• Agribusiness and Information Management
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• v.8 no.1
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• pp.17-26
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• 2016

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world's area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On $23^{rd}$ November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called 'Andhra Pradesh Micro Irrigation Project (APMIP)', first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied ($X_1$) and fertigation cost ($X_2$) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of 'Information and Communication Technology (ICT) and its applications in irrigation water management' for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.163-178
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• 2014

Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

• Radiation Oncology Journal
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• v.23 no.2
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• pp.98-105
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• 2005

Purpose : The objective of our study was to evaluate the immunohistochemical expression of p53 and bax proteins as prognostic markers in FIGO stage IIb invasive squamous cell carcinoma of the uterine cervix. Materials and Methods : Sixty-five cases of squamous cell carcinoma of the cervix (stage IIb) that were diagnosed from October 1995 to December 2003 were analyzed retrospectively for the bax and p53 expression. These expressions were determined immunohistochemically and they were correlated to the patients' overall survival and disease-free survival. Results : The overall 5-year survival (OS) rate and the disease-free survival (DFS) rate were $65.1\%$ and $62.9\%$, respectively. p53 and bax immunoreactivity was seen in $26.2\%$ and $52.3\%$ of cases, respectively, with variable levels of expression. On the univariate analysis, only p53 positivity correlated with poor survival in DFS (log-rank test p=0.027), but this significance was not maintained on multivariated analysis by Cox's regression. The nine cases with the immunophenotype ps3+/bax- had the poorest survival. Conclusion : Neither p53 nor bax expression are Independent predictors of the prognosis for stage IIb cervical squamous cancers. Evaluation of p53 and bax co-expression may affect the clinical outcome and further investigation is needed.

• 한국노년학
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• v.38 no.3
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• pp.551-567
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• 2018

Demographic and socio-structural information is useful to identify potential welfare recipients who are in need of disease-prevention and intervention services. Thus, the present study aims to explore the differences in grip strength among middle and old-aged adults by living conditions and by living area. The 5th wave data of Korean Longitudinal Study of Aging was utilized. The dependent variable was grip strength, and the independent variables were living alone (living alone or not) and living area (city or non-city). Covariates were age, education, log-transformed household income, spouse existence, body mass index, self-rated health conditions, depressive symptoms, cognitive function, smoking, regular exercise, frequency of meeting with friends, and the number of social participation. Regression analysis was performed for middle-aged men, middle-aged women, old-aged men, and old-aged women, respectively. ANOVA and Chi-test were additionally used to specifically discuss significant results. Cross-sectional weight was applied to all analyses. According to the results, living alone and living area did not have significant effects on grip strength among middle-aged men, old-aged men, and old-aged women. In middle-aged women, however, living alone and living area were significantly associated with grip strength. To be specific, middle-aged women who lived alone in rural areas had the lowest grip strength compared to other middle-aged women. Additional analysis showed that middle-aged women who lived alone in rural areas had risk factors, such as low education level, low income, or high depressive symptoms. It implies that middle-aged women living alone in rural areas may have physical health risks, so they might be in need of disease prevention. This study is meaningful in that it can provide reliable information on the latent welfare recipients by using representative panel data and applying weight values.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.87-96
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• 2022

Recently, the purchase of fresh-cut produce and meal kits has increased. Ready-to-eat (RTE) fresh-cut products have potentially hazard of cross-contamination of various microorganisms in the processes of peeling, slicing, dicing, and shredding. There are frequent cases of protozoa food poisoning, such as Cyclospora and Cryptosporidium, caused by fresh-cut products. The objective of the study is to investigate the microbiological qualities of various types of RTE fresh-cut products in the domestic on/offline markets. RTE fresh-cut fruits cup (n=100), fresh-cut vegetables (n=50), and vegetables in meal kits (Vietnamese spring rolls and white radish rolls kits, n=50) were seasonally analyzed. The contamination levels of hygienic indicator organisms, yeast and mold (YM), and foodborne pathogens (Bacillus cereus, Staphylococcus aureus, Listeria monocytogenes, Salmonella spp., and Escherichia coli O157:H7) were monitored. Overall, the lowest microbiological qualities of meal kits vegetables were observed, followed by RTE fresh-cut fruits cup and fresh-cut vegetables. Contamination levels of total aerobic bacteria, coliforms, and YM in meal kits vegetables were 5.91, 3.90, and 4.71 logs CFU/g, respectively. From the qualitative analysis, 6 out of 200 RTE fresh-cut products (3%) returned positive result for S. aureus. From the quantitative analysis, the contamination levels of S. aureus in purple cabbage from a meal-kit and fresh-cut pineapple were below the acceptable limit (100 CFU/g). Staphylococcus enterotoxin seg and sei genes were detected in RTE fresh-cut celery and red cabbage from meal-kits, respectively. S. aureus contamination must be carefully controlled during the manufacturing processes of RTE fresh-cut products. Neither Cyclospora cayetanensis nor Cryptosporidium parvum was detected in the samples of RTE fresh-cut products and vegetables from meal-kits from the Korean retail markets.

