• Title/Summary/Keyword: Quantitative Approaches

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Enhancing Predictive Accuracy of Collaborative Filtering Algorithms using the Network Analysis of Trust Relationship among Users (사용자 간 신뢰관계 네트워크 분석을 활용한 협업 필터링 알고리즘의 예측 정확도 개선)

  • Choi, Seulbi;Kwahk, Kee-Young;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.22 no.3
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    • pp.113-127
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    • 2016
  • Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

Usability index evaluation system for mobile WAP service (무선인터넷 서비스 사용성 지수 평가 체계)

  • Park, Hwan-Su
    • 한국HCI학회:학술대회논문집
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    • 2008.02b
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    • pp.152-157
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    • 2008
  • The customer satisfaction of WAP service greatly relies on the usability of the service due to the limited display size of a mobile phone and limitation in realizing UI (User Interface) for function keys, browser, and OS (operating system) Currently, a number of contents providers develop and deliver varying services, and thus, it is critical to control quality level of UI in consistent standards and manner. This study suggests usability index evaluation system to achieve consistent UI quality control of various WAP services. The system adopts both top-down and bottom-up approaches. The former concerns deriving UI design components and evaluation checklists for the WAP, based on the usability attributes and UI principles. The latter concerns deriving usability-related evaluation checklists from the established UI design features, and then grouping them from the viewpoint of usability principles and attributes. This bidirectional approach has two outstanding advantages: it allows thorough examination of potential elements that can cause usability problems from the standpoint of usability attributes, and also derives specific evaluation elements from the perspective of UI design components that are relevant to the real service environment. The evaluation system constitutes a hierarchical structure by networking usability attributes, UI guideline which indicates usability principles for each attribute, and usability evaluation checklist for each UI component that enables specific evaluation. Especially, each evaluation checklist contains concrete contents and format so that it can be readily marked in O/X. The score is based on the ratio of number of items that received positive answer to the number of total items. This enables a quantitative evaluation of the usability of mobile WAP service. The validity of the proposed evaluation system has been proved through comparative analysis with the real usability problems based on the user test. A software was developed that provides guideline for evaluation objects, criteria and examples for each checklist, and automatically calculates a score. The software was applied to evaluating and improving the real mobile WAP service.

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Regional Distribution of Cerebral Blood Flow in Childhood Measured by $^{99m}Tc-HMPAO$ SPECT : Reference Values of Semiquantitative Indices and Effect of Age ($^{99m}Tc-HMPAO$ SPECT를 이용한 어린이 국소뇌혈류의 정량적 분석 : 정량적 지표들의 참고값 및 연령에 따른 변화)

  • Kim, Sang-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Koh, Chang-Soon;Cho, Soo-Churl;Hong, Seung-Bong;Yoon, Byung-Woo;Roh, Jae-Kyu;Myung, Ho-Jin
    • The Korean Journal of Nuclear Medicine
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    • v.25 no.1
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    • pp.6-16
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    • 1991
  • Regional cerebral blood flow (rCBF) was evaluated in 12 children ranging in age from 2.7 to 10.0 yr using $^{99m}Tc-HMPAO$ SPECT. For quantitative analysis, 13 pairs of homologous regions of interest (ROIs) were created on three attenuation-corrected 18.8 mm thick transverse slices matching the cerebral cortical regions, deep gray matter, cerebellar hemisphere, and vascular territories, and the semiquantitative indices including "right to left ratio" [(mean count/voxel of homologous right ROI) / (mean count/voxel of homologous left ROI)] and "regional index"(RI) [(mean count/voxel of a ROI)/ (mean count/voxel of all ROIs of each hemisphere)] were calculated. Mean values of right to left ratios of homologous regions ranged from 0.984 to 1.028 in children under 5 yr (group 1) and from 0.982 to 1.012 in children between 5 and 10 yr (group 2), and the mean $value{\pm}2S.D.$ for each region did not exceed 11% and 12% in group 1 and group 2, respectively. There were no statistically significant differences between the RIs of the homologous right and left regions. Significant differences of RIs were found both between vascular regions (p<0.0005 for goup 1, and p=0.0001 for goup 2) and between regions of cerebral cortices (p<0.0005 for group 1, and p<0.005 for group 2) with a relatively high value in the occipital cortex and the lower values in the cerebellum and deep gray matter among the regions of cerebral cortices in both groups. There were no significant differences between the RIs of corresponding regions of group 1 and group 2, except a significantly higher value of right deep gray matter in group 2 than in group 1(p=0.0301). The RIs of the superior frontal cortex and deep gray matter showed to be positively correlated with age (superior frontal cortex; right: rs=0.5254, p=0.0814, left : rs=0.5919, p=0.0496/deep gray matter; right: rs=0.8246, p=0.0062, left: rs=0.6266, p=0.0377). The results suggest that the rCBF pattern of children approaches that of adults in an accipito-rostral direction. This time course of rCBF changes is in agreement with behavioral, neurophysiological, and anatomical alterations known to occur in the developing brain.

