• International Journal of Knowledge Content Development & Technology
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• v.4 no.1
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• pp.23-37
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• 2014

The Trust and Authority in Scholarly Communications in the Light of the Digital Transition research project1) was a study which investigated the behaviours and attitudes of academic researchers as producers and consumers of scholarly information resources in respect to how they determine authority and trustworthiness. The research questions for the study arose out of CIBER's studies of the virtual scholar. This paper focuses on elements of this study, mainly an analysis of a scholarly publisher's usage logs, which was undertaken at the start of the project in order to build an evidence base, which would help calibrate the main methodological tools used by the project: interviews and questionnaire. The specific purpose of the log study was to identify and assess the digital usage behaviours that potentially raise trustworthiness and authority questions. Results from the self-report part of the study were additionally used to explain the logs. The main findings were that: 1) logs provide a good indicator of use and information seeking behaviour, albeit in respect to just a part of the information seeking journey; 2) the 'lite' form of information seeking behaviour observed in the logs is a sign of users trying to make their mind up in the face of a tsunami of information as to what is relevant and to be trusted; 3) Google and Google Scholar are the discovery platforms of choice for academic researchers, which partly points to the fact that they are influenced in what they use and read by ease of access; 4) usage is not a suitable proxy for quality. The paper also provides contextual data from CIBER's previous studies.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.708-711
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• 2008

This study is intended to build research for ways to utilize material information in the design and working business for public works. The contents and results of this study can be classified into object-oriented DB application to bridge construction and object-oriented DB utilization of civil material information. First, application of object-oriented DB to bridge construction 1) constructs the work unit of classified work table as an object(Each object constructs material information on the statement of quantity calculation as data), 2) constructs object-oriented DB for superstructure and substructure of PSC Beam bridge, 3) leads to the research for ways to utilize materials by developing 3D bridge prototype with REVIT structure. Secondly, ways to utilize object-oriented DB for civil material information identified the possibility for utilizing it in making 2D drawings for design work, preparing materials list, analyzing structure for working businesses, selecting and purchasing materials, managing process and maintaining. It is suggested that the results of this study should be applied to all bridge constructions through test-bed and additional studies so as to secure the credibility of the results of this study.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.87-98
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• 2019

As artificial intelligence is actively studied, it is being applied to various fields such as image, video and natural language processing. The natural language processing, in particular, is being studied to enable computers to understand the languages spoken and spoken by people and is considered one of the most important areas in artificial intelligence technology. In natural language processing, it is a complex, but important to make computers learn to understand a person's common sense and generate results based on the person's common sense. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn common sense easily from computers. However, the existing knowledge graphs are organized only by focusing on specific languages and fields and have limitations that cannot respond to neologisms. In this paper, we propose an intelligent chatbotsystem that collects and analyzed data in real time to build an automatically scalable knowledge graph and utilizes it as the base data. In particular, the fine-tuned BERT-based for relation extraction is to be applied to auto-growing graph to improve performance. And, we have developed a chatbot that can learn human common sense using auto-growing knowledge graph, it verifies the availability and performance of the knowledge graph.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.179-192
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• 2008

This case study shows constructing the knowledge-based system using a rule-based approach for detecting illegal transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions, the adoption of a knowledge-based system in the KoFIU is essential. Also since different types of information from various organizations are converged into the KoFIU, constructing a knowledge-based system for practical use and data management regarding money laundering is definitely required. The success of the financial information system largely depends on how well we can build the knowledge-base for the context. Therefore we designed and constructed the knowledge-based system for anti-money laundering by committing domain experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation, measured by the empirical ratio of Suspicious Transaction Reports (STRs) reported to law enforcements, shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently, and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.181-203
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• 2022

This study analyzed domestic and foreign literature and examined cases of foreign Community of Practice(CoP) of experts to find out what benefits researchers can gain from participating in their CoP, how the CoP was established, and how data is shared within the CoP. In addition, this study discussed on how to establish a CoP of experts in Korea for sharing and using research data. By participating in the CoP of experts, members can be provided with the opportunity to build an experts' network and have a chance to meet with various experts, to acquire and share their expertise and information, to receive help from other experts, to learn about their expertise, and to have opportunities for professional experiences. In addition, this study discussed 4 factors such as operation method and management system, memberships and number of members, activities, and management of data and repository for establishing a CoP of experts for sharing and using research data. This study provides a knowledge base for building a CoP of experts in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.570-576
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• 2020

This study uses beacons and smartphone Global Positioning System (GPS) receivers to establish a location-based disaster/hazard prediction system. Beacons are usually installed indoors to locate users using triangulation in the room, but this study is differentiated from previous studies because the system is used outdoors to collect information on registration location and temperature and humidity in hazardous areas. In addition, since it is installed outdoors, waterproof, dehumidifying, and dustproof functions in the beacons themselves are required, and in case of heat and humidity, the sensor must be exposed to the outside, so the waterproof function is supplemented with a separate container. Based on these functions, information on declining and vulnerable areas is identified in real time, and temperature/humidity information is collected. We also propose a system that provides weather and fine-dust information for the area concerned. User location data are acquired through beacons and smartphone GPS receivers, and when users transmit from declining or vulnerable areas, they can establish the data to identify dangerous areas. In addition, temperature/humidity data in a microspace can be collected and utilized to build data to cope with climate change. Data can be used to identify specific areas of decline in a microspace, and various analyses can be made through the accumulated data.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1137-1142
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• 2017

Cyber hacking attacks and cyber terrorism are damaging to the lives of the people, and in the end, national security is threatened. Cyber-hacking attacks leaked nuclear power cooling system design drawings, cyber accidents such as hacking of Cheongwadae's homepage and hacking of KBS stations occurred. The Act on Information and Communication Infrastructure Protection, Promotion of Information and Communication Network Utilization and Information Protection, and the Personal Information Protection Act remove the responsibility for cyber attacks, but it is difficult to prevent attacks by hackers armed with new technologies. This paper studies the development of cyber security experts for cyber security. Build a Knowledge Data Base for cyber security professionals. Web hacking, System hacking, and Network hacking technologies and evaluation. Through researches on the operation and acquisition of cyber security expert certification, we hope to help nurture cyber security experts for national cyber security.

• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.2
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• pp.101-111
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• 2009

In this study, the physico-chemical characteristics of municipal solid waste (MWS) which was treated in gangwon area were investigated. It is necessary to measure the characteristics of municipal solid waste for build a waste treatment and RDF facility and for data-base and total managing of the landfill. It was found that the average density of solid wastes is in the range of $101.8{\sim}199.8kg/m^3$. This MSW was composed of 30.7% of food wastes, 36.3% of papers, 15.8% of plastics & vinyls, 1.9% of textiles, 3.2% of wood and 1.5% of rubber & leathers respectively. Most of MSW are composed of food, paper and plastic waste and the combustible waste is more than 90%. For three components, moisture is 44.6%, combustible component is 47.7% and ash is 7.7% respectively. The chemical elements are carbon, oxygen, and hydrogen on the dry basis of wastes. The low heating value of the MSW measured by calorimeter was obtained as 2,631 kcal/kg, and the high heating value of the MSW was obtained as 3,310 kcal/kg.