• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Korean Journal of Psychosomatic Medicine
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• v.12 no.2
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• pp.165-173
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• 2004

Objectives: Diabetes mellitus is a heterogeneous, chronic, progressive disease characterized by hyperglycemia and abnormality in protein, carbohydrate, fat metabolism. Recent studies have reorted two times prevalence of depression in individuals with diabetes compared to individuals without diabetics. This study was designed to investigate glycemic controls, anxiety, alexithymia, stress responses between depressed diabetic patients and non-depressed diabetic patients. Methods The subjects were 60 diabetic patients(mean age : $50.3{\pm}9.7$ years, 31 men and 29 women) who were confirmed to have diabetes depending on the laboratory findings as welt as clinical symptoms at the St. Vincent Hospital Diabetes Clinic, from Mar. 2004 to Sep. 2004. Laboratory test including, blood chemistry. glycated hemoglobin, urinalysis for proteinuria and Korean version of Beck Depression Inventory(BDI), State and Trait Anxiety Inventory(STAI), Toronto Alexithymia Scale(TAS) and Stress Response Inventory(SRI) were used for assessment. Based on BDI scores, all diabetics were divided into 13 depressed-diabetics group(above 20 point) and 47 non-depressed group(below 20 point). We compared demographic data. glycemic controls, STAI, TAS and SRI scores between two groups by independent t-test. Results : 1) Depressed diabetic groups were 13(mean age : $55.4{\pm}7.2$ years, 7 men and 6 women) and non depressed groups were 47(mean age $48.9{\pm}9.8$ years, 24 men and 23 women). In depressed diabetics, compared with non-depressed group, manifested aged(p=0.031), but other demographic data showed no difference between two groups. 2) No significant differences were noted in FBS, PP2h, Hb A1C, total cholesterol, HDL-cholesterol, SGOT/SGPT, BUN levels between depressed and non-depressed groups. But, blood creatine levels of depressed group were significantly increased than non-depressed group(p=0.026). 3) No significant differences were found in the score of STAI, STAI-S, STAI-T, TAS between depressed and non-depressed groups. 4) The SRI scores of depressed groups were significantly higher than non-depressed groups$(59.7{\pm}24.9\;vs.\;31.5{\pm}22.0)(p=0.000)$. Conclusion : The above results suggest that depressed diabetic patients are have more stress responses and higher blood creatine levels. However, there were no differences in laboratory data related to glycemic controls, and anxiety. alexithymia levels between two groups. We suggest that physicians should consider integrated approaches for psychiatric problems in the management of diabetes.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.131-143
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• 2015

Purpose : By comparing a CT fusion plan based on MRI with a plan based on only MRI without CT, we intended to study usefulness of a plan based on only MRI. And furthermore, we intended to realize a realtime MR-IGRT by MRI image without CT scan during the course of simulation, treatment planning, and radiation treatment. Materials and Methods : BBB CT (Brilliance Big Bore CT, 16slice, Philips), Viewray MRIdian system (Viewray, USA) were used for CT & MR simulation and Treatment plan of 11 patients (1 Head and Neck, 5 Breast, 1 Lung, 3 Liver, 1 Prostate). When scanning for treatment, Free Breathing was enacted for Head&Neck, Breast, Prostate and Inhalation Breathing Holding for Lung and Liver. Considering the difference of size between CT and Viewray, the patient's position and devices were in the same condition. Using Viewray MRIdian system, two treatment plans were established. The one was CT fusion treatment plan based on MR image. Another was MR treatment plan including electron density that [ICRU 46] recommend for Lung, Air and Bone. For Head&Neck, Breast and Prostate, IMRT was established and for Lung and Liver, Gating treatment plan was established. PTV's Homogeneity Index(HI) and Conformity Index(CI) were use to estimate the treatment plan. And DVH and dose difference of each PTV and OAR were compared to estimate the treatment plan. Results : Between the two treatment plan, each difference of PTV's HI value is 0.089% (Head&Neck), 0.26% (Breast), 0.67% (Lung), 0.2% (Liver), 0.4% (Prostate) and in case of CI, 0.043% (Head&Neck), 0.84% (Breast), 0.68% (Lung), 0.46% (Liver), 0.3% (Prostate). As showed above, it is on Head&Neck that HI and CI's difference value is smallest. Each difference of average dose on PTV is 0.07 Gy (Head&Neck), 0.29 Gy (Breast), 0.18 Gy (Lung), 0.3 Gy (Liver), 0.18 Gy (Prostate). And by percentage, it is 0.06% (Head&Neck), 0.7% (Breast), 0.29% (Lung), 0.69% (Liver), 0.44% (Prostate). Likewise, All is under 1%. In Head&Neck, average dose difference of each OAR is 0.01~0.12 Gy, 0.04~0.06 Gy in Breast, 0.01~0.21 Gy in Lung, 0.06~0.27 Gy in Liver and 0.02~0.23 Gy in Prostate. Conclusion : PTV's HI, CI dose difference on the Treatment plan using MR image is under 1% and OAR's dose difference is maximum 0.89 Gy as heterogeneous tissue increases when comparing with that fused CT image. Besides, It characterizes excellent contrast in soft tissue. So, radiation therapy using only MR image without CT scan is useful in the part like Head&Neck, partial breast and prostate cancer which has a little difference of heterogeneity.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.101-123
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• 2012

Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

• Journal of Chest Surgery
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• v.37 no.1
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• pp.19-26
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• 2004

Background: The aims of this study are to verify the result of the surgical treatment of ALCAPA and to identify the postoperative changes of left ventricular dimensions and mitral regurgitation (MR), Material and Method: Fifteen patients operated on since 1985 were included in the study. The patients operated on before 1998 (n=9) showed heterogeneous properties with various surgical strategies and cardiopulmonary bypass techniques. However, six patients were operated on with the established surgical strategy since 1998; 1) Dual perfusion and dual cardioplegic solution delivery through ascending aorta and main pulmonary artery, 2) Coronary transfer by rolled-conduit made of pulmonary artery wall flap, and 3) Additional mitral valvular procedure was not peformed. Result: Median age of the study group was 6 months (1 month to 34 years). The operative methods were left subclavian artery to left coronary artery anastomosis in 1, simple ligation in 2, Takeuchi operation in 2, and coronary reimplantation in 10 patients. The mean follow up period was 5.5<5.8 years (2 months 14 years), There were one early death (6.7%) and one late death. Overall 5-year survival rate was 85.6$\pm$9.6%. The Z-value of left ventricular end-diastolic and end-systolic dimensions were 6.4$\pm$3.0 and 5.1 $\pm$3.6 preoperatively, and decreased to 1.7$\pm$ 1.9 and 0.8$\pm$ 1.6 in 3 months (p<0.05). Significant preoperative MR was identified in 6 patients (40%) and all the patients showed immediate improvement of MR within f month postoperatively. There were 3 cases of reoperation due to coronary anastomosis site stenosis and recurrence of MR. However, there was no mortality nor late reoperation in the patients operated on after 1998. Conclusion: The surgical treatment of ALCAPA showed favorable survival and early recovery of ventricular dimensions and mitral valvular function. Although long-term reintervention was required in some cases of earlier period, all the cases after 1998 showed excellent surgical outcome without long-term problem.

• Radiation Oncology Journal
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• v.26 no.2
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• pp.83-90
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• 2008

