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A study of Artificial Intelligence (AI) Speaker's Development Process in Terms of Social Constructivism: Focused on the Products and Periodic Co-revolution Process (인공지능(AI) 스피커에 대한 사회구성 차원의 발달과정 연구: 제품과 시기별 공진화 과정을 중심으로)

  • Cha, Hyeon-ju;Kweon, Sang-hee
    • Journal of Internet Computing and Services
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    • v.22 no.1
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    • pp.109-135
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    • 2021
  • his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

The Zhouyi and Artificial Intelligence (『주역』과 인공지능)

  • Bang, In
    • Journal of Korean Philosophical Society
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    • v.145
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    • pp.91-117
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    • 2018
  • This paper aims to clarify the similarities and differences between the Zhouyi and artificial intelligence. The divination of the Zhouyi is rooted in the oldest system of human knowledge, while artificial intelligence stands at the cutting edge of modern scientific revolution. At first sight, there does not appear to be any association that links the one to the another. However, they share the same ground as seen from a semiotic standpoint because both of them depend on the semiotic system as a means of obtaining knowledge. At least four aspects can be pointed out in terms of similarities. First, artificial intelligence and the Zhouyi use artificial language that consists of semiotic signs. Secondly, the principle that enables divination and artificial intelligence lies in imitation and representation. Thirdly, artificial intelligence and the Zhouyi carry out inferences based on mathematical algorithms that adopt the binary system. Fourth, artificial intelligence and the Zhouyi use analogy as a means of obtaining knowledge. However, those similarities do not guarantee that the Zhouyi could arrive at the scientific certainty. Nevertheless, it can give us important insight into the essence of our civilization. The Zhouyi uses intellect in order to get new information about the unknown world. However, it is hard to know what kind of intellect is involved in the process of divination. Likewise, we do not know the fundamental character of artificial intelligence. The intellect hidden in the unknown subject is a mystic and fearful existence to us. Just as the divination of the Zhouyi inspires the sense of reverence toward the supernatural subject, we could not but have fear in front of the invisible subject hidden in artificial intelligence. In the past, traditional philosophy acknowledged the existence of intellect only in conscious beings. Nonetheless, it becomes evident that human civilization ushers into a new epoch. As Ray Kurzweil mentioned, the moment of singularity comes when artificial intelligence surpasses human intelligence. In my viewpoint, the term of singularity can be used for denoting the critical point in which the human species enters into the new phase of civilization. To borrow the term of Shao Yong(邵雍) in the Northern Song Dynasty, the past civilization belongs to the Earlier Heaven(先天), the future civilization belongs to the Later Heaven(後天). Once our civilization passes over the critical point, it is impossible to go back into the past. The opening of the Later Heaven foretold by the religious thinkers in the late period of Joseon Dynasty was a prophecy in its own age, but it is becoming a reality in the present.

Estimation of Heading Date using Mean Temperature and the Effect of Sowing Date on the Yield of Sweet Sorghum in Jellabuk Province (평균온도를 이용한 전북지역 단수수의 출수기 추정 및 파종시기별 수량 변화)

  • Choi, Young Min;Choi, Kyu-Hwan;Shin, So-Hee;Han, Hyun-Ah;Heo, Byong Soo;Kwon, Suk-Ju
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.64 no.2
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    • pp.127-136
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    • 2019
  • Sweet sorghum (Sorghum bicolor L. Moench), compared to traditional crops, has been evaluated as a useful crop with high adaptability to the environment and various uses, but cultivation has not expanded owing to a lack of related research and information in Korea. This study was conducted to estimate heading date in 'Chorong' sweet sorghum based on climate data of the last 30 years (1989 - 2018) from six regions (Jeonju, Buan, Jeongup, Imsil, Namwon, and Jangsu) in Jellabuk Province. In addition, we compared the growth and quality factors by sowing date (April 10, April 25, May 10, May 25, June 10, June 25, and July 10) in 2018. Days from sowing to heading (DSH) increased to 107, 96, 83, 70, 59, 64, and 65 days in order of the sowing dates, respectively, and the average was 77.7 days. The effective accumulated temperature for heading date was $1,120.3^{\circ}C$. The mean annual temperature was the highest in Jeonju, followed in descending order by Jeongup, Buan, Namwon, Imsil, and Jangsu. The DSH based on effective accumulated temperature gradually decreased in all sowing date treatments in the six regions during the last 30 years. DSH of the six regions showed a negative relationship with mean temperature (sowing date to heading date) and predicted DSH ($R^2=0.9987**$) calculated by mean temperature was explained with a probability of 89% of observed DSH in 2017 and 2018. At harvest, fresh stem weight and soluble solids content were higher in the April and July sowings, but sugar content was higher in the May 10 ($3.4Mg{\cdot}ha^{-1}$) and May 25 ($3.1Mg{\cdot}ha^{-1}$) sowings. Overall, the April and July sowings were of low quality and yield, and there is a risk of frost damage; thus, we found May sowings to be the most effective. Additionally, sowing dates must be considered in terms of proper harvest stage, harvesting target (juice or grain), cultivation altitude, and microclimate.

