover, knowledge management for inaccurate information is required, since knowledge inferred from the wrong information will also generate more incorrect information based on the dependencies between the inference rules. Therefore, this paper suggests that the SWAT, knowledge management system should be combined with the SWRL (Semantic Web Rule Language) reasoning based on ATMS (Assumption-based Truth Maintenance System). Moreover, this system was constructed by combining with SWRL reasoning and ATMS for managing large ontology data based on the distributed In-memory framework. Based on this, the ATMS monitoring system allows users to easily detect and correct wrong knowledge. We used the LUBM (Lehigh University Benchmark) dataset for evaluating the suggested method which is managing the knowledge through the retraction of the wrong SWRL inference data on large data.

• Journal of Environmental Impact Assessment
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• v.27 no.1
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• pp.92-104
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• 2018

The loss of biodiversity has become a global issue. In order to cope with this problem, national biodiversity strategies and action plan (NBSAP) at national level as well as local biodiversity strategies and action plan (LBSAP) at local level have been established in many countries. In this study, we analyzed 8 domestic LBSAPs and 41 foreign LBSAPs through semantic network analysis to investigate the characteristics of domestic and foreign LBSAPs. The results showed that conservation and management were the most used keywords in both domestic and foreign LBSAPs but the ranking of other keywords used in vision, goal, strategy, and action plan sector was different. Thus, it has been found that there is a difference between domestic and foreign practical approaches to conservation and management of biodiversity. Results of the network analysis showed that the domestic network has a more detailed distributed network, while the foreign network has a more comprehensive and integrally configured dense network. These differences may be due to differences of threats to biodiversity, problem recognition, or differences in local circumstances. These results are expected to help establish LBSAP in other region or to assess the local roles to achieve the strategic goals of the Convention on Biological Diversity.

• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.401-407
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• 2013

In parallel with the development of ship equipment, bridge systems have been improved, but marine accidents due to human error have not been reduced. Recently, research in nautical bridge equipment has focused on suitable ergonomic designs in order to reduce these errors due to human factors. In a bridge of a ship, there are numerous auditory signals that deliver important information clearly to the sailors. However, only a few studies have been conducted related to the human recognition of these auditory signals. There are three types of auditory signals: voice alarms, abstract sounds, and auditory icons. This study was conducted in order to design more appropriate auditory icons using a sensibility evaluation method. The auditory icons were rated to have five warning situations (engine failure, fire, steering failure, low power, and collision) using the Semantic Differential Method. It is expected that the results of this study will be used as basic data for auditory displays inside bridges and for integrated bridge alarm systems.

• Industry Promotion Research
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• v.6 no.2
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• pp.55-62
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• 2021

The number of single-parent families in South Korea increased since 2000, related to a sharp rise in the divorce rate of 50s and an increase in male mortality rates among those aged 40s-50s. Middle-aged single mothers experience a critical period realizing self-actualization needs, while being in the middle adulthood from the lifespan developmental perspective. In this respect, it is significant to study self-actualization of middle-aged single mothers through guided imagery and music (GIM) in order to provide them with psychological support. This study was conducted from September 2018 to June 2020, and the GIM sessions were conducted at least 10 times. Four participants were selected among the middle-aged single mothers. The imagery experiences of participants in the GIM sessions were classified into four sub-elements: physicalness, emotion, memory, and sense. Within those sub-elements, eight semantic units were categorized into 46 elements. Finally, 152 semantic units were derived. Moreover, the self-actualization which participants experienced through GIM presented three archetypal images: shadow, persona, and the self. In the GIM sessions, experiences of putting their negative emotions associated with family into words and changing passive self-imagery into active one enabled participants to bring the shadow into their consciousness, there by recognizing their positive and bright internal self. Furthermore, participants could map that their current status as people marginalized by siblings and parents, enraged and holding double standards for others, was suppressed by their 'good daughter' and 'religious' personas. This realization lead them to realize and restore their persona. The use of GIM in the study allowed participants to elicit re-experiences of the negative events, while experiencing various imagery and music. This process helped participants achieve self-actualization.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.28-45
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• 2023

Although we have entered the era of digital transformation, there is currently no system that efficiently collects, manages, integrates, and services a large number of archaeological digital source materials produced as a result of cultural relics research, i.e., an intelligent integrated management and service platform for archaeological academic information. In this regard, the need to build a digital dictionary of Korean archaeology was confirmed by examining the problem of the Digital Encyclopedia of Korean Archaeology, which is currently available in PDF format on the web, the current status of the publication and use of the Dictionary of Korean Archaeology, and the cases of building digital platforms at home and abroad. Therefore, this paper aims to suggest a general direction for creating a digital encyclopedia of Korean archaeology based on the Dictionary of Korean Archaeology, which includes quality knowledge information, to reconsider the accessibility of archaeological data in conformity with data access limitations. The application of the series Dictionary of Korean Archaeology, published since 2001, and the necessity for digital transformation were examined, as well as the application of data from the archaeological data archiving platforms of Europe, the USA, Japan, and cases of establishing platforms corresponding to specialized encyclopedias from Korea. Based on these, a three-step implementation plan and detailed projects were suggested to create the Digital Encyclopedia of Korean Archaeology. Through this, we proposed the design of metadata for computerized records and the expansion to semantic (meaning-based) data that gives and shows the relationship information between the produced metadata as the implementation tasks to build the Digital Dictionary of Korean Archaeology. It is hoped that such research will help create an integrated intelligent management and service platform for archaeology, raise awareness, and provide a better understanding of Korean archaeology to the general public.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.429-450
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• 2023