• Journal of Chest Surgery
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• v.55 no.2
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• pp.126-142
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• 2022

Background: Thymic epithelial tumors (TETs) are rare, and information regarding their surgical outcomes and prognostic factors has rapidly changed in the past few decades. We analyzed surgical treatment practices for TETs and outcomes in terms of overall survival (OS) and freedom from recurrence (FFR) during a 13-year period in Korea. Methods: In total, 1,298 patients with surgically resected TETs between 2000 and 2013 were enrolled retrospectively. OS and FFR were calculated using the Kaplan-Meier method and evaluated with the log-rank test. Prognostic factors for OS and FFR were analyzed with multivariable Cox regression. Results: A total of 1,098 patients were diagnosed with thymoma, and 200 patients were diagnosed with thymic carcinoma. Over the study period, the total number of patients with surgically treated TETs and the proportion of patients who underwent minimally invasive thymic surgery (MITS) increased annually. The 5-year and 10-year survival rates of surgically treated TETs were 91.0% and 82.1%, respectively. The 5-year and 10-year recurrence rates were 86.3% and 80.0%, respectively. The outcomes of surgically treated TETs improved over time. Multivariable Cox hazards analysis for OS, age, tumor size, and Masaoka-Koga stage were independent predictors of prognosis. The World Health Organization classification and tumor-node-metastasis (TNM) staging were also related to the prognosis of TETs. Conclusion: Surgical treatment of TETs achieved a good prognosis with a recent increase in MITS. The M-K stage was the most important prognostic factor for OS and FFR. The new TNM stage could also be an effective predictor of the outcomes of TETs.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Chest Surgery
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• v.38 no.1 s.246
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• pp.44-49
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• 2005

Although thymomas are relatively common mediastinal tumors, to date not only has a universal system of pathologic classification not been established but neither has a clearly defined predictable relationship between treatment and prognosis been made. Recently, a new guideline for classification was reported by WHO, and efforts, based on this work, have been made to better define the relationship between treatment and pro­gnostic outcome. In the present study a comparative analysis between the WHO classification and Masaoka stage system with the clinical disease pattern was conducted. Material and Method: A total of 98 patients undergoing complete resection for mediastinal thymoma between Juanuary 1993 and June 2003 were included in the present study. The male female ratio was 48 : 50 and the mean age at operation was $49.6{\pm}13.9\;years.$ A retrospective analytic comparison studying the relationship between the WHO classification and the Masaoka stage system with the clinical disease pattern of thymoma was conducted. Pathologic slide specimens were carefully examined, details of postoperative treatment were documented, and a relationship with the prognostic outcome and recurrence was studied. Result: There were 7 patients in type A according to the WHO system of classification, 14 in AB, 28 in B 1, 23 in B2, 18 in B3, and 9 in type C. The study of the relationship between the Masaoka stage and WHO classification system showed 4 patients to be in WHO system type A, 7 in type AB, 22 in B 1, 17 in B2, and 3 in type B3 among 53 $(54{\%})$ patients shown to be in Masaoka stage I. Among 28 $(28.5{\%})$ patients in Masaoka stage II system, there were 2 patients in type A, 7 in AB, 4 in B 1, 2 in B2, 8 in B3, and 5 in type C. Among 15 $(15.3{\%})$ in Masaoka stage III, there were 1 patient in type B1, 3 in B2, 7 in B3, and 4 in type C. Finally, among 2 $(2{\%})$ patients found to be in Masaoka stage IV there was 1 patient in type B1, and 1 in type B2. The mean follow up duration was $28{\pm}6.8$ months. There were 3 deaths in the entire series of which 2 were in type B2 (Masaoka stages III and IV), and 1 was in type C (Masaoka stage II). Of the patients that experienced relapse, 6 patients remain alive of which 2 were in type B2 (Masaoka III), 2 in type B3 (Masaoka I and III) and 2 in type C (Masaoka stage II). The 5 year survival rate by the Kaplan-Meier method was $90{\%}$ for those in type B2 WHO classification system, $87.5{\%}$ for type C. The 5 year freedom from recurrence rate was $80.7{\%}$ for those in WHO type B2, $81.6{\%}$ for those in type B3, and $50{\%}$ for those in type C. By the Log-Rank method, a statistically significant correlation between survival and recurrence was found with the WHO system of classification (p<0.05). An analysis of the relationship between the WHO classification and Masaoka stage system using the Spearman correction method, showed a slope=0.401 (p=0.023), showing a close correlation. Conclusion: As type C of the WHO classification system is associated with a high postoperative mortality and recurrence rate, aggressive treatment postoperatively and meticulous follow up are warranted. The WHO classification and Masaoka stage system were found to have a close relationship with each other and either the WHO classification method or the Masaoka stage system may be used as a predict prognostic outcome of Thymoma.