Real-time CRM Strategy of Big Data and Smart Offering System: KB Kookmin Card Case (KB국민카드의 빅데이터를 활용한 실시간 CRM 전략: 스마트 오퍼링 시스템)

  • Choi, Jaewon;Sohn, Bongjin;Lim, Hyuna
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.1-23
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    • 2019
  • Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

Convergent Studies of Utilization Plan and Brand Suggestion for Abandoned Passenger Ferry Terminal in Jangseungpo to Improve Local Community Value (지역 가치 증진을 위한 장승포 폐 여객선 터미널의 활용 방안 및 브랜드 제안에 관한 융합 연구)

  • Lee, Ha Na;Oh, Kwang Myung;Paik, Jin Kyung
    • Korea Science and Art Forum
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    • v.37 no.2
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    • pp.239-250
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    • 2019
  • Along with changes in the industrial structure, revitalizing decrepit or abandoned industrial-age infrastructures are actively under way on a global scale. This study was motivated by an interest in investigating currently idle industrial infrastructures and revitalizing the abandoned passenger ferry terminal in Geoje's Jangseungpo and surrounding areas. The main aims of this study were to examine regional features for the purpose of establishing urban renewal plans and field opinions of the local residents on how to proceed with the restoration of the passenger ferry terminal. To this end, this paper looked into previous case studies of converting decrepit industrial infrastructures into new cultural venues, depending on each region's special circumstances. This paper's findings are as follows: First, as a result of this investigation, the author found that in all cases in Korea and elsewhere revitalization focused on creating modern cultural spaces appropriate for the region while retaining its traditional value. At the same time, they sought sustainable cultural and economic revival. Second, as a result of the investigation on Geoje City's local characteristics, the author found that the surrounding areas' commercial districts were depressed after the terminal's closure. At the time of the investigation, the city government was trying to reopen the terminal as a major port offering multiple international ferry destinations while attracting tourists. Third, as a result of the surveys on the local residents, it was found that more than half of the residents were in agreement with the city government's plan to reopen the terminal and expressed their wishes that they want the terminal to have other uses such as cultural venues. Based on these research results, the author makes proposals, including expanding the passenger ferry terminal and offering cultural spaces within and near the terminal, based on the local residents' opinions and in reflection of local circumstances. As part of this effort, the author also recommends a new brand name and design plan for the new passenger ferry terminal so that Geoje City can improve its local community value.

A study on artificial flowers in the late Joseon Dynasty, focusing on a birthday banquet inBongsudang Hall in 1795 (1795년 봉수당 진찬(奉壽堂進饌)으로 보는 조선 후기 채화(綵花) 고찰)

  • LEE Kyunghee;KIM Youngsun
    • Korean Journal of Heritage: History & Science
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    • v.56 no.1
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    • pp.182-205
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    • 2023
  • The use of royal artificial flowers was finally found through schematics and records in Wonhaeng Eulmyojeongri Uigwe, which organized the procession to Hwaseong in 1795. The results of classifying the uses of artificial flowers in the brthday banquet at Bongsudang Hall in 1795 and considering the shape, user, and usage are as follows. According to literature records, artificial flowers were made with high-quality materials such as gold, silver, and silk thread in the early period, but were mainly made of paper in the later period. Artificial flowers were used for decorating official hats, Bongsudang Hall, and banquet tables. The Sagwonhwa was used for decoration of the official hats of members of the royal family, and the one on the top was called Eosam-Sagwonhwa. At the birthday banquet inBongsudang Hall, King Jeongjo and Hyegyeonggung used the Eosam-Sagwonhwa and put it on the right side of the official hats. Officials put peach blossom with two petals on the left side of the official hats for decoration. The artificial flowers for decoration of the official hats of musicians and dancers were more expensive and flashier than the officials' ones. Depending on the dance, several artificial flowers were inserted into the official hats. When measuring the size of artificial flowers, the scale used was when making a ceremonial article. For artificial flowers for decoration of the banquet hall, red and white peach blossoms were placed in two jars with dragons painted on them and them placed on two red-painted tables, respectively. The table and jar with flowers were tied together with a red cotton string and fixed so as not to fall over. The artificial flowers for decoration of the banquet table of King Jeongjo, Hyegyeonggung, and the king's sisters were a large lotus, medium-sized lotus, peony, rose, and specially made peach flowers. The artificial flowers for decoration of the banquet table of guests and officials were small lotuses and peach blossoms. The artificial flowers used in the birthday banquet at Bongsudang Hall the most were peach blossoms, and peaches had the meaning of longevity and exorcism. It is expected that the above research results will be helpful in understanding the characteristics and usage of artificial flowers in the period of King Jeongjo and use in reproducing royal feasts and producing traditional cultural contents.

