• Information Systems Review
• /
• v.20 no.1
• /
• pp.1-16
• /
• 2018

The development and generalization of the Internet increased the popularity of food delivery service applications in Korea. The food delivery market based on online-to-offline service is growing rapidly. This study compares the usability of Korean food delivery service application between that of Chinese food delivery service application. This study suggests improvement points for Korean food delivery service applications. To conduct this study, we explore the status of various food delivery service applications and conduct interviews and surveys based on the honeycomb model developed by Peter Morville. This study obtained the following results. First, all restaurants participating in the Korean food delivery service must be able to accept order through the application. Second, the shopping cart function must be able to accept order of all restaurants simultaneously. Third, when users look for menu recommendation, their purchase history and shopping cart functions should appear at the first page of the website. Users should be able to perceive the improved usability of the website using those functions. Fourth, when the search window is fixed on the top of each page, users should be able to find the information they need. Fifth, the application must allow users to find the exact location of the delivery person and the estimated delivery time. Finally, the restaurants'address should be disclosed and fast delivery time should be confirmed to enhance users'trust on the application. This study contributes to academia and industry by suggesting useful insight into food delivery service applications and improving the point of food delivery service application in Korea.

• Land and Housing Review
• /
• v.5 no.1
• /
• pp.53-56
• /
• 2014

Hong Kong, a well-known metropolis characterized by skyscrapers on both sides of the Victoria Harbour, consists mainly of 3 parts, namely the Hong Kong Island, the Kowloon peninsula and the New Territories (N.T.) which is the land area north of Kowloon plus a number of outlying islands. Located in the N.T. are all the new towns, market towns; and in the plains and valleys lie scattered village houses of not more than 3 storeys within the confines of well-defined village. These village houses are governed by a rural housing policy that could be traced back to the very beginning of the former British administration in the N.T. By the Convention of Peking of 1898, the N.T., comprising the massive land area north of Kowloon up to Shenzhen River and 235 islands, was leased to Britain by China for 99 years from 1st July 1898. Soon after occupation, the colonial government conducted a survey of this uncharted territory from 1899 to 1903, and set up a land court to facilitate all land registration work and to resolve disputed claims. By 1905, the Block Crown Leases with Schedule of Lessees and details of the lots, each with a copy of the lot index plan (Demarcation Plan) were executed. Based on the above, Crown rent rolls were prepared for record and rent collection purposes. All grants of land thereafter are known as New Grant lots. After completion and execution of the Block Crown Lease in 1905, N.T. villagers had to purchase village house lots by means of Restricted Village Auctions; and Building Licences were issued to convert private agricultural land for building purposes but gradually replaced by Land Exchanges (i.e. to surrender agricultural land for the re-grant of building land) from the early 1960's until introduction of the current Small House Policy in October 1972. It was not until the current New Territories Small House Policy came into effect in December 1972 that the Land Authority can make direct grant of government land or approve the conversion of self-owned agricultural land to allow indigenous villagers to build houses within the village environs under concessionary terms. Such houses are currently restricted to 700 square feet in area and three storeys with a maximum height of 27 feet. An indigenous villager is a male descendent of a villager who was the resident of a recognized village already existing in 1898. Each villager is only allowed one concessionary grant in his lifetime. Upon return of Hong Kong to the People's Republic of China on July 1st, 1997, the traditional rights of indigenous villagers are protected under Article 40 of the Basic Law (a mini-constitution of the Hong Kong Special Administrative Region). Also all N.T. leases have been extended for 50 years up to 2047. Owing to the escalating demand and spiral landed property prices in recent years, abuse of the N.T. Small House Policy has been reported in some areas and is a concern in some quarters. The Hong Kong Institute of Land Administration attempts to study the history that leads to the current rural housing policy in the New Territories with particular emphasis on the small house policy, hoping that some light can be shed on the "way forward" for such a controversial policy.

