• Title/Summary/Keyword: Evaluation Module(Evaluation System)

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Optimum Operating Condition for Micro-Filtration Process as a Seawater Desalination Pretreatment (해수담수화 전처리로서 가압식 MF 공정의 최적 운전조건 도출)

  • Kim, Youngmin;Jang, Jung-Woo;Kim, Jin-Ho;Choi, June-Seok;Lee, Sangho;Kim, Sukwi
    • Journal of Korean Society of Environmental Engineers
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    • v.35 no.9
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    • pp.624-629
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    • 2013
  • The relation between performance maintenance conditions and those cost efficiency was studied to choose an optimum operating condition in the seawater desalination pretreatment system. A hollow fiber microfiltration module, which was developed with domestic technology, was tested with the various operating conditions such as chemically enhanced backwash cycles and design dosages of a cleaning chemical. Transmembrane pressure was measured to investigate membrane fouling status and cleaning degree. In addition, economic analysis was performed to compare water production costs by the operation condition. As a result, The operation mode III, chemically enhanced backwash at once a day with 100 mg/L of sodium hypochlorite (NaOCl) was selected. The concurrent evaluation between membrane filtration performance and its economic analysis will be suitable to choose an efficient optimum condition.

Smart Camera Technology to Support High Speed Video Processing in Vehicular Network (차량 네트워크에서 고속 영상처리 기반 스마트 카메라 기술)

  • Son, Sanghyun;Kim, Taewook;Jeon, Yongsu;Baek, Yunju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.1
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    • pp.152-164
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    • 2015
  • A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.

A Comparative Research on End-to-End Clinical Entity and Relation Extraction using Deep Neural Networks: Pipeline vs. Joint Models (심층 신경망을 활용한 진료 기록 문헌에서의 종단형 개체명 및 관계 추출 비교 연구 - 파이프라인 모델과 결합 모델을 중심으로 -)

  • Sung-Pil Choi
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.1
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    • pp.93-114
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    • 2023
  • Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

Enhancing Small-Scale Construction Sites Safety through a Risk-Based Safety Perception Model (소규모 건설현장의 위험성평가를 통한 안전인지 모델 연구)

  • Kim, Han-Eol;Lim, Hyoung-Chul
    • Journal of the Korea Institute of Building Construction
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    • v.24 no.1
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    • pp.97-108
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    • 2024
  • This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2013 (설비공학 분야의 최근 연구 동향 : 2013년 학회지 논문에 대한 종합적 고찰)

  • Lee, Dae-Young;Kim, Sa Ryang;Kim, Hyun-Jung;Kim, Dong-Seon;Park, Jun-Seok;Ihm, Pyeong Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.12
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    • pp.605-619
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    • 2014
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2013. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of fluid machinery, pipes and relative parts including orifices, dampers and ducts, fuel cells and power plants, cooling and air-conditioning, heat and mass transfer, two phase flow, and the flow around buildings and structures. Research issues dealing with home appliances, flows around buildings, nuclear power plant, and manufacturing processes are newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for general analytical model for desiccant wheels, the effects of water absorption on the thermal conductivity of insulation materials, thermal properties of Octadecane/xGnP shape-stabilized phase change materials and $CO_2$ and $CO_2$-Hydrate mixture, effect of ground source heat pump system, the heat flux meter location for the performance test of a refrigerator vacuum insulation panel, a parallel flow evaporator for a heat pump dryer, the condensation risk assessment of vacuum multi-layer glass and triple glass, optimization of a forced convection type PCM refrigeration module, surface temperature sensor using fluorescent nanoporous thin film. In the area of pool boiling and condensing heat transfer, researches on ammonia inside horizontal smooth small tube, R1234yf on various enhanced surfaces, HFC32/HFC152a on a plain surface, spray cooling up to critical heat flux on a low-fin enhanced surface were actively carried out. In the area of industrial heat exchangers, researches on a fin tube type adsorber, the mass-transfer kinetics of a fin-tube-type adsorption bed, fin-and-tube heat exchangers having sine wave fins and oval tubes, louvered fin heat exchanger were performed. (3) In the field of refrigeration, studies are categorized into three groups namely refrigeration cycle, refrigerant and modeling and control. In the category of refrigeration cycle, studies were focused on the enhancement or optimization of experimental or commercial systems including a R410a VRF(Various Refrigerant Flow) heat pump, a R134a 2-stage screw heat pump and a R134a double-heat source automotive air-conditioner system. In the category of refrigerant, studies were carried out for the application of alternative refrigerants or refrigeration technologies including $CO_2$ water heaters, a R1234yf automotive air-conditioner, a R436b water cooler and a thermoelectric refrigerator. In the category of modeling and control, theoretical and experimental studies were carried out to predict the performance of various thermal and control systems including the long-term energy analysis of a geo-thermal heat pump system coupled to cast-in-place energy piles, the dynamic simulation of a water heater-coupled hybrid heat pump and the numerical simulation of an integral optimum regulating controller for a system heat pump. (4) In building mechanical system research fields, twenty one studies were conducted to achieve effective design of the mechanical systems, and also to maximize the energy efficiency of buildings. The topics of the studies included heating and cooling, HVAC system, ventilation, and renewable energies in the buildings. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment is mostly focused on indoor environment and building energy. The main researches of indoor environment are related to infiltration, ventilation, leak flow and airtightness performance in residential building. The subjects of building energy are worked on energy saving, operation method and optimum operation of building energy systems. The remained studies are related to the special facility such as cleanroom, internet data center and biosafety laboratory. water supply and drain system, defining standard input variables of BIM (Building Information Modeling) for facility management system, estimating capability and providing operation guidelines of subway station as shelter for refuge and evaluation of pollutant emissions from furniture-like products.