The purpose of this study is to examine recent trends and intellectual structures in research related to open data. To achieve this, the study conducted a search for the keyword "open data" in Scopus and collected a total of 6,543 papers from 1999 to 2023. After data preprocessing, the study focused on the author keywords of 5,589 papers to perform network analysis and derive centrality in the field of open data research and linked open data research. As a result, the study found that "big data" exhibited the highest centrality in research related to open data. The research in this area mainly focuses on the utilization of open data as a concept of public data, studies on the application of open data in analysis related to big data as an associated concept, and research on topics related to the use of open data, such as the reproduction, utilization, and access of open data. In linked open data research, both triadic centrality and closeness centrality showed that "the semantic web" had the highest centrality. Moreover, it was observed that research emphasizing data linkage and relationship formation, rather than public data policies, was more prevalent in this field.

• Information Systems Review
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• v.25 no.1
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• pp.27-46
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• 2023

Research on restaurant recommender systems has been proposed due to the development of the food service industry and the increasing demand for restaurants. Existing restaurant recommendation studies extracted consumer preference information through quantitative information or online review sensitivity analysis, but there is a limitation that it cannot reflect consumer semantic preference information. In addition, there is a lack of recommendation research that reflects the detailed attributes of restaurants. To solve this problem, this study proposed a model that can learn the interaction between consumer preferences and restaurant attributes by applying deep learning techniques. First, the convolutional neural network was applied to online reviews to extract semantic preference information from consumers, and embedded techniques were applied to restaurant information to extract detailed attributes of restaurants. Finally, the interaction between consumer preference and restaurant attributes was learned through the element-wise products to predict the consumer preference rating. Experiments using an online review of Yelp.com to evaluate the performance of the proposed model in this study confirmed that the proposed model in this study showed excellent recommendation performance. By proposing a customized restaurant recommendation system using big data from the restaurant industry, this study expects to provide various academic and practical implications.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.2
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• pp.103-123
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• 2006

Assuming that the knowledge creation and retrieval functions could be the most important factors for a successful knowledge management(KM) especially during the promotion stage of KM, this study suggests an e-learning application as one of best methods for producing knowledge and also the integrated knowledge repository model in which learning, knowledge. and information objects can be semantically associated through topic map-based knowledge map. The traditional KM system provides a simple directory-based knowledge map. which can not provide the semantic links between topics or objects. The proposed model can be utilized as a solution to solve the above-mentioned disadvantages of the traditional models. In order to collect the basic data for the proposed model, first, case studies utilizing interviews and surveys were conducted targeting at three Korean insurance companies' knowledge managers(or e-learning managers) and librarians. Second, the related studies and other topic map-based pilot systems were investigated.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.131-156
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• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering Process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention on the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy (KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance. The KAH consists of two types of knowledge abstraction hierarchies. The value abstraction hierarchy is constructed by abstract values that are hierarchically derived from specific data values in the underlying database on the basis of generalization and specialization relationships. The domain abstraction hierarchy is built on the various domains of the data values and incorporates the classification relationship between super-domains and sub-domains. On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, database operations are discussed for both the generalization and specialization Processes, and the conceptual query handling. A prototype system has been implemented at KAIST that demonstrates the usefulness of KAH in ordinary database application systems.

• Journal of the Korean Society for information Management
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• v.15 no.3
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• pp.133-150
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• 1998

For the purpose of new‘organizational knowledge centric knowledge management’, this paper proposes the knowledge creating organizational memory which shows the knowledge creation in organization according to the dialectical circulation between the domain knowledge and the task knowledge, based on the Yin Yang theory. This paper defines two kinds of organizational knowledge such as the domain knowledge and task knowledge and designs them in the pursuit of its lifecycle. Knowledge creating organizational memory is designed to three knowledge components that circulate through the domain knowledge and the task knowledge according to the object-oriented methodology. Organizational knowledge is designed into the graphical structure of ( i ) knowledge ( ⅱ ) relation between knowledge objects and ( ⅲ ) degree of relation, which receive the legacy of organizational knowledge such as data schema, process model and knowledge base. This design of organizational knowledge can be applied to CBR(Case Based Reasoning), one of knowledge mining tools to create new organizational knowledge.