• Journal of KIISE
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• v.44 no.12
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• pp.1282-1289
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• 2017

Since the study of deep convolutional neural network became prevalent, one of the important discoveries is that a feature map from a convolutional network can be extracted before going into the fully connected layer and can be used as a saliency map for object detection. Furthermore, the model can use features from each different layer for accurate object detection: the features from different layers can have different properties. As the model goes deeper, it has many latent skip connections and feature maps to elaborate object detection. Although there are many intermediate layers that we can use for semantic segmentation through skip connection, still the characteristics of each skip connection and the best skip connection for this task are uncertain. Therefore, in this study, we exhaustively research skip connections of state-of-the-art deep convolutional networks and investigate the characteristics of the features from each intermediate layer. In addition, this study would suggest how to use a recent deep neural network model for semantic segmentation and it would therefore become a cornerstone for later studies with the state-of-the-art network models.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.341-347
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• 2017

As the amount of document data increases, the user needs summarized information to understand the document. However, existing document summary research methods rely on overly simple statistics, so there is insufficient research on multiple document summaries for ambiguity of sentences and meaningful sentence generation. In this paper, we investigate semantic connection and preprocessing process to process unnecessary information. Based on the vocabulary semantic pattern information, we propose a multi-document summarization method that enhances semantic connectivity between sentences using VAE. Using sentence word vectors, we reconstruct sentences after learning from compressed information and attribute discriminators generated as latent variables, and semantic connection processing generates a natural summary sentence. Comparing the proposed method with other document summarization methods showed a fine but improved performance, which proved that semantic sentence generation and connectivity can be increased. In the future, we will study how to extend semantic connections by experimenting with various attribute settings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2704-2719
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• 2022

Lately, neo-Chinese style furniture has been frequently noticed by product design professionals for the big part it played in promoting traditional Chinese culture. This article is an attempt to use big data semantic analysis method to provide effective design research method for neo-Chinese furniture design. By using big data mining program TEXTOM for big data collection and analysis, the data obtained from typical websites in a set time period will be sorted and analyzed. On the basis of "neo-Chinese furniture" samples, key data will be compared, classification analysis of overall data, and horizontal analysis of typical data will be performed by the methods of word frequency analysis, connection centrality analysis, and TF-IDF analysis. And we tried to summarize according to the related views and theories of the design. The research results show that the results of data analysis are close to the relevant definitions of design. The core high-frequency vocabulary obtained under data analysis, such as popular, furniture, modern, etc., can provide a reasonable and effective focus of attention for the designs. The result obtained through the systematic sorting and summary of the data can be a reliable guidance in the direction of our design. This research attempted to introduce related big data mining semantic analysis methods into the product design industry, to supply scientific and objective data and channels for studies on design, and to provide a case on the practical application of big data analysis in the industry.

• Korean Institute of Interior Design Journal
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• v.27 no.3
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• pp.33-40
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• 2018

As the standard for the value of modern people's life increases, hotels make efforts for the users' qualitative and mental satisfaction. As an approach to hotel space design differentiated for new experiences for travelers, a design that reflects the placeness is needed so that people can experience the local culture and historical meaning of the place. Thus, this study divides the components of placeness into physical factors, socio-cultural factors, and semantic factors. As for methods for the design expression of placeness formation, physical factors are classified as the connection to surrounding environments, center, passage, and area. Socio-cultural factors are classified as cultural experiences in the place. Semantic factors are classified as symbolism and historicity. For a case analysis in this study, overseas four-star hotels or higher, where placeness stood out are analyzed, based on the above-extracted components of placeness. As a result of the analysis, the hotels in the cases showed an aspect of expression that emphasized semantic factors despite there were differences in the detailed expression method, depending on the designers. The expression of the place that reflected locality and temporality showed the connection of time, connecting the past with the present. In the future, only the design expression based on the historical and symbolic meanings of the place will be the experience that remains in the users' memories, very precisely.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.7-22
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• 2014

By the publications of RDF and OWL, the Semantic Web is confirmed as a technology through which information in the Internet can be processed by machines. The focus of the Semantic Web study after then has moved to how to provide more useful information to users for their decision making beyond simple use of the structured data in ontologies. SWRL that makes logical inference possible by rules, and SWCL that formulates constraints under the Semantic Web environment are some of many efforts toward the achievement of that goal. Constraint represents a connection or a relationship between individual data in ontology. Based on SWCL, this paper tries to extend the language by adding one more type of constraint, implication constaint, in its repertoire. When users use binary variables to represent logical relationships in mathematical models, it requires and knowledge on the solver to solve the models. The use of implication constraint ease this difficulty. Its need, definition and relevant technical description is presented by the use of the optimal common attribute selection problem in product design.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.9-21
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• 2006