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Data Mining Approaches for DDoS Attack Detection (분산 서비스거부 공격 탐지를 위한 데이터 마이닝 기법)

  • Kim, Mi-Hui;Na, Hyun-Jung;Chae, Ki-Joon;Bang, Hyo-Chan;Na, Jung-Chan
    • Journal of KIISE:Information Networking
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    • v.32 no.3
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    • pp.279-290
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    • 2005
  • Recently, as the serious damage caused by DDoS attacks increases, the rapid detection and the proper response mechanisms are urgent. However, existing security mechanisms do not effectively defend against these attacks, or the defense capability of some mechanisms is only limited to specific DDoS attacks. In this paper, we propose a detection architecture against DDoS attack using data mining technology that can classify the latest types of DDoS attack, and can detect the modification of existing attacks as well as the novel attacks. This architecture consists of a Misuse Detection Module modeling to classify the existing attacks, and an Anomaly Detection Module modeling to detect the novel attacks. And it utilizes the off-line generated models in order to detect the DDoS attack using the real-time traffic. We gathered the NetFlow data generated at an access router of our network in order to model the real network traffic and test it. The NetFlow provides the useful flow-based statistical information without tremendous preprocessing. Also, we mounted the well-known DDoS attack tools to gather the attack traffic. And then, our experimental results show that our approach can provide the outstanding performance against existing attacks, and provide the possibility of detection against the novel attack.

Research Trend of the Healthcare and Medical Care for Elders in the Journal of the Korea Gerontological Society (한국노년학의 보건·의료·건강영역 연구동향)

  • Kim, Hyun Sook;Park, Yeon-Hwan;Kim, Young Sun
    • 한국노년학
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    • v.38 no.3
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    • pp.705-723
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    • 2018
  • In this study we review the selected articles on elderly health and medical care published in the Journal of the Korea Gerontological Society (JKGS) in the last 40 years, and make suggestions for future research directions for gerontological health and medical care issues. Of all the 40 year publications from volume 1 (1980) to 38 (2017), we first examined the 30th anniversary review on the subject of gerontological nursing care and healthcare policies published in JKGS from 1980 (vol. 1, No. 1) to 2008 (vol. 28, No. 2), and reviewed recent 237 researches of this decade (out of all 655 articles from 2008, vol. 28, No. 3 to 2017, vol. 38, No. 4). We could find the following trends. Firstly, the analysis of the primary authors in the past 10 years revealed that those in public health, nursing and other health-related including physical education areas have dealt the subjects focusing on physical health while those in social welfare mostly on mental health. That is, physical health has been the prime subject of researches in the health and medical care area. Secondly, in the same period quantitative researches were accounted for 89.9%, which is similar to the trend of the first 30 years 81.5 %. On the other hand, qualitative studies were only 11 cases and the focus group interview were the most frequently used method comprising 33.3% among them. Thirdly, the non-experimental researches in the past 10 years comprise 65.4%, which was 82.7% in 1980 2008 period, indicating the increasing trend in experimental researches to deal with the issues in medical and healthcare fields. Lastly, the subjects of the researches were mostly the elders who are healthy, residents of city areas, or home dwellers, and 60% of them were over 65 years old in the past 10 years while the proportion was 42.7% in the previous review period. 81.6 % of the researches in the past 10 years was dealing both genders, slightly decreased trend compared to 88.5% of the previous review period. This study reveals that the researches in non-experimental physical health remains the main stream of JKGS despite the efforts by some researchers to diversify the methods and subjects. Systematic and in-depth researches employing multidisciplinary, qualitative, longitudinal and meta-analytical approaches are called for to guide the gerontolgical health issues with preventive and proactive perspectives.