Purpose: For the first time, a nationwide survey of the Patterns of Care Study(PCS) for the various radiotherapy treatments of esophageal cancer was carried out in South Korea. In order to observe the different parameters, as well as offer a solid cooperative system, we compared the Korean results with those observed in the United States(US) and Japan. Materials and Methods: Two hundreds forty-six esophageal cancer patients from 21 institutions were enrolled in the South Korean study. The patients received radiation theraphy(RT) from 1998 to 1999. In order to compare these results with those from the United States, a published study by Suntharalingam, which included 414 patients[treated by Radiotherapy(RT)] from 59 institutions between 1996 and 1999 was chosen. In order to compare the South Korean with the Japanese data, we choose two different studies. The results published by Gomi were selected as the surgery group, in which 220 esophageal cancer patients were analyzed from 76 facilities. The patients underwent surgery and received RT with or without chemotherapy between 1998 and 2001. The non-surgery group originated from a study by Murakami, in which 385 patients were treated either by RT alone or RT with chemotherapy, but no surgery, between 1999 and 2001. Results: The median age of enrolled patients was highest in the Japanese non-surgery group(71 years old). The gender ratio was approximately 9:1(male:female) in both the Korean and Japanese studies, whereas females made up 23.1% of the study population in the US study. Adenocarcinoma outnumbered squamous cell carcinoma in the US study, whereas squamous cell carcinoma was more prevalent both the Korean and Japanese studies(Korea 96.3%, Japan 98%). An esophagogram, endoscopy, and chest CT scan were the main modalities of diagnostic evaluation used in all three countries. The US and Japan used the abdominal CT scan more frequently than the abdominal ultrasonography. Radiotherapy alone treatment was most rarely used in the US study(9.5%), compared to the Korean(23.2%) and Japanese(39%) studies. The combination of the three modalities(Surgery+RT+Chemotherapy) was performed least often in Korea(11.8%) compared to the Japanese(49.5%) and US(32.8%) studies. Chemotherapy(89%) and chemotherapy with concurrent chemoradiotherapy(97%) was most frequently used in the US study. Fluorouracil(5-FU) and Cisplatin were the most preferred drug treatments used in all three countries. The median radiation dose was 50.4 Gy in the US study, as compared to 55.8 Gy in the Korean study regardless of whether an operation was performed. However, in Japan, different median doses were delivered for the surgery(48 Gy) and non-surgery groups(60 Gy). Conclusion: Although some aspects of the evaluation of esophageal cancer and its various treatment modalities were heterogeneous among the three countries surveyed, we found no remarkable differences in the RT dose or technique, which includes the number of portals and energy beams.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.47-55
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• 2015

Recently, the environment of a hospital information system is a trend to combine various SMART technologies. Accordingly, various smart devices, such as a smart phone, Tablet PC is utilized in the medical information system. Also, these environments consist of various applications executing on heterogeneous sensors, devices, systems and networks. In these hospital information system environment, applying a security service by traditional access control method cause a problems. Most of the existing security system uses the access control list structure. It is only permitted access defined by an access control matrix such as client name, service object method name. The major problem with the static approach cannot quickly adapt to changed situations. Hence, we needs to new security mechanisms which provides more flexible and can be easily adapted to various environments with very different security requirements. In addition, for addressing the changing of service medical treatment of the patient, the researching is needed. In this paper, we suggest a dynamic approach to medical information systems in smart mobile environments. We focus on how to access medical information systems according to dynamic access control methods based on the existence of the hospital's information system environments. The physical environments consist of a mobile x-ray imaging devices, dedicated mobile/general smart devices, PACS, EMR server and authorization server. The software environment was developed based on the .Net Framework for synchronization and monitoring services based on mobile X-ray imaging equipment Windows7 OS. And dedicated a smart device application, we implemented a dynamic access services through JSP and Java SDK is based on the Android OS. PACS and mobile X-ray image devices in hospital, medical information between the dedicated smart devices are based on the DICOM medical image standard information. In addition, EMR information is based on H7. In order to providing dynamic access control service, we classify the context of the patients according to conditions of bio-information such as oxygen saturation, heart rate, BP and body temperature etc. It shows event trace diagrams which divided into two parts like general situation, emergency situation. And, we designed the dynamic approach of the medical care information by authentication method. The authentication Information are contained ID/PWD, the roles, position and working hours, emergency certification codes for emergency patients. General situations of dynamic access control method may have access to medical information by the value of the authentication information. In the case of an emergency, was to have access to medical information by an emergency code, without the authentication information. And, we constructed the medical information integration database scheme that is consist medical information, patient, medical staff and medical image information according to medical information standards.y Finally, we show the usefulness of the dynamic access application service based on the smart devices for execution results of the proposed system according to patient contexts such as general and emergency situation. Especially, the proposed systems are providing effective medical information services with smart devices in emergency situation by dynamic access control methods. As results, we expect the proposed systems to be useful for u-hospital information systems and services.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.