Recent Progress in Air Conditioning and Refrigeration Research - A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2004 and 2005 - (공기조화, 냉동 분야의 최근 연구 동향 -2004년 및 2005년 학회지 논문에 대한 종합적 고찰-)

  • Choi, Yong-Don;Kang, Yong-Tae;Kim, Nae-Hyun;Kim, Man-Hoe;Park, Kyoung-Kuhn;Park, Byung-Yoon;Park, Jin-Chul;Hong, Hi-Ki
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.19 no.1
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    • pp.94-131
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    • 2007
  • A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 2004 and 2005 has been done. Focus has been put on current status of research in the aspect of heating, cooling, air-conditioning, ventilation, sanitation and building environment. The conclusions are as follows. (1) Most of fundamental studies on fluid flow were related with heat transportation of facilities. Drop formation and rivulet flow on solid surfaces were interesting topics related with condensation augmentation. Research on micro environment considering flow, heat, humidity was also interesting for comfortable living environment. It can be extended considering biological aspects. Development of fans and blowers of high performance and low noise were continuing topics. Well developed CFD and flow visualization(PIV, PTV and LDV methods) technologies were widely applied for developing facilities and their systems. (2) The research trends of the previous two yews are surveyed as groups of natural convection, forced convection, electronic cooling, heat transfer enhancement, frosting and defrosting, thermal properties, etc. New research topics introduced include natural convection heat transfer enhancement using nanofluid, supercritical cooling performance or oil miscibility of $CO_2$, enthalpy heat exchanger for heat recovery, heat transfer enhancement in a plate heat exchanger using fluid resonance. (3) The literature for the last two years($2004{\sim}2005$) is reviewed in the areas of heat pump, ice and water storage, cycle analysis and reused energy including geothermal, solar and unused energy). The research on cycle analysis and experiments for $CO_2$ was extensively carried out to replace the Ozone depleting and global warming refrigerants such as HFC and HCFC refrigerants. From the year of 2005, the Gas Engine Heat Pump(GHP) has been paid attention from the viewpoint of the gas cooling application. The heat pipe was focused on the performance improvement by the parametric analysis and the heat recovery applications. The storage systems were studied on the performance enhancement of the storage tank and cost analysis for heating and cooling applications. In the area of unused energy, the hybrid systems were extensively introduced and the life cycle cost analysis(LCCA) for the unused energy systems was also intensively carried out. (4) Recent studies of various refrigeration and air-conditioning systems have focused on the system performance and efficiency enhancement. Heat transfer characteristics during evaporation and condensation are investigated for several tube shapes and of alternative refrigerants including carbon dioxide. Efficiency of various compressors and expansion devices are also dealt with for better modeling and, in particular, performance improvement. Thermoelectric module and cooling systems are analyzed theoretically and experimentally. (5) According to the review of recent studies on ventilation systems, an appropriate ventilation systems including machenical and natural are required to satisfied the level of IAQ. Also, an recent studies on air-conditioning and absorption refrigeration systems, it has mainly focused on distribution and dehumidification of indoor air to improve the performance were carried out. (6) Based on a review of recent studies on indoor environment and building service systems, it is noticed that research issues have mainly focused on optimal thermal comfort, improvement of indoor air Quality and many innovative systems such as air-barrier type perimeter-less system with UFAC, radiant floor heating and cooling system and etc. New approaches are highlighted for improving indoor environmental condition as well as minimizing energy consumption, various activities of building control and operation strategy and energy performance analysis for economic evaluation.

