• International journal of advanced smart convergence
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• v.5 no.4
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• pp.40-47
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• 2016

Journalism robot by using a computer algorithm, while maintaining the precision and reliability of the existing media refers to an article which is automatically created. In this paper, we introduce 'stock robot' of robot journalism which writes securities articles and describe artificial intelligence algorithms in stages. Key steps of stock robot implemented artificial intelligence algorithm through four steps of data collection and storage, key event extraction, article content production, and article production. This research has developed a stock robot that collects and analyzes data on social issues and stock indexes for the last 2 years. In the future, as the algorithm is further developed, it becomes possible to write securities articles quickly and accurately through social issues. It will also provide customized information tailored to the user's preferences.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.301-316
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• 2020

Algorithm journalism refers to the practices of automated news generation using algorithms that generate human sounding narratives. Algorithm journalism is known to have strengths in automating repetitive tasks through rapid and accurate analysis of data, and has been actively used in news domains such as sports and finance. In this paper, we propose an interactive card news system that generates personalized local election articles in 2018. The system consists of modules that collects and analyzes election data, generates texts and images, and allows users to specify their interests in the local elections. When a user selects interested regions, election types, candidate names, and political parties, the system generates card news according to their interest. In the study, we examined how personalized card news are evaluated in comparison with text and card news articles by human journalists, and derived implications on the potential use of algorithm in reporting political events.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.85-90
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• 2023

The Ant Colony System (ACS) is a variant of Ant colony optimization algorithm which is well-known in Traveling Salesman Problem. This paper proposed a hybrid method based on genetic algorithm (GA) and ant colony system (ACS), called GACS, to solve traffic routing problem. In the GACS, we use genetic algorithm to optimize the ACS parameters that aims to attain the shortest trips and time through new functions to help the ants to update global and local pheromones. Our experiments are performed by the GACS framework which is developed from VANETsim with the ability of real map loading from open street map project, and updating traffic light in real-time. The obtained results show that our framework acquired higher performance than A-Star and classical ACS algorithms in terms of length of the best global tour and the time for trip.

• ETRI Journal
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• v.35 no.5
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• pp.900-910
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• 2013

Small-screen mobile terminals have difficulty accessing existing Web resources designed for large-screen devices. This paper presents an adaptive transformation method based on webpage semantic features to solve this problem. According to the text density and link density features of the webpages, the webpages are divided into two types: index and content. Our method uses an index-based webpage transformation algorithm and a content-based webpage transformation algorithm. Experiment results demonstrate that our adaptive transformation method is not dependent on specific software and webpage templates, and it is capable of enhancing Web content adaptation on small-screen terminals.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.13-32
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• 2018

The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.