• Title/Summary/Keyword: media analysis

Search Result 6,438, Processing Time 0.042 seconds

Comparative Analysis of Image Quality and Adverse Events between Iopamidol 250 and Ioversol 320 in Hepatic Angiography for Transcatheter Arterial Chemoembolization (경동맥 화학색전술을 위한 간동맥 혈관조영술에서 Ioversol 320과 비교한 Iopamidol 250의 영상 화질 비교 분석과 조영제 유해반응 평가)

  • Min Jae Gu;Jae Hyuck Yi;Young Hwan Kim;Hee Jung Lee;Ung Rae Kang;Seung Woo Ji
    • Journal of the Korean Society of Radiology
    • /
    • v.81 no.1
    • /
    • pp.166-175
    • /
    • 2020
  • Purpose This study aimed to compare the image quality and adverse events between Iopamidol 250 and Ioversol 320 usage during transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma (HCC). Materials and Methods Medical records and hepatic angiography from 113 patients who underwent TACE with Iopamidol 250 (44 patients) and Ioversol 320 (69 patients) were retrospectively reviewed. Vessel perception on hepatic angiography was graded into three categories by two radiologists for hepatic subsegmental arteries, the right gastroepiploic artery, right gastric artery, and pancreaticoduodenal artery. Imaging concordance was assessed by comparing the number of detected HCCs on hepatic angiography and CT. The adverse events before and after hepatic angiography were evaluated. Results The mean vessel perception scores were 2.92 and 2.94 for Iopamidol 250 and Ioversol 320, respectively. The imaging concordance was 31 (70.5%) and 46 (66.7%) patients for Iopamidol 250 and Ioversol 320, respectively. There were no statistical differences in vessel perception or imaging concordance (p > 0.05). One and six patients experienced nausea for Iopamidol 250 and Ioversol 320, respectively. There was no statistical difference in adverse events (p = 0.24). Conclusion Iopamidol 250 can be used in hepatic angiography for TACE without significant difference in image quality or occurrence of adverse events from Ioversol 320.

The synthesis of dextran from rice hydrolysates using Gluconobacter oxydans KACC 19357 bioconversion (Gluconobacter oxydans 생물전환을 통한 쌀 가수분해물 유래 dextran 합성)

  • Seung-Min Baek;Hyun Ji Lee;Legesse Shiferaw Chewaka;Chan Soon Park;Bo-Ram Park
    • Food Science and Preservation
    • /
    • v.31 no.1
    • /
    • pp.149-160
    • /
    • 2024
  • Dextran is a glucose homo-polysaccharide with a predominantly α-1,6 glycosidic linkage of microbial source and is known to be produced primarily by lactic acid bacteria. However, it can also be obtained through the dextran dextrinase of acetic acid bacteria (Gluconobacter oxydans). The dextrin-based dextran was obtained from rice starch using G. oxydans fermentation of rice hydrolysate, and its properties were studied. Both dextrin- and rice hydrolysate-added media maintained the OD value of 6 after 20 h of incubation with acetic acid bacteria, and the gel permeation chromatography (GPC) analysis of the supernatant after 72 h of incubation confirmed that a polymeric material with DP of 480 and 405, which was different from the composition of the substrate in the medium, was produced. The glucose linkage pattern of the polysaccharide was confirmed using the proton nuclear magnetic resonance (1H-NMR) and the increased α-1,4:α-1,6 bond ratio from 0.23 and 0.13 to 1:2.37 and 1:4.4, respectively, indicating that the main bonds were converted to α-1,6 bonds. The treatment of dextrin with a rat-derived alpha-glucosidase digestive enzyme resulted in a slow release of glucose, suggesting that rice hydrolysate can be converted to dextran using acetic acid bacteria with glycosyltransferase activity to produce high-value bio-materials with slowly digestible properties.