Analysis of Research Trends of 'Word of Mouth (WoM)' through Main Path and Word Co-occurrence Network (주경로 분석과 연관어 네트워크 분석을 통한 '구전(WoM)' 관련 연구동향 분석)

  • Shin, Hyunbo;Kim, Hea-Jin
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.179-200
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    • 2019
  • Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

A Data-based Sales Forecasting Support System for New Businesses (데이터기반의 신규 사업 매출추정방법 연구: 지능형 사업평가 시스템을 중심으로)

  • Jun, Seung-Pyo;Sung, Tae-Eung;Choi, San
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.1-22
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    • 2017
  • Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

If This Brand Were a Person, or Anthropomorphism of Brands Through Packaging Stories (가설품패시인(假设品牌是人), 혹통과고사포장장품패의인화(或通过故事包装将品牌拟人化))

  • Kniazeva, Maria;Belk, Russell W.
    • Journal of Global Scholars of Marketing Science
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    • v.20 no.3
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    • pp.231-238
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    • 2010
  • The anthropomorphism of brands, defined as seeing human beings in brands (Puzakova, Kwak, and Rosereto, 2008) is the focus of this study. Specifically, the research objective is to understand the ways in which brands are rendered humanlike. By analyzing consumer readings of stories found on food product packages we intend to show how marketers and consumers humanize a spectrum of brands and create meanings. Our research question considers the possibility that a single brand may host multiple or single meanings, associations, and personalities for different consumers. We start by highlighting the theoretical and practical significance of our research, explain why we turn our attention to packages as vehicles of brand meaning transfer, then describe our qualitative methodology, discuss findings, and conclude with a discussion of managerial implications and directions for future studies. The study was designed to directly expose consumers to potential vehicles of brand meaning transfer and then engage these consumers in free verbal reflections on their perceived meanings. Specifically, we asked participants to read non-nutritional stories on selected branded food packages, in order to elicit data about received meanings. Packaging has yet to receive due attention in consumer research (Hine, 1995). Until now, attention has focused solely on its utilitarian function and has generated a body of research that has explored the impact of nutritional information and claims on consumer perceptions of products (e.g., Loureiro, McCluskey and Mittelhammer, 2002; Mazis and Raymond, 1997; Nayga, Lipinski and Savur, 1998; Wansik, 2003). An exception is a recent study that turns its attention to non-nutritional packaging narratives and treats them as cultural productions and vehicles for mythologizing the brand (Kniazeva and Belk, 2007). The next step in this stream of research is to explore how such mythologizing activity affects brand personality perception and how these perceptions relate to consumers. These are the questions that our study aimed to address. We used in-depth interviews to help overcome the limitations of quantitative studies. Our convenience sample was formed with the objective of providing demographic and psychographic diversity in order to elicit variations in consumer reflections to food packaging stories. Our informants represent middle-class residents of the US and do not exhibit extreme alternative lifestyles described by Thompson as "cultural creatives" (2004). Nine people were individually interviewed on their food consumption preferences and behavior. Participants were asked to have a look at the twelve displayed food product packages and read all the textual information on the package, after which we continued with questions that focused on the consumer interpretations of the reading material (Scott and Batra, 2003). On average, each participant reflected on 4-5 packages. Our in-depth interviews lasted one to one and a half hours each. The interviews were tape recorded and transcribed, providing 140 pages of text. The products came from local grocery stores on the West Coast of the US and represented a basic range of food product categories, including snacks, canned foods, cereals, baby foods, and tea. The data were analyzed using procedures for developing grounded theory delineated by Strauss and Corbin (1998). As a result, our study does not support the notion of one brand/one personality as assumed by prior work. Thus, we reveal multiple brand personalities peacefully cohabiting in the same brand as seen by different consumers, despite marketer attempts to create more singular brand personalities. We extend Fournier's (1998) proposition, that one's life projects shape the intensity and nature of brand relationships. We find that these life projects also affect perceived brand personifications and meanings. While Fournier provides a conceptual framework that links together consumers’ life themes (Mick and Buhl, 1992) and relational roles assigned to anthropomorphized brands, we find that consumer life projects mold both the ways in which brands are rendered humanlike and the ways in which brands connect to consumers' existential concerns. We find two modes through which brands are anthropomorphized by our participants. First, brand personalities are created by seeing them through perceived demographic, psychographic, and social characteristics that are to some degree shared by consumers. Second, brands in our study further relate to consumers' existential concerns by either being blended with consumer personalities in order to connect to them (the brand as a friend, a family member, a next door neighbor) or by distancing themselves from the brand personalities and estranging them (the brand as a used car salesman, a "bunch of executives.") By focusing on food product packages, we illuminate a very specific, widely-used, but little-researched vehicle of marketing communication: brand storytelling. Recent work that has approached packages as mythmakers, finds it increasingly challenging for marketers to produce textual stories that link the personalities of products to the personalities of those consuming them, and suggests that "a multiplicity of building material for creating desired consumer myths is what a postmodern consumer arguably needs" (Kniazeva and Belk, 2007). Used as vehicles for storytelling, food packages can exploit both rational and emotional approaches, offering consumers either a "lecture" or "drama" (Randazzo, 2006), myths (Kniazeva and Belk, 2007; Holt, 2004; Thompson, 2004), or meanings (McCracken, 2005) as necessary building blocks for anthropomorphizing their brands. The craft of giving birth to brand personalities is in the hands of writers/marketers and in the minds of readers/consumers who individually and sometimes idiosyncratically put a meaningful human face on a brand.