Researches on enhancing the searching function of the web service using the ontology concept have been studying. One of them suggests a searching method for UDDI using DAML and DAML+OIL. However this approach has inconveniences to use operations proper to the circumstance and to define respective ontologies according to them. To solve these problems, we introduce an effective method of dealing with N-Triple, filtering care Triples, merging Triples, semantic connection between Triples and searching Triples for searching information and recommending the results in semantic web environment. Furthermore, we implement this proposed method in a system to test it. Finally, we test the system in the virtual semantic web environment for out research analysis.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.101-108
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• 2019

In this research, I conducted a semantic network analysis centering on media articles on purchasing, revitalizing, and utilizing the former Busan branch of Hansung Bank, a modern architectural heritage. We sought the most efficient analysis elements for the analysis of the social arguments about preservation and utilization embedded in media articles. For this reason, Degree Centrality measures how many connections the word described in the media article has, and Betweenness Centrality measures the influence that controls the flow of information through correlation I examined. In addition, keyword that express the theme well examined the aggregation structure in each sub-network. In this research, in theoretical terms, it makes sense in that the social discussion embedded in the article of the mass media is grasped empirically through semantic network analysis of words. Methodological aspect is best when it includes nouns and adjectives and the distance between words is more than four words in the analysis of the cohesive structure of the semantic network to determine whether the influence of social discussions is best assessed through the connection between words to media articles.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.222-230
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• 2023

The purpose of this study is to provide basic data on sports entertainment programs by collecting data on unstructured data generated by Naver and Google for SBS entertainment program 'Women Who Score Goal', which began regular broadcast in June 2021, and analyzing public perceptions through data mining, semantic matrix, and CONCOR analysis. Data collection was conducted using Textom, and 27,911 cases of data accumulated for 16 months from June 16, 2021 to October 15, 2022. For the collected data, 80 key keywords related to 'Kick a Goal' were derived through simple frequency and TF-IDF analysis through data mining. Semantic network analysis was conducted to analyze the relationship between the top 80 keywords analyzed through this process. The centrality was derived through the UCINET 6.0 program using NetDraw of UCINET 6.0, understanding the characteristics of the network, and visualizing the connection relationship between keywords to express it clearly. CONCOR analysis was conducted to derive a cluster of words with similar characteristics based on the semantic network. As a result of the analysis, it was analyzed as a 'program' cluster related to the broadcast content of 'Kick a Goal' and a 'Soccer' cluster, a sports event of 'Kick a Goal'. In addition to the scenes about the game of the cast, it was analyzed as an 'Everyday Life' cluster about training and daily life, and a cluster about 'Broadcast Manipulation' that disappointed viewers with manipulation of the game content.

• Journal of health informatics and statistics
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• v.43 no.4
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• pp.274-281
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• 2018

Objectives: The purpose of this study is to comprehensively compare the trends of health administration and health policy in the field of health care using the semantic network analysis in the inaugural address of the Ministry of Health and Welfare of each regime in Korea. Methods: This study used a language network analysis method that uses Korean Key Words In Context (KrKwic) program and NetMiner program in sequence. The analysis was conducted by Minister Hwa-joong Kim during the Moo-hyun Roh government, Minister Jae-hee Jeon during the Myung-bak Lee government, Minister Young Jin of Geun-hye Park government and Government Jae-in Moon's inaugural address of Neung-Hoo Park Minister, respectively. Results: The key words differentiated by each regime are that the Moo-hyun Roh Government's Minister Hwa-joong Kim had high connection centrality values in the words 'balanced development', 'comprehensive' and 'reform'. Minister Jae-Hee Jeon of Myung-bak Lee Government had high connection centrality values in the words 'poverty' and 'return'. In the case of Minister Young Jin of Geun-hye Park Government had high connection centrality values in the words 'demand', 'Customized' and 'Life cycle'. In the case of Minister Neung-Hoo Park of Jae In Moon Government had high connection centrality values in the words 'Welfare state', 'Embracing' and 'Soundness'. Conclusions: If the role of health administration in the health care field and the health care policies are constantly changed according to the policies of each regime, it is inconsistent and it is difficult to approach from the long term perspective for public health promotion. In the future, health policy should be developed and implemented with a long-term perspective and consistency based on the consensus and participation of the people with less influence on the change and direction of each government's policies.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.4
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• pp.41-65
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• 2022

This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.