• Radiation Oncology Journal
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• v.13 no.4
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• pp.359-368
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• 1995

Purpose : This is a retrospective analysis for pattern of failure, survival rate and prognostic factors of 114 patients with histologically proven invasive cancer of the uterine cervix treated with definitive irradiation. Materials and Methods : One hundred fourteen patients with invasive carcinoma of the cervix were treated with a combination of intracavitary irradiation using Fletcher-Suit applicator and external beam irradiation by 6MV X-ray at the Ewha Womans University Hospital between March 1982 and Mar 1990. The median age was 53 years(range:30-77 years). FIGO stage distribution was 19 for IB, 23 for IIA, 42 for IIB, 12 for IIIA and 18 for IIIB. Summation dose of external beam and intracavitary irradiation to point A was 80-90 Gy(median:8580 cGy) in early stage(IB-IIA) and 85-100 Gy(median:8850 cGy) in advanced stage(IIB-IIIB). Kaplan-Meier method was used to estimate the survival rate and multivariate analysis for progrostic factors was performed using the Log likelihood for Weibull Results : The pelvic failure rates by stage were $10.5{\%}$ for IB. $8.7{\%}$ for IIA, $23.8{\%}$ for IIB, $50.0{\%}$ for IIIA and $38.9{\%}$ for IIIB. The rate of distant metastasis by stage were $0{\%}$ for IB, $8.7{\%}$ for IIA, $4.8{\%}$ for IIB. $0{\%}$ for IIIA and $11.1{\%}$ for IIIB. The time of failure was from 3 to 50 months and with median of 15 months after completion of radiation therapy. There was no significant coorelation between dose to point A($\leq$90 Gy vs >90 Gy) and pelvic tumor control(P>0.05). Incidence rates of grade 2 rectal and bladder complications were $3.5{\%}$(4/114) and $7{\%}$(8/114), respectively and 1 patient had sigmoid colon obstruction and 1 patient had severe cystitis. Overall 5-year survival rate was $70.5{\%}$ and disease-free survival rate was $53.6{\%}$. Overall 5-year survival rate by stage was $100{\%}$ for IB, $76.9{\%}$ for IIA, $77.6{\%}$ for IIB $87.5{\%}$ for IIIA and $69.1{\%}$ for IIIB. Five-rear disease-free survival rate by stage was $81.3{\%}$ for IB, $67.9{\%}$ for IIA, $46.8{\%}$ for IIB, $45.4{\%}$ for IIIA and $34.4{\%}$ for IIIB. The prognostic factors for disease-free survival rate by multivariate analysis was performance status(p= 0.0063) and response rate after completion of radiation therapy(p= 0.0026) but stage, age and radiation dose to point A were not siginificant. Conclusion : The result of radiation therapy for early stage of the uterine cervix cancer was relatively good but local control rate and survival rate in advanced stage were poor inspite of high dose irradiation to point A above 90 Gy. Prospective randomized studies are recommended to establish optimal tumor doses for various stages and volume of carcinoma of uterine cervix, And ajuvant chemotherapy or radiation-sensitizing agents must be considered to increase the pelvic control and survival rate in advanced cancer of uterine cervix.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.