An Intelligent Decision Support System for Selecting Promising Technologies for R&D based on Time-series Patent Analysis (R&D 기술 선정을 위한 시계열 특허 분석 기반 지능형 의사결정지원시스템)

  • Lee, Choongseok;Lee, Suk Joo;Choi, Byounggu
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.79-96
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    • 2012
  • As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

A Study on the long-term Hemodialysis patient중s hypotension and preventation from Blood loss in coil during the Hemodialysis (장기혈액투석환자의 투석중 혈압하강과 Coil내 혈액손실 방지를 위한 기초조사)

  • 박순옥
    • Journal of Korean Academy of Nursing
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    • v.11 no.2
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    • pp.83-104
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    • 1981
  • Hemodialysis is essential treatment for the chronic renal failure patient's long-term cure and for the patient management before and after kidney transplantation. It sustains the endstage renal failure patient's life which didn't get well despite strict regimen and furthermore it becomes an essential treatment to maintain civil life. Bursing implementation in hemodialysis may affect the significant effect on patient's life. The purpose of this study was to obtain the basic data to solve the hypotension problem encountable to patient and the blood loss problem affecting hemodialysis patient'a anemic states by incomplete rinsing of blood in coil through all process of hemodialysis. The subjects for this study were 44 patients treated hemodialysis 691 times in the hemodialysis unit, The .data was collected at Gang Nam 51. Mary's Hospital from January 1, 1981 to April 30, 1981 by using the direct observation method and the clinical laboratory test for laboratory data and body weight and was analysed by the use of analysis of Chi-square, t-test and anlysis of varience. The results obtained an follows; A. On clinical laboratory data and other data by dialysis Procedure. The average initial body weight was 2.37 ± 0.97kg, and average body weight after every dialysis was 2.33 ± 0.9kg. The subject's average hemoglobin was 7.05±1.93gm/dl and average hematocrit was 20.84± 3.82%. Average initial blood pressure was 174.03±23,75mmHg and after dialysis was 158.45±25.08mmHg. The subject's average blood ion due to blood sample for laboratory data was 32.78±13.49cc/ month. The subject's average blood replacement for blood complementation was 1.31 ±0.88 pint/ month for every patient. B. On the hypotensive state and the coping approaches occurrence rate of hypotension was 28.08%. It was 194 cases among 691 times. 1. In degrees of initial blood pressure, the most 36.6% was in the group of 150-179mmHg, and in degrees of hypotension during dialysis, the most 28.9% in the group of 40-50mmHg, especially if the initial blood pressure was under 180mmHg, 59.8% clinical symptoms appeared in the group of“above 20mmHg of hypotension”. If initial blood pressure was above 180mmHg, 34.2% of clinical symptoms were appeared in the group of“above 40mmHg of hypotension”. These tendencies showed the higher initial blood pressure and the stronger degree of hypotension, these results showed statistically singificant differences. (P=0.0000) 2. Of the occuring times of hypotension,“after 3 hrs”were 29.4%, the longer the dialyzing procedure, the stronger degree of hypotension ann these showed statistically significant differences. (P=0.0142). 3. Of the dispersion of symptoms observed, sweat and flush were 43.3%, and Yawning, and dizziness 37.6%. These were the important symptoms implying hypotension during hemodialysis accordingly. Strages of procedures in coping with hypotension were as follows ; 45.9% were recovered by reducing the blood flow rate from 200cc/min to 1 00cc/min, and by reducing venous pressure to 0-30mmHg. 33.51% were recovered by controling (adjusting) blood flow rate and by infusion of 300cc of 0,9% Normal saline. 4.1% were recovered by infusion of over 300cc of 0.9% normal saline. 3.6% by substituting Nor-epinephiine, 5.7% by substituting blood transfusion, and 7,2% by substituting Albumin were recovered. And the stronger the degree of symptoms observed in hypotention, the more the treatments required for recovery and these showed statistically significant differences (P=0.0000). C. On the effects of the changes of blood pressure and osmolality by albumin and hemofiltration. 