• Korean Journal of Heritage: History & Science
• /
• v.52 no.4
• /
• pp.56-77
• /
• 2019

Bi-Seok is a treasure trove of funeral rites and an important cultural asset that can shed light on the historical and social history of calligraphy, but research of the topic is still insignificant. In particular, research on the production method of Bi-Seok remains an unproven field. The production of Bi-Seok can be roughly divided into ma-jeong (refining stone), sculpture, and the Buk-chil (process of engraving letters) process. This article reveals some facts: First, performing ma-jeong to the Sang-Seok, Honyu-Seok, Bi-seok, which are known to be God's things. This process is needed because of the change in the perception of the Honyu-Seok due to the settlement and propagation of Confucian ceremonial rituals in the times of hardship in 1592 and 1636. As the crafting process of ma-jeong did not remain concrete, it was only possible to examine the manufacturing process of Bi-Seok through its materials and tools. Second, the rapid proliferation of Oh-Seok and Sa-jeo-chwi-yong (purchase of things made by private citizens) in the Yeongjo era has great importance in social and cultural history. When the Gang-Hwa-Seok of the commodity were exhausted, the Oh-Seok that was used by Sadebu (upper civil class) were used in the tomb of Jangneung, which made Oh-Seok popular among people. In particular, the use of Oh-Seok and the Ma-Jeong process could minimize chemical and physical damage. Third, the writing method of the Bi-seok is Buk-chil. After Buk-Chil of Song Si-Yeol was used on King Hyojong's tomb, the Buk-Chil process ( printing the letters on the back of the stone and rubbing them to make letters) became the most popular method in Korea and among other East Asian countries, and the fact that it was institutionalized to this scale was quite impressive. Buk-Chil became more sophisticated by using red ink rather than black ink due to the black color that results from Oh-Seok. Fourth, the writing method changes in the late Joseon Dynasty. Until the time of Yeongjo's regime, when inscribing, the depth of the angle was based on the thickness of the stroke, thus representing the shade. This technique, of course, did not occur at every Pyo-Seok or Shindobi, but was maintained by outstanding artisans belonging to government agencies. Therefore, in order to manufacture Bi-Seok, Suk-seok, YeonJeong, Ma-jeong, Jeong-Gan, ChodoSeoIp, Jung-Cho, Ip-gak, Gyo-Jeong, and Jang-Hwang, a process was needed to make one final product. Although all of these methods serve the same purpose of paying respects and propagandizing the great work of deceased persons, through this analysis, it was possible to see the whole process of Pyo-Seok based upon the division of techniques and the collaboration of the craftsmen.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.23-46
• /
• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of the Korean Society of School Health
• /
• v.11 no.2
• /
• pp.297-307
• /
• 1998

The purpose of this paper is to understand the prescription and management of medicines by school-nurses. A survey was mailed to 199 school-nurses in elementary and secondary schools in Pusan from February 10 to March 31, 1997. It was shown that 97.0% of the schools have visiting school-doctors and only 29.6% have visiting school-pharmacists. 36.7% of the respondents don't know the amount of this annual health-related budget. Concerning the annual budget of purchasing medicines, 50.4% of the elementary schools spend 210,000 won to 400,000 won and 45.0% of the secondary schools spend more than 610,000 won. 56.3% of the respondents said the budget was enough, but 5% said it was not. 70.9% of the schools purchase medicines twice a year. The average number of students visiting the nurse in a year are 1,892 in elementary schools, 1.6 times per student and 2,471 in secondary schools, 1.7 times per student, respectively. The annual average number of students who were prescribed medicine a year are 1,804 in elementary schools, 1.5 times per student, 2,372 in secondary schools, 1.7 times per student. The percentage of students who are prescribed internal medicines was 45.5% in elementary, schools and 61.3% in secondary schools, respectively. To the preralence sicknesses, the wound was the most common, accounting for 42.7% in elementary and 22.6% in secondary schools. Next was abdominal pain, indigestion, and headaches in elementary schools; and colds, indigestion, and abdominal pain in secondary schools, respectively. To the dirersity of medicines prescribed: internal medicines 29 for abdominal pain, 25 for indigestion, 8 for physiological pain, 13 for headaches, 30 for colds, and 10 for eye disease; external medicines 2 for skin disease, 10 for toothaches and 31 for other sicknesses. 42.7% of the respondents said the schools have enough medicines, but 7.6% said that schools need more. 50.8% of the respondents said they get information on medicines from TV advertisements or medicine-related books, 16.6% get information from visiting pharmacists. More experienced nurse-teachers are likely to get information from visiting pharmacists, but 37.5% of the respondents who have less then four year experience in school get information through other nurse-teachers before deciding to buy medicines. To the choice of medicines: 83.9% of the respondents said that they choose safe medicines with less side-effects. 40.7% responded that they write down the prescription history daily, but 6.1% said they do this only once in two or three months. To the confidence in prescriptions, 37.7% of the respondents said they are sure of the effectiveness of the medicines they prescribe. To what extent the nurse-teachers prescribe, 50.3% said they prescribe to the level of anagelics, and 21.1% prescribe to anti-histamines and antibiotics. 80.4% said that the details of illnesses and medicines to be prescribed in school should be regulated by a school health-care law. To the problems in prescription, 79.9% of the respondents worry about abuse by students who want prescriptions but have no serious illnesses, 57.8% worrg about the lack of information on medicines and dosage. And 55.8% said they can't tell the difference between medicines whose brands are different, but bare the same ingredients. The conclusion of this study is that a health education program is necessary to prevent the misuse or abuse by students and a continuing education program for school-nurses is needed to solve the problems related to the purchasing and prescription of medicines. The criteria of the prescription of medicines also should be regulated by a school health-care law or management acts.

