• 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.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.1
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• pp.45-52
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• 2015

Purpose : The dose distribution of organ at risk (OAR) and normal tissue is affected by treatment technique in postoperative radiation therapy for prostate cancer. The aim of this study was to compare dose distribution characteristic and to evaluate treatment efficiency by devising VMAT plans according to applying differed number of arc and IMRT plan for postoperative patient of prostate cancer radiation therapy using a rectal balloon. Materials and Methods : Ten patients who received postoperative prostate radiation therapy in our hospital were compared. CT images of patients who inserted rectal balloon were acquired with 3 mm thickness and 10 MV energy of HD120MLC equipped Truebeam STx (Varian, Palo Alto, USA) was applied by using Eclipse (Version 11.0, Varian, Palo Alto, USA). 1 Arc, 2 Arc VMAT plans and 7-field IMRT plan were devised for each patient and same values were applied for dose volume constraint and plan normalization. To evaluate these plans, PTV coverage, conformity index (CI) and homogeneity index (HI) were compared and $R_{50%}$ was calculated to assess low dose spillage as per treatment plan. $D_{25%}$ of rectum and bladder Dmean were compared on OAR. And to evaluate the treatment efficiency, total monitor units(MU) and delivery time were considered. Each assessed result was analyzed by average value of 10 patients. Additionally, portal dosimetry was carried out for accuracy verification of beam delivery. Results : There was no significant difference on PTV coverage and HI among 3 plans. Especially CI and $R_{50%}$ on 7F-IMRT were the highest as 1.230, 3.991 respectively(p=0.00). Rectum $D_{25%}$ was similar between 1A-VMAT and 2A-VMAT. But approximately 7% higher value was observed on 7F-IMRT compare to the others(p=0.02) and bladder Dmean were similar among the all plan(P>0.05). Total MU were 494.7, 479.7, 757.9 respectively(P=0.00) for 1A-VMAT, 2A-VMAT, 7F-IMRT and at the most on 7F-IMRT. The delivery time were 65.2sec, 133.1sec, 145.5sec respectively(p=0.00). The obvious shortest time was observed on 1A-VMAT. All plans indicated over 99.5%(p=0.00) of gamma pass rate (2 mm, 2%) in portal dosimetry quality assurance. Conclusion : As a result of study, postoperative prostate cancer radiation therapy for patient using a rectal balloon, there was no significant difference of PTV coverage but 1A-VMAT and 2A-VMAT were more efficient for dose reduction of normal tissue and OARs. Between VMAT plans. $R_{50%}$ and MU were little lower in 2A-VMAT but 1A-VMAT has the shortest delivery time. So it is regarded to be an effective plan and it can reduce intra-fractional motion of patient also.

• Journal of Korean Home Economics Education Association
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• v.28 no.3
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• pp.47-63
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• 2016

The purpose of this study is to suggest the basic information for diverse and balanced research and development in this field with understanding research trends related to safety education in home economics. In order to so, this study makes population and sampling by targeting cases which refer to 'safety' on 15 papers of academic journals related to home economics registered in the National Research Foundation from 2001 to 2015, 244 papers related to safety education area and 179 master doctorate thesis by searching keyword as 'safety'. Analysis contents are research trends of papers related to safety education by year and by subject and research trends of safety education by area and by research method. As a result of the study, first, the number of research papers related to safety education by year on home economics curriculum repeated increase and decrease and there have been consistent studies conducted on safety education with 14-52 papers per every year and yearly average 28.2 papers. On the other hand, the most number of studies conducted in 2015 with 52 papers which are twice as much of 26 papers in 2014. This seems to be affected by the announcement of safety comprehensive countermeasures from government and the emphasis of safety subject on 2015 curriculum revision of the Ministry of Education. Second, with regards to research trends by topic, 137 papers are related to safety education (29%), 336 papers are related to safety actual condition (71%). Accidents and recognition had a greater percentage in a paper before 2009 (74.4%) and studies are increased after 2009 (from 21 papers to 53 papers) in terms of development or evaluation of safety education program, development of education materials, development of education method etc. Subject area dealt with the most on the research of safety actual condition is regarding safety accidents or effective variables (23.2%). Subject regarding the variables are researches related to factors influencing family violence, internet addiction, spouse violence, willingness to purchase unsafe food, age harassment, or suicidal attempt etc. Next, researches related to safety recognition (13.9%), safety knowledge and attitude (7.4%), safety behaviors (6.3%), safety consciousness (2.3%) show in sequence. Subject area dealt with the most on the researches regarding safety education is development and evaluation of safety education program (11%) and this appears the most in 2015 by year (21.5%). Third, with regards to eight areas of safety education, there are 143 papers regarding public safety (33.8%), 106 papers regarding violence and personal safety (25.1%), 93 papers regarding general subject on safety or whole safety area (22%) and 58 papers regarding drug and internet addiction (13.7%) in sequence. And there is no paper related to first aid and 1 paper is related to occupational safety (0.2%). Occupational safety area is less researched nevertheless its included in home economic curriculum as relative chapter. First aid does not directly correlate with home economics curriculum but should be studied in preparation for accident which could happen in practical class. Forth, with regards to research trends by research method, quantitative research (89.1%) is mostly used and both research study (70.4%) and experimental research (18.7%) are used the most frequently. In particular, researches on the actual condition of safety education and experimental studies for effectiveness verification take most of research method. As qualitative studies, there are phenomenological study (3.1%) and case study (3.1%) related to actual conditions of safety accidents. 10 papers (2.4%) are mixture of quantitative and qualitative research and some research conducted research study and experimental research at the same time (0.9%). With regards to subject of study, human environments (87.5%) are more than physical environments (12.5) and students (48.4%) are more than teachers and school parents (20.6%). As the subject of physical environments, school (6.5%) is the most but home environment is none. As a result of the study, research for the development of evaluation tool for evaluating safety education, occupational safety and lifelong education should be conducted from this time forward. In addition, the object of study shall be expanded to both human environments in terms of entire life and physical environments for home. An in-depth qualitative research should be needed by observing and meeting with each student.