1. Changes of blood pressure in the group which didn't required treatment in hypotension and the group required treatment, were averaged 21.5mmHg and 44.82mmHg. So the difference in the latter was bigger than the former and these showed statistically significant difference (P=0.002). On the changes of osmolality, average mean were 12.65mOsm, and 17.57mOsm. So the difference was bigger in the latter than in the former but these not showed statistically significance (P=0.323). 2. Changes of blood pressure in the group infused albumin and in the group didn't required treatment in hypotension, were averaged 30mmHg and 21.5mmHg. So there was no significant differences and it showed no statistical significance (P=0.503). Changes of osmolality were averaged 5.63mOsm and 12.65mOsm. So the difference was smaller in the former but these was no stitistical significance (P=0.287). Changes of blood pressure in the group infused Albumin and in the group required treatment in hypotension were averaged 30mmHg and 44.82mmHg. So the difference was smaller in the former but there is no significant difference (P=0.061). Changes of osmolality were averaged 8.63mOsm, and 17.59mOsm. So the difference were smaller in the former but these not showed statistically significance (P=0.093). 3. Changes of blood pressure in the group iutplemented hemofiltration and in the Uoup didn't required treatment in hypotension were averaged 22mmHg and 21.5mmHg. So there was no significant differences and also these showed no statistical significance (P=0.320). Changes of osmolality were averaged 0.4mOsm and 12.65mOsm. So the difference was smaller in the former but these not showed statistical significance(P=0.199). Changes of blood pressure in the group implemented hemofiltration and in the group required treatment in hypotension were averaged 22mmHg and 44.82mmHg. So the difference was smatter in the former and these showed statistically significant differences (P=0.035). Changes of osmolality were averaged 0.4mOsm and 17.59mOsm. So the difference was smaller in the former but these not showed statistical significance (P=0.086). D. On the changes of body weight, and blood pressure, between the group of hemofiltration and hemodialysis. 1, Changes of body weight in the group implemented hemofiltration and hemodialysis were averaged 3.340 and 3.320. So there was no significant differences and these showed no statistically significant difference, (P=0.185) but standard deviation of body weight averaged in comparison with standard difference of body weight was statistically significant difference (P=0.0000). Change of blood Pressure in the group implemented hemofiltration and hemodialysis were averaged 17.81mmHg and 19.47mmHg. So there was no significant differences and these showed no statistically significant difference (P=0.119), But in comparison with standard deviation about difference of blood pressure was statistically significant difference. (P=0.0000). E. On the blood infusion method in coil after hemodialysis and residual blood losing method in coil. 1, On comparing and analysing Hct of residual blood in coil by factors influencing blood infusion method. Infusion method of saline 200cc reduced residual blood in coil after the quantitative comparison of Saline Occ, 50cc, 100cc, 200cc and the differences showed statistical significance (p < 0.001). Shaking Coil method reduced residual blood in Coil in comparison of Shaking Coil method and Non-Shaking Coil method this showed statistically significant difference (P < 0.05). Adjusting pressure in Coil at OmmHg method reduced residual blood in Coil in comparison of adjusting pressure in Coil at OmmHg and 200mmHg, and this showed statistically significant difference (P < 0.001). 2. Comparing blood infusion method divided into 10 methods in Coil with every factor respectively, there was seldom difference in group of choosing Saline 100cc infusion between Coil at OmmHg. The measured quantity of blood loss was averaged 13.49cc. Shaking Coil method in case of choosing saline 50cc infusion while adjusting pressure in coil at OmmHg was the most effective to reduce residual blood. The measured quantity of blood loss was averaged 15.18cc.

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