Clickstream Big Data Mining for Demographics based Digital Marketing (인구통계특성 기반 디지털 마케팅을 위한 클릭스트림 빅데이터 마이닝)

  • Park, Jiae;Cho, Yoonho
    • Journal of Intelligence and Information Systems
    • /
    • v.22 no.3
    • /
    • pp.143-163
    • /
    • 2016
  • The demographics of Internet users are the most basic and important sources for target marketing or personalized advertisements on the digital marketing channels which include email, mobile, and social media. However, it gradually has become difficult to collect the demographics of Internet users because their activities are anonymous in many cases. Although the marketing department is able to get the demographics using online or offline surveys, these approaches are very expensive, long processes, and likely to include false statements. Clickstream data is the recording an Internet user leaves behind while visiting websites. As the user clicks anywhere in the webpage, the activity is logged in semi-structured website log files. Such data allows us to see what pages users visited, how long they stayed there, how often they visited, when they usually visited, which site they prefer, what keywords they used to find the site, whether they purchased any, and so forth. For such a reason, some researchers tried to guess the demographics of Internet users by using their clickstream data. They derived various independent variables likely to be correlated to the demographics. The variables include search keyword, frequency and intensity for time, day and month, variety of websites visited, text information for web pages visited, etc. The demographic attributes to predict are also diverse according to the paper, and cover gender, age, job, location, income, education, marital status, presence of children. A variety of data mining methods, such as LSA, SVM, decision tree, neural network, logistic regression, and k-nearest neighbors, were used for prediction model building. However, this research has not yet identified which data mining method is appropriate to predict each demographic variable. Moreover, it is required to review independent variables studied so far and combine them as needed, and evaluate them for building the best prediction model. The objective of this study is to choose clickstream attributes mostly likely to be correlated to the demographics from the results of previous research, and then to identify which data mining method is fitting to predict each demographic attribute. Among the demographic attributes, this paper focus on predicting gender, age, marital status, residence, and job. And from the results of previous research, 64 clickstream attributes are applied to predict the demographic attributes. The overall process of predictive model building is compose of 4 steps. In the first step, we create user profiles which include 64 clickstream attributes and 5 demographic attributes. The second step performs the dimension reduction of clickstream variables to solve the curse of dimensionality and overfitting problem. We utilize three approaches which are based on decision tree, PCA, and cluster analysis. We build alternative predictive models for each demographic variable in the third step. SVM, neural network, and logistic regression are used for modeling. The last step evaluates the alternative models in view of model accuracy and selects the best model. For the experiments, we used clickstream data which represents 5 demographics and 16,962,705 online activities for 5,000 Internet users. IBM SPSS Modeler 17.0 was used for our prediction process, and the 5-fold cross validation was conducted to enhance the reliability of our experiments. As the experimental results, we can verify that there are a specific data mining method well-suited for each demographic variable. For example, age prediction is best performed when using the decision tree based dimension reduction and neural network whereas the prediction of gender and marital status is the most accurate by applying SVM without dimension reduction. We conclude that the online behaviors of the Internet users, captured from the clickstream data analysis, could be well used to predict their demographics, thereby being utilized to the digital marketing.

Structural Properties of Social Network and Diffusion of Product WOM: A Sociocultural Approach (사회적 네트워크 구조특성과 제품구전의 확산: 사회문화적 접근)

