• Journal of the Korea Society of Computer and Information
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• v.23 no.6
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• pp.9-14
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• 2018

This paper focuses on how the latest progress in digital media and technology affects the writing education environment. In the contemporary era, collecting numerous pices of information online, and arranging them to create new knowledge is important. There is also a need to seek new methods for writing education to stay in tune with the times. To that end, this paper suggests an open writing model using hypertexts. This writing model consists of a total of five stages, which are use of information, compilation of information, open mutual discussion, search of additional information and writing to recreate knowledge. The final outcome of such writing is writing using footnotes. By describing the gist of the keyword and adding numerous footnotes, such writing opens up an infinite possibility of re-creating information into new knowledge. This method can help university students who are accustomed to the digital society to proactively use information and improve multi-disciplinary communication skills required today. This author applied such a model to university writing education and found that more than 82% of the students were satisfied. Through the process of collaboration and recreation of knowledge in writing, learners found distinct benefits and noted their horizons had broadened. Given this effect, the open writing model using hypertexts is meaningful in that it forms a learning community that goes beyond a one-way feedback from instructor to student and instead nudges students to realize collective intellect. Moreover, it is meaningful in that it moves away from a top-down approach of the instructors passing down knowledge about writing and its rules, and towards a more proactive involvement by students in creating knowledge.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.1
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• pp.277-301
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• 2020

The purpose of this study is to analyze art museum websites and derive implications for future operation of art museum websites. To this end, this research collected basic information about art museums according to '2018 National General Report of Cultural Infrastructure' and investigate the websites of 30 art museums through multi-step sampling process. This study analyzed the structure and menu of the art museum websites as well as the current state of various contents provided by the websites and the search service for the collections offered by the websites. Following sentences are the results. First of all, the art museum websites offer 5.6 top menus on average. Secondly, contents related to art museum, exhibitions, news, education, general forum, and SNS are the basic contents that should be provided on the art museum websites. Third, for contents related to news, education, and events have problems with hierarchical structure and need to be adjusted. Fourth, in the content type, specialized information contents are relatively insufficient and thus need to be improved. Fifth, the art museum websites should give sufficient information about the collection and offer directory searching hat includes keyword searching as well as detail searching service. It is also required to reorganize the directory along with the download function for searched results and the sorting service.

• 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.