• Journal of Environmental Health Sciences
• /
• v.43 no.1
• /
• pp.1-22
• /
• 2017

'The worstest environment disaster', 'World's first biocide massacre', 'Home-based Sewol ferry disaster' are all phrases attached to the recent humidifier disinfectant disaster. In the spring of 2011, four of 8 pregnant women including 1 adult man passed away at a university hospital in Seoul due to breathing failure. Epidemiologic investigation conducted by the Korean CDC soon revealed the inhalation of humidifier disinfectant, which had been widely used in Korea during the winter, to be responsible for the disease. As well as lung fibrosis hardening of the lungs, other diseases including asthma, rhinitis, skin disease, liver disease, fetal disease or cancers have been researched for their relation with exposure to the products. By February 9, 2017, 5,342 cases had registered for health problems and 1,131 of them were already dead (20.8% mortality rate). Based on studies by government agencies and a telephone survey of the general population by Seoul National University and civic groups, around 20% of the general public of Korea has used these products. Since the market release of the first product by SK Chemical in 1994, over 7.1 million items from around 20 brands were sold up to 2011. Most of the products were manufactured by well-known large conglomerates such as SK, Lotte, Samsung, Shinsegye, LG, and GS, as well as some European companies including UK-based Reckitt Benckiser and TESCO, the German firm Henkel, the Danish firm KeTox, and an Irish company. Even though this disaster was unveiled in 2011 by the Korean government, the issue of the victims was neglected for over five years. In 2016, an unexpected but intensive investigation by prosecutors found that Reckitt Benckiser manipulated and concealed animal tests for its own brand and brought several university experts and company employees to court. The matter was an intense social issue in Korea from May to June with a surge in media coverage. The prosecutor's investigation and a nationwide boycott campaign organized by victims and environmental groups against Reckitt Benckiser, whose product had been used by more than 70% of victims, led to the producer's official apology and a compensation scheme. A legislative investigation organized after the April 2016 national election revealed the producers' faults and the government's responsibility, but failed to meet expectations. A special law for the victims passed the National Assembly in January 2017 and a punitive system together with a massive environmental epidemiology investigation are expected to be the only solutions for this tragedy. Sciences of medicine, toxicology and environmental health have provided decisive evidence so far, but for the remaining problems the perspectives of social sciences such as sociology and jurisprudence are highly necessary, similar to with the Minamata disease and Wonjin Rayon events. It may not be easy to follow this issue using unfamiliar terminology from medical and chemical science and the long, complicated history of the event. For these reasons the author has attempted to write this article in a question and answer format to render it easier to follow. The 17 questions are: Q1 What is humidifier disinfectant? Q2 What kind of health problems are caused by humidifier disinfectant? Q3 How many victims are there? Q4 What is the analysis of the 1,112 cases of death? Q5 What is the problem with the government's diagnostic criteria and the solution? Q6 Who made what brands? Q7 Has there been a recall? What is still on sale? Q8 Was safety not checked by any producers? Q9 What are the government's responsibilities? Q10 Is it true that these products were sold only in Korea? Q11 Why and how was it unveiled only in 2011 after 17 years of sales? Q12 What delayed the resolution of the victim issue? Q13 What is the background of the prosecutor's investigation in early 2016? Q14 Is it possible to report new victim cases without evidence of product purchase? Q15 What is happening with the victim issue? Q16 How does it compare with the cases of Minamata disease and Wonjin Rayon? Q17 Are there prevention measures and lessons?