  • Yoon, Sung-Joon;Han, Hee-Eun
    • Journal of Distribution Research
    • /
    • v.16 no.1
    • /
    • pp.141-177
    • /
    • 2011
  • I. Research Objectives: Most of the previous studies on diffusion have concentrated on efficacy of WOM communication with the use of variables at individual level (Iacobucci 1996; Midgley et al. 1992). However, there is a paucity of studies which investigated network's structural properties as antecedents of WOM from the perspective of consumers' sociocultural propensities. Against this research backbone, this study attempted to link the network's structural properties and consumer' WOM behavior on cross-national basis. The major research objective of this study was to examine the relationship between network properties and WOM by comparing Korean and Chinese consumers. Specific objectives of this research are threefold; firstly, it sought to examine whether network properties (i.e., tie strength, centrality, range) affect WOM (WOM intention and quality of WOM). Secondly, it aimed to explore the moderating effects of cutural orientation (uncertainty avoidance and individuality) on the relationship between network properties and WOM. Thirdly, it substantiates the role of innovativeness as antecedents to both network properties and WOM. II. Research Hypotheses: Based on the above research objectives, the study put forth the following research hypotheses to validate. ${\cdot}$ H 1-1 : The Strength of tie between two counterparts within network will positively influence WOM effectivenes ${\cdot}$ H 1-2 : The network centrality will positively influence the WOM effectiveness ${\cdot}$ H 1-3 : The network range will positively influence the WOM effectiveness ${\cdot}$ H 2-1 : The consumer's uncertainty avoidance tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 2-2 : The consumer's individualism tendency will moderate the relationship between network properties and WOM effectiveness ${\cdot}$ H 3-1 : The consumer's innovativeness will positively influence the social network properties ${\cdot}$ H 3-2 : The consumer's innovativeness will positively influence WOM effectiveness III. Methodology: Through a pilot study and back-translation, two versions of questionnaire were prepared, one in Korean and the other in Chinese. The chinese data were collected from the chinese students enrolled in language schools in Suwon city in Korea, while Korean data were collected from students taking classes in a major university in Seoul. A total of 277 questionnaire were used for analysis of Korean data and 212 for Chinese data. The reason why Chinese students living in Korea rather than in China were selected was based on two factors: one was to neutralize the differences (ie, retail channel availability) that may arise from living in separate countries and the second was to minimize the difference in communication venues such as internet accessibility and cell phone usability. SPSS 12.0 and AMOS 7.0 were used for analysis. IV. Results: Prior to hypothesis verification, mean differences between the two countries in terms of major constructs were performed with the following result; As for network properties (tie strength, centrality and range), Koreans showed higher scores in all three constructs. For cultural orientation traits, Koreans scored higher only on uncertainty avoidance trait than Chinese. As a result of verifying the first research objective, confirming the relationship between network properties and WOM effectiveness, on Korean side, tie strength(Beta=.116; t=1.785) and centrality (Beta=.499; t=6.776) significantly influenced on WOM intention, and similar finding was obtained for Chinese side, with tie strength (Beta=.246; t=3.544) and centrality (Beta=.247; t=3.538) being significant. However, with regard to WOM argument quality, Korean data yielded only centrality (Beta=.82; t=7.600) having a significant impact on WOM, whereas China showed both tie strength(Beat=.142; t=2.052) and centrality(Beta=.348; t=5.031) being influential. To answer for the second research objective addressing the moderating role of cultural orientation, moderated regression anaylsis was performed and the result showed that uncertainty avoidance moderated between network range and WOM intention for both Korea and China, But for Korea, the uncertainty avoidance moderated between tie strength and WOM quality, while for China it moderated between network range and WOM intention. And innovativeness moderated between tie strength and WOM intention for Korea but it moderated between network range and WOM intention for China. As a result of analysing for third research objective, we found that for Korea, innovativeness positively influenced centrality only (Beta=.546; t=10.808), while for China it influenced both tie strength (Beta=.203; t=2.998) and centrality(Beta=.518; t=8.782). But for both countries alike, the innovativeness influenced positively on WOM (WOM intention and WOM quality). V. Implications: The study yields the two practical implications. Firstly, the result suggests that companies targeting multinational customers need to identify segments which are susceptible to the positive WOM and WOM information based on individual traits such as uncertainty avoidance and individualism and based on that, develop marketing communication strategy. Secondly, the companies need to divide the market on Roger's five innovation stages and based on this information, enforce marketing strategy which utilizes social networking tools such as public media and WOM. For instance, innovator and early adopters, if provided with new product information, will be able to capitalize upon the network advantages and thus add informational value to network operations using SNS or corporate blog.

  • PDF

The Analyses of Treatment Results and Prognostic Factors in Supradiaphragmatic CS I-II Hodgkin's Disease (횡경막상부에 국한된 임상적 병기 1-2기 호지킨병에서 치료 결과와 예후 인자의 분석)

