• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.3-14
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• 2018

For satisfying consumer needs, commercial facilities require a variety of sale-related space expressions and eye-catching product arrangements; space composition can also be a direct marketing strategy. The human eye is the sensory organ that acquires the largest amount of information, and an analysis of visual information helps in understanding visual relations between . However, the existing studies are mostly focused on analysis of still frames in experimental images, and there is a lack of studies analyzing gaze information based on mobile images of commercial spaces. Therefore, this study analyzed emotional responses through gaze information of space users in reality using a video of a movement route through a commercial facility. The analysis targeted straight sections of the moving route; based on the data acquired, sectional characteristics of five gaze intensity ranges were examined. As a result, section A, the starting point of the route, had a low gaze intensity, while section B had the highest gaze intensity. This indicates that, starting in section B, the subjects explored the space in a stable way and needed time to adapt to the experimental video. In relation to space characteristics of the gaze-concentrated area, display formats of the right stores in 4 of 6 sections received greater attention. The gaze of consumers was mostly focused on props, and big gaze information was revealed in showcase display formats of the stores. In conclusion, this analysis method can provide highly useful direct design data about merchandise display and merchandise component arrangement based on consumer visual preference.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.213-220
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• 2011

In the current construction industry where various stakeholders take part, BIM Data exchange using standard format can provide a more efficient working environment for related staffs during the life-cycle of the building. Currently, the formats used to exchange the data from 3D-CAD application to structure energy analysis at the design stages are IFC, the international standard format provided by IAI, and gbXML, developed by Autodesk. However, because of insufficient data compatibility, the BIM data produced in the 3D-CAD application cannot be directly used in the energy analysis, thus there needs to be additional data entry. The reasons for this are as follows: First, an IFC file cannot contain all the data required for energy simulation. Second, architects sometimes write material names on the drawings that are not matching to those in the standard material library used in energy analysis tools. DOE-2.2 and Energy Plus are the most popular energy analysis engines. And both engines have their own material libraries. However, our investigation revealed that the two libraries are not compatible. First, the types and unit of properties were different. Second, material names used in the library and the codes of the materials were different. Furthermore, there is no material library in Korean language. Thus, by comparing the basic library of DOE-2, the most commonly used energy analysis engine worldwide, and EnergyPlus regarding construction materials; this study will analyze the material data required for energy analysis and propose a way to effectively enter these using semantic web's ontology. This study is meaningful as it enhances the objective credibility of the analysis result when analyzing the energy, and as a conceptual study on the usage of ontology in the construction industry.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.179-184
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• 2024

Franchise are now a red ocean in Food industry and they need to find other options to appeal for their product, the uprising content, food tech. The franchises are working on R&D to help franchisees with the operations. Through this paper, we analyze the franchise interest on food tech and to help find the necessity of development for franchisees who are in needs with hand, not of human, but of technology. Using Textom, a big data analysis tool, "franchise" and "food tech" were selected as keywords, and search frequency information of Naver and Daum was collected for a year from 01 January, 2023 to 31 December, 2023, and data preprocessing was conducted based on this. For the suitability of the study and more accurate data, data not related to "food tech" was removed through the refining process, and similar keywords were grouped into the same keyword to perform analysis. As a result of the word refining process, a total of 10,049 words were derived, and among them, the top 50 keywords with the highest relevance and search frequency were selected and applied to this study. The top 50 keywords derived through word purification were subjected to TF-IDF analysis, visualization analysis using Ucinet6 and NetDraw programs, network analysis between keywords, and cluster analysis between each keyword through Concor analysis. By using big data analysis, it was found out that franchise do have interest on food tech. "technology", "franchise", "robots" showed many interests and keyword "R&D" showed that franchise are keen on developing food tech to seize competitiveness in Franchise Industry.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.850-861
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• 2003