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.6
• /
• pp.1-11
• /
• 2019

This study aims to understand the tendencies and characteristics when constructing landscape architectural archives in the United States, and to find implications for creating Korean landscape architectural archives. Focusing on seven American landscape architectural archives operated by public institutes, universities, and research institutes, this study examines the background, mission, scope, subject, acquisition, arrangement, and application of the programs in the archives. The results show that the characteristics of the American landscape architectural archives are as follows: first, the recognition of the value and importance of the landscape plays a major role in the establishment of archives; second, the purpose of the archives is to educate and encourage people to find diversity or significance of landscapes; third, the subject and scope of the archives vary according to the purpose of each operating institution; fourth, the main acquisitional method is to receive a donation and to purchase materials or documents; fifth, the classification systems of each archive differs depending on the subject and scope; and sixth, the archives were built on the basis of participation and collaboration with various experts and organizations with stable and sustainable financial resources. These characteristics offer three implications for constructing landscape architectural archives in Korea. First, a long-term vision for landscape architectural archives and the establishment of differentiated themes are required. Second, appropriate methods of material collection and systems of classification, recording, and digitization are necessary and therefore research and pilot archives are required. Third, it is necessary to secure the sustainability of archives by developing ways to utilize the archives in connection with academic and educational programs, thereby securing financial resources and allowing for the establishment of appropriate policies. As basic research, this study is significant as it provides a basis for further research concerning the development of landscape architectural archives in Korea.

• Journal of agricultural medicine and community health
• /
• v.12 no.1
• /
• pp.102-110
• /
• 1987

One of the familiar medical facility that most people reach easily in Korea is the drug store. In Korea, it is possible to purchase all kinds of common drugs without physician's prescriptions, which caused some problems. In other words, such treatment without professional supervision has led to medical, social and economical problems. In view of the above, this study is aimed at revealing the actual status of long-term use of drugs in some urban residents. Long-term use of drugs is operationally defined as using certain drugs at least once a week for more than 3 months. This survey took the residents of Guro 6-Dong where was one of the target areas for Community Health Development Project managed by Korea University as a target population. A sample of 1,517 residents was selected by the multistage sampling method. The interview was conducted on September 21st and 22nd in 1985. The object of this study was to compare the result with that of the rural area which was obtained by the same method, tools and research team, prior to this study in 1984. The results were as follows; 1) The age-standardization of the study showed that 97 per 1,000 urban residents were actually on long-term drug use. The prevalance of long-term use is high in accordance with aging and low with education level. 2) Out of 1,000 urban samples the most popular item involved in the long-term drug use was antipyretic-analgesic-antiinflammatory drug (26), and next in order was vitamin (23), antibiotics (13), digestives (10) and antacids (7). In the rural samples as for compare, that was antipyretic-analgesic-antiinflammatory drug (100), antacids (36), digestives (23), adrenocortical hormones (12) etc. 3) With antipyrctic-analgesic-antiinflammatory drugs, 50% of the urban samples were taking for more than a year, whereas such were 82.7% of the rural samples. Using such a high percentage of antipyretic-analgesic-antiinflamatory drugs in the rural residents is probably due to the high prevalence rate of musculo-skeletal diseases. 4) The urban long-term drug users of antipyretic-analgesic-antiinflammatory drugs were influenced mostly by the mass media (43.6%), next in order was pharmacist (35.9%) and physician (10.3%). Comparing with the result from the rural areas the role of mass media was much more influencial in the urban areas. 60% of them consulted with pharmacists, 14.3% with physicians and 25.7% had no history of consultation in the urban samples. 5) Considering the incidence of knowing the possible side-effects of each drug, 28.2% of the urban residents had no recognition about side-effects prior to use antipyretic-analgesic-antiinflammatory drugs. In the rural residents, 29.67o had no knowledge about the side-effects before using the drug. 6) For the solution of the above problems, it is necessary to limit the advertisement of some drugs by the parmaceutical company. And therapeutic drugs which may bring on side effects in case of long-term use should not be sold at drug stores without physician's prescription.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.93-107
• /
• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Asia pacific journal of information systems
• /
• v.20 no.1
• /
• pp.81-99
• /
• 2010

Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.