  • Park Won;Suh Chang Ok;Chung Eun Ji;Cho Jae Ho;Chung Hyun Cheol;Kim Joo Hang;Roh Jae Kyung;Hahn Jee Sook;Kim Gwi Eon
    • Radiation Oncology Journal
    • /
    • v.16 no.2
    • /
    • pp.147-157
    • /
    • 1998
  • Purpose : The aim of this retrospective study is to assess the necessity of s1aging laparotomy in the management of supradiaphragmatic CS I-II Hodgkin's disease. Prognostic factors and the usefulness of prognostic factor groups were also analyzed. Materials and Methods : From 1985 to 1995, fifty one Patients who were diagnosed as supradiaphragmatic CS I-II Hodgkin's disease at Yonsei Cancer Center in Seoul, Korea were enrolled in this study Age range was 4 to 67 with median age of 30. The number of patients with each CS IA, II A, and IIB were 16, 25, and 10, respectively. Radiotherapy(RT) was delivered using 4 or 6 MV photon beam to a total dose of 19.5 to 55.6Gy (median dose : 45Gy) with a 1.5 to 1.BGy per fraction. Chemotherapy(CT) was given in 2-12 cycles(median : 6 cycles). Thirty one Patients were treated with RT alone, 4 patients with CT alone and 16 patients with combined chemoradiotherapy. RT volumes varied from involved fields(3), subtotal nodal fields(18) or mantle fields(26). Results : Five-year disease-free survival rate(DFS) was $78.0\%$ and overall survival rate(05) was $87.6\%$. Fifty Patients achieved a complete remission after initial treatment and 8 patients were relapsed. Salvage therapy was given to 7 patients, 1 with RT alone, 4 with CT alone, 2 with RT+CT. Only two patients were successfully salvaged. Feminine gender and large media-stinal adenopathy were significant adverse prognostic factors in the univariate analysis for DFS. The significant adverse prognostic factors of OS were B symptom and clinical stage. When patients were analyzed according to European Organization for Research and Treatment of Cancer(EORTC) prognostic factor groups, the DFS in Patients with very favorable, favorable and unfavorable group was 100, 100 and $55.8\%$(p<0.05), and the 05 in each patients' group was 100, 100 and $75.1\%$(p<0.05), respectively. In very favorable and favorable groups, the DFS and 05 were all $100\%$ by RT alone, but in unfavorable group, RT with CT had a lesser relapse rate than RT alone. The subtotal nodal irradiation had better OFS than mantle RT in patients treated with RT. Conclusion : In present study, the DFS and OS in patients who did not undergo s1aging laparotomy were similar with the results in the literatures of which patients were surgically staged. Therefore, we may suggest that staging laparotomy would not influence the outcome of treatments. In univariate analysis, gender, large mediastinal adenopathy. B symptoms and clinical stage were significant prognostic factors for the survival rate. We confirm the usefulness of EORTC prognostic factor groups which may be a good.

  • PDF

A Study on the Distribution, Contents and Types of Stone Inscription of Wuyi-Gugok in China (중국 무이구곡 바위글씨(石刻)의 분포와 내용 및 유형에 관한 연구)

  • Rho, Jae-Hyun;Cheng, Zhao-Xia;Kim, Hong-Gyun
    • Journal of the Korean Institute of Traditional Landscape Architecture
    • /
    • v.38 no.1
    • /
    • pp.115-131
    • /
    • 2020
  • Through literature research and field investigation, this paper attempts to study the distribution, morphology and the typification of the visual and perceptual stone inscription in Wuyi-Gugok of China. The results are as follows: First, there are 350 stone inscriptions in total from the 1st Gok to 9th Gok in Wuyi-Gugok. Second, according to the analysis of the stone inscription distribution, 74(21.2%) stone inscriptions in the 5th Gok, 67(19.2%) in the 6th Gok, 65(18.6%) in the 1st Gok, 60(17.2%) in the 2nd Gok and 53(15.2%) in the 4th Gok are confirmed. The above five Goks contain 319(91.1%) stone inscriptions, so they have rich cultural landscape. Third, according to the survey, the number of the stone inscriptions existed in the Sugwangseok of the 1st Gok are 41(22.6%), in the Homagan of Cheonyubong of the 6th Gok are 29(8.3%), in the Jesiam of the 4th Gok are 23(6.6%), in the Nyeongam of the 2nd Gok are 22(6.3%), in the Hyangseongam of the 6th Gok are 21(6%), in the Unwa of the 5th Gok are 19(5.4%), in the Bokhoam of the 5th Gok are 18(5.1%), in the Eunbyeongbong of the 5th Gok are 17(4.9%), in the Daejangbong of the 4th Gok are 14(4%), in the Daewangbong of the 1st Gok and the Geumgokam of the 4th Gok are 12(3.4%). Thus, a total of 228 (65.1%) stone inscriptions are concentrated in these 11 sites, which represent the popularity and cultural value of these rocks. Fourth, the stone inscription of Wuyi-Gugok, praising the landform and topographical geological landscape of Mount Wuyi, mainly describe the scenic name of each Gok related to Zhu Xi's Gugok culture, appreciate Zhu Xi's tracks and the stone inscription in the sacred land of Neo-Confucianism culture, and also record the Confucian edification of mencius thoughts, Muigun(武夷君) and the myths and legends related to the site names of Wuyi mountain, which can remind people of the worldview of the celestial paradise where the gods live and the fairyland of the land of peach blossoms. In addition, it indicates that the historical and cultural landscape, which is full of colorful history and myths and legends, including allusions related to Confucian, buddhist and Taoist celebrities and the ancestor ancient things related to traditional culture of China is very diverse. Fifth, the results of the classification, based on the content of the stone inscription in Wuyi-Gugok, are classified as the scenery name inscription, the praise scene inscription, the recording travel inscription, the recording event inscription, the philosophy inscription, the expressing emotion inscription, the religion inscription, the inscription for auspiciousness, the slogan and expressing ambition inscription and the official document notice inscription, among which there are 102(29.1%) praise scene inscriptions, 93(26.6%) scenery name inscriptions and 61(17.4%) recording travel inscriptions. The stone inscriptions of Wuyi-Gugok have the characteristics of the special emphasis on scenery names, landscape praise and commemorative tours. Sixth, the analysis of the intertext between the 「Figure of Wuyi-Gugok」 and Wuyi-Gugok rock letters, in the study found that the method of propagation between media was mostly the method of propagation of quotations and maintained intermedia through extension, repetition, extension, and compression.