When creating annotation information in a free~form environment, ambiguity arises during the analysis stage between geometric information and the annotations. This needs to be resolved so that the accurate creation of annotation information in a free-form annotation environment is possible. This paper identifies and analyzes the ambiguities, specifying methods that are tailored to each of the various contexts that can cause conflicts with free-form marking in a XML-based annotation environment. The proposed general method is based on context which includes various textual and structure information between free-form marking and the annotations themselves. The context information used is expressed in XML based DTD, within the paper. The results are printed and shared through a system specifically implemented for this study. The results from the implementation of the Proposed method show that the annotated areas included in the free-form marking information are more accurate, achieving more accurate exchange results amongst multiple users in a heterogeneous document environment.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.3
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• pp.103-131
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• 2012

This study aimed to identify the entire lifecycle of research projects in science and technology. Specifically, it attempted to reveal major research steps and research activities from the beginning to the end of R&D projects. It also investigated information needs, source use and problems scientists encounter in each research step. In-depth interviews with 24 Korean scientists in the fields of bio- and nano-science and technology revealed five major steps of lifecycle, namely idea formation, seeking funding, experiment and analysis, output disseminations, and evaluation. We further identified specific information behaviors and salient communication and research tools in each step.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.1-7
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• 2011

Satellite imagery information have not been fully utilized due to the low R&D investment in remote sensing application though Korea had succeeded in developing series of earth observing satellites during the last decades. However, another series of earth observing satellites such as KOMPSAT 3, 3-A, 5 are going to be launched in the near future. And recent global warming issues stimulate both private and public sectors to make the most of satellite imagery information. Therefore, it is inevitable to promote the utilization of Korean satellite imagery information. In this study, we analyzed the demand and restrictions in exploitation of satellite imagery information in Korea through the online survey and interview. The results showed that the standardization of pre-processing, service of detailed technical information, fast and reliable image data delivery system are mostly required.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.2
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• pp.49-65
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• 2018

Are the benefits derived from ICT based reference and information service worth the financial and other commitments devoted to it? In an attempt to answer this, this study delved into finding out the perceived benefits; the rational for ICT based reference services in Nigerian university libraries. The main objectives were to find out the purposes for using ICT facilities in reference services delivery and the perceived benefits derived from using ICT resources in reference and information services. Being a survey, questionnaire was used to collect data from the librarians of twelve (12) universities; two (2) each sampled from the six geopolitical zones of Nigeria. Data was analyzed using frequencies, mean scores and standard deviations. ANOVA statistical analysis was used to test the hypothesis of no significance difference in the benefits derived from ICT based reference services using p-value of 0.05 to calculate the level of significance. Findings showed that librarians and library users made use of ICT facilities for different reference purposes especially to obtain information they need using the internet. Other reference needs for which patrons used the ICT facilities included: - access to current e-books and e - journals, user education and access to global information in other libraries. Provision of current awareness services (CAS) and selective dissemination of information services (SDI), on-line searching using workstations in the library, provision of on-line public access catalogue (OPAC) services, keeping statistics of users of the reference section and compilation of bibliographies. Further findings showed that the librarians and library users derive a lot of benefits from their use of ICT facilities in reference services. The results showed that easy retrieval and dissemination of information to patrons were ranked highest by the librarians amongst others.

• The Journal of Information Technology
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• v.7 no.1
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• pp.87-104
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• 2004

This study is to understand basic knowledge on e-logistics through the analysis of third party logistics(3PL) as well as fourth party logistics(4PL) and to suggest some activation plans of e-logistics of information era to get competition in the field of international logistics. Compared with advanced countries, Korean companies has not activated 3PL logistics as Korean companies are not inclined to open their business information to others and they didn't recognize the importance of logistics. As the business environments are worsening little by little, there has been greater concerns for e-logistics as a way of focusing on the core-business. Most of Korean companies has outsourced simple and limited scope of 3PL and 4PL services with 1st level of logistics outsourcing. To activate e-logistics, Korean government and private enterprises have to pursue the following strategies. First, Korean government should change the present laws preventing the enterprises specialized in 3PL from doing business and should pursue logistics information and standardization. Also the government needs to support 3PL companies. Second, private companies do their best to retain and develope factors of logistics resources professional and to develope the latest technology. 3PL providers have pursue effective logistics strategies and to invest capitals for the information technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.