Incorporating Social Relationship discovered from User's Behavior into Collaborative Filtering (사용자 행동 기반의 사회적 관계를 결합한 사용자 협업적 여과 방법)

  • Thay, Setha;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.1-20
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    • 2013
  • Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

Medical Information Dynamic Access System in Smart Mobile Environments (스마트 모바일 환경에서 의료정보 동적접근 시스템)

  • Jeong, Chang Won;Kim, Woo Hong;Yoon, Kwon Ha;Joo, Su Chong
    • 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.

Content-based Recommendation Based on Social Network for Personalized News Services (개인화된 뉴스 서비스를 위한 소셜 네트워크 기반의 콘텐츠 추천기법)

  • Hong, Myung-Duk;Oh, Kyeong-Jin;Ga, Myung-Hyun;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.57-71
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    • 2013
  • Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

The Effect of Perceived Shopping Value Dimensions on Attitude toward Store, Emotional Response to Store Shopping, and Store Loyalty (지각된 쇼핑가치차원이 점포태도, 쇼핑과정에서의 정서적 경험, 점포충성도에 미치는 영향에 관한 연구)

  • Ahn Kwang Ho;Lee Ha Neol
    • Asia Marketing Journal
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    • v.12 no.4
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    • pp.137-164
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    • 2011
  • In the past, retailers secured customer loyalty by offering convenient locations, unique assortments of goods, better services than competitors, and good credit policy. All this has changed. Goods assortments among stores have become more alike as national-brand manufacturers place their goods in more and more retail stores. Service differentiation also has eroded. Many department stores have trimmed services, and many discount stores have increased theirs. Customers have become smarter shoppers. They don't pay more for identical brands, especially when service differences have diminished. In the face of increased competition from discount storess and specialty stores, department stores are waging a comeback war. Growth of intertype competition, competition between store-based and non-store-based retailing and growing investment in technology are changing the way consumers shop and retailers sell. Different types of stores-discount stores, catalog showrooms, department stores-all compete for the same consumers by carrying the same type of merchandise. The biggest winners are retailers that have helped shoppers to be economically cautious, simplified their increasingly busy and complicated lives, and provided an emotional connection. The growth of e-retailers has forced traditional brick-and-mortar retailers to respond. Basically brick-and-mortar retailers utilize their natural advantages, such as products that shoppers can actually see, touch, and test, real-life customer service, and no delivery lag time for small-sized purchases. They also provide a shopping experience as a strong differentiator. They are adopting practices as calling each shopper a "guest". The store atmosphere should match the basic motivations of the shopper. If target consumers are more likely to be in a task-oriented and functional mindset, then a simpler, more restrained in-store environment may be better. Consistent with this reasoning, some retailers of experiential products are creating in-store entertainment to attract customers who want fun and excitement. The retail experience must deliver value to turn a one-time visitor into a loyal customer. Retailers need a tool that measures the full range of components that define experience-based value. This study uses an experiential value scale(EVS) developed by Mathwick, Malhotra and Rigdon(2001) which reflects the benefits derived from perceptions of playfulness, aesthetics, customer "return on investment" and service excellence. EVS is useful to predict differences in shopping preferences and patronage behavior of customers. EVS consists of items measuring efficiency, economic value, visual appeal, entertainment value, service excellence, escapism, and intrinsic enjoyment, which are subscales of experiencial value. Efficiency, economic value, service excellence are linked to the utilitarian shopping value. And visual appeal, entertainment value, escapism and intrinsic enjoyment are linked to hedonic shopping value. It has been found that consumers value hedonic experiences activated from escapism and attractiveness of shopping environment as much as the product quality, price, and the convenient location. As a result, many department stores, discount stores, and other retailers are introducing differential marketing strategy based on emotional/hedonic values. Many researches suggest that consumers go shopping not only for buying products but also for various shopping experiences. In other words, they seek the practical, rational value as well as social, recreational values in the shopping process(Babin et al, 1994; Bloch et al, 1994). Retailers may enhance buyer's loyalty to store by providing excellent emotional/hedonic value such as the excitement from shopping, not just the practical value of buying good products efficiently. We investigate the effect of perceived shopping values on the emotional experience and store loyalty based on the EVS(Experiential Value Scales) developed by Holbrook(1994), Mathwick, Malhotra and Rigdon(2001). This study assumes that the relative effect of shopping value dimensions on the responses of shoppers will differ according to types of stores and analyzes the moderating effect of store type(department store VS. discount store) on the causal relationship between shopping value dimensions and store loyalty. Emprical results show that utilitarian values of shopping experience and hedonic value of shipping experience give the positive effect on the emotional response of consumers and store loyalty. We also found the moderating effect of store types. The effect of utilitarian shopping values on the attitude toward discount store is higher than the effect of utilitarian shopping values on the attitude toword department store. And the effect of hedonic shopping value on the emotional response to discount store is higher than on the emotional response to department store. The empirical results reflect on the recent trend that discount stores try to fulfill the hedonic needs of consumers as well as utilitarian needs(i.e, low price) that discount stores traditionally have focused on

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