Interlaboratory Comparison of Blood Lead Determination in Some Occupational Health Laboratories in Korea (일부 산업보건기관들의 혈중연 분석치 비교)

  • Ahn, Kyu Dong;Lee, Byung Kook
    • Journal of Korean Society of Occupational and Environmental Hygiene
    • /
    • v.5 no.1
    • /
    • pp.8-15
    • /
    • 1995
  • The reliable measurement of metal in biological media in human body is one of critical indicators for the proper evaluation of its toxic effect on human health. Recently in Korea the necessity of quality assurance of measurement in occupational health and occupational hygiene fields brought out regulatory quality control program. Lead is often used as a standard metal for the program in both fields of occupational health and hygiene. During last 20 years lead poisoning was prevalent in Korea and still is one of main heavy metal poisoning and the capability of the measurement of blood lead is one of prerequisites for institute of specialized occupational health in Korea. Furthermore blood lead is most important indicator to evaluate lead burden of human exposure to lead and the reliable and accurate analysis is most needed whenever possible. To evaluate the extent of the interlaboratory differences of blood lead measurement in several well-known institute specialized in occupational health in Korea, authors prepared 68 blood samples from two storage battery industries and all samples were divided into samples with 2 ml. One set of 68 samples were analyzed by authors's laboratory(Soonchunhyang University Institute of Industrial Medicine: SIIM) and 40 samples of other set were analyzed by C University Institute of Industrial Medicine(CIIM) and the rest 28 samples of other set were analyzed by Japanese institute(K Occupational Health Center:KOHC). Authors also prepared test bovine samples which were obtained from Japanese Federation of Occupational Health Organization (JFOHO) for quality control. Authors selected 2 other well-known occupational health laboratories and one laboratory specialized for instrumental analysis. A total of 6 laboratories joined the interlaboratory comparison of blood lead measurement and the results obtained were as follows: 1. There was no significant difference in average blood lead between SIIM and CIIM in different group of blood lead concentration, and the relative standard deviation of two laboratories was less than 3.0%. On the other hand, there was also no significant difference of average blood lead between SIIM and KOHC with relative standard deviation of 6.84% as maximum. 2. Taking less than 15% difference of mean or less than 6 ug/dl difference in below 40 ug/dl in whole blood as a criteria of agreement of measurement between two laboratories, agreement rates were 87.5%(35/40) and 78.6%(22/28) between SIIM and CIIM, SIIM and KOHC respectively. 3. The correlation of blood lead between SIIM and CIIM was 0.975 (p=0.0001) and the regression equation was SIIM = 2.19 + 0.9243 ClIM, whereas the correlation between SUM and KOHC was O.965(p=0.0001) with the equation of SIIM = 1.91 + 0.9794 KOHC. 4. Taking the reference value as a dependent variable and each of 6 laboratories's measurement value as a independent variable, the determination coefficient($R^2$) of simple regression equations of blood lead measurement for bovine test samples were very high($R^2>0.99$), and the regression coefficient(${\beta}$) was between 0.972 and 1.15 which indicated fairly good agreement of measurement results.