A Study on Intelligent Value Chain Network System based on Firms' Information (기업정보 기반 지능형 밸류체인 네트워크 시스템에 관한 연구)

  • Sung, Tae-Eung;Kim, Kang-Hoe;Moon, Young-Su;Lee, Ho-Shin
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.67-88
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    • 2018
  • Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

Assessing Middle School Students' Understanding of Radiative Equilibrium, the Greenhouse Effect, and Global Warming Through Their Interpretation of Heat Balance Data (열수지 자료 해석에서 드러난 중학생의 복사 평형, 온실 효과, 지구 온난화에 대한 이해)

  • Chung, Sueim;Yu, Eun-Jeong
    • Journal of the Korean earth science society
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    • v.42 no.6
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    • pp.770-788
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    • 2021
  • This study aimed to determine whether middle school students could understand global warming and the greenhouse effect, and explain them in terms of global radiative equilibrium. From July 13 to July 24 in 2021, 118 students in the third grade of middle school, who completed a class module on 'atmosphere and weather', participated in an online assessment consisting of multiple-choice and written answers on radiative equilibrium, the greenhouse effect, and global warming; 97 complete responses were obtained. After analysis, it was found that over half the students (61.9%) correctly described the meaning of radiative equilibrium; however, their explanations frequently contained prior knowledge or specific examples outside of the presented data. The majority of the students (92.8%) knew that the greenhouse effect occurs within Earth's atmosphere, but many (32.0%) thought of the greenhouse effect as a state in which the radiative equilibrium is broken. Less than half the students (47.4%) answered correctly that radiative equilibrium occurs on both Earth and the Moon. Most of the students (69.1%) understood that atmospheric re-radiation is the cause of the greenhouse effect, but few (39.2%) answered correctly that the amount of surface radiation emitted is greater than the amount of solar radiation absorbed by the Earth's surface. In addition, about half the students (49.5%) had a good understanding of the relationship between the increase in greenhouse gases and the absorption of atmospheric gases, and the resulting reradiation to the surface. However, when asked about greenhouse gases increases, their thoughts on surface emissions were very diverse; 14.4% said they increased, 9.3% said there was no change, 7.2% said they decreased, and 18.6% gave no response. Radiation equilibrium, the greenhouse effect, and global warming are a large semantic network connected by the balance and interaction of the Earth system. This can thus serve as a conceptual system for students to understand, apply, and interpret climate change caused by global warming. Therefore, with the current climate change crisis facing mankind, sophisticated program development and classroom experiences should be provided to encourage students to think scientifically and establish scientific concepts based on accurate understanding, with follow-up studies conducted to observe the effects.

A Methodology for Automatic Multi-Categorization of Single-Categorized Documents (단일 카테고리 문서의 다중 카테고리 자동확장 방법론)

  • Hong, Jin-Sung;Kim, Namgyu;Lee, Sangwon
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.77-92
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    • 2014
  • Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

A Study on Market Size Estimation Method by Product Group Using Word2Vec Algorithm (Word2Vec을 활용한 제품군별 시장규모 추정 방법에 관한 연구)

  • Jung, Ye Lim;Kim, Ji Hui;Yoo, Hyoung Sun
    • 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.