  • PDF

Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
    • /
    • v.15 no.4
    • /
    • pp.61-85
    • /
    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

  • PDF
  • Subject-Balanced Intelligent Text Summarization Scheme (주제 균형 지능형 텍스트 요약 기법)

    • Yun, Yeoil;Ko, Eunjung;Kim, Namgyu
      • Journal of Intelligence and Information Systems
      • /
      • v.25 no.2
      • /
      • pp.141-166
      • /
      • 2019
    • Recently, channels like social media and SNS create enormous amount of data. In all kinds of data, portions of unstructured data which represented as text data has increased geometrically. But there are some difficulties to check all text data, so it is important to access those data rapidly and grasp key points of text. Due to needs of efficient understanding, many studies about text summarization for handling and using tremendous amounts of text data have been proposed. Especially, a lot of summarization methods using machine learning and artificial intelligence algorithms have been proposed lately to generate summary objectively and effectively which called "automatic summarization". However almost text summarization methods proposed up to date construct summary focused on frequency of contents in original documents. Those summaries have a limitation for contain small-weight subjects that mentioned less in original text. If summaries include contents with only major subject, bias occurs and it causes loss of information so that it is hard to ascertain every subject documents have. To avoid those bias, it is possible to summarize in point of balance between topics document have so all subject in document can be ascertained, but still unbalance of distribution between those subjects remains. To retain balance of subjects in summary, it is necessary to consider proportion of every subject documents originally have and also allocate the portion of subjects equally so that even sentences of minor subjects can be included in summary sufficiently. In this study, we propose "subject-balanced" text summarization method that procure balance between all subjects and minimize omission of low-frequency subjects. For subject-balanced summary, we use two concept of summary evaluation metrics "completeness" and "succinctness". Completeness is the feature that summary should include contents of original documents fully and succinctness means summary has minimum duplication with contents in itself. Proposed method has 3-phases for summarization. First phase is constructing subject term dictionaries. Topic modeling is used for calculating topic-term weight which indicates degrees that each terms are related to each topic. From derived weight, it is possible to figure out highly related terms for every topic and subjects of documents can be found from various topic composed similar meaning terms. And then, few terms are selected which represent subject well. In this method, it is called "seed terms". However, those terms are too small to explain each subject enough, so sufficient similar terms with seed terms are needed for well-constructed subject dictionary. Word2Vec is used for word expansion, finds similar terms with seed terms. Word vectors are created after Word2Vec modeling, and from those vectors, similarity between all terms can be derived by using cosine-similarity. Higher cosine similarity between two terms calculated, higher relationship between two terms defined. So terms that have high similarity values with seed terms for each subjects are selected and filtering those expanded terms subject dictionary is finally constructed. Next phase is allocating subjects to every sentences which original documents have. To grasp contents of all sentences first, frequency analysis is conducted with specific terms that subject dictionaries compose. TF-IDF weight of each subjects are calculated after frequency analysis, and it is possible to figure out how much sentences are explaining about each subjects. However, TF-IDF weight has limitation that the weight can be increased infinitely, so by normalizing TF-IDF weights for every subject sentences have, all values are changed to 0 to 1 values. Then allocating subject for every sentences with maximum TF-IDF weight between all subjects, sentence group are constructed for each subjects finally. Last phase is summary generation parts. Sen2Vec is used to figure out similarity between subject-sentences, and similarity matrix can be formed. By repetitive sentences selecting, it is possible to generate summary that include contents of original documents fully and minimize duplication in summary itself. For evaluation of proposed method, 50,000 reviews of TripAdvisor are used for constructing subject dictionaries and 23,087 reviews are used for generating summary. Also comparison between proposed method summary and frequency-based summary is performed and as a result, it is verified that summary from proposed method can retain balance of all subject more which documents originally have.

    Stock Price Prediction by Utilizing Category Neutral Terms: Text Mining Approach (카테고리 중립 단어 활용을 통한 주가 예측 방안: 텍스트 마이닝 활용)

    • Lee, Minsik;Lee, Hong Joo
      • Journal of Intelligence and Information Systems
      • /
      • v.23 no.2
      • /
      • pp.123-138
      • /
      • 2017
    • Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.


    (34141) Korea Institute of Science and Technology Information, 245, Daehak-ro, Yuseong-gu, Daejeon
    Copyright (C) KISTI. All Rights Reserved.