• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.127-135
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• 2014

Purpose : By taking advantage of each imaging modality, the use of fused CT/MRI image has increased in prostate cancer radiation therapy. However, fusion uncertainty may cause partial target miss or normal organ overdose. In order to complement such limitation, our hospital acquired MRI image (Planning MRI) by setting up patients with the same fixing tool and posture as CT simulation. This study aims to evaluate the usefulness of the Planning MRI through comparing and analyzing the diagnostic MRI image and Planning MRI image. Materials and Methods : This study targeted 10 patients who had been diagnosed with prostate cancer and prescribed nonhormone and definitive RT 70 Gy/28 fx from August 2011 to July 2013. Each patient had both CT and MRI simulations. The MRI images were acquired within one half hour after the CT simulation. The acquired CT/MRI images were fused primarily based on bony structure matching. This study measured the volume of prostate in the images of Planning MRI and diagnostic MRI. The diameters at the craniocaudal, anteroposterior and left-to-right directions from the center of prostate were measured in order to compare changes in the shape of prostate. Results : As a result of comparing the volume of prostate in the images of Planning MRI and diagnostic MRI, they were found to be $25.01cm^3$(range $15.84-34.75cm^3$) and $25.05cm^3$(range $15.28-35.88cm^3$) on average respectively. The diagnostic MRI had an increase of 0.12 % as compared with the Planning MRI. On the planning MRI, there was an increase in the volume by $7.46cm^3$(29 %) at the transition zone directions, and there was a decrease in the volume by $8.52cm^3$(34 %) in the peripheral zone direction. As a result of measuring the diameters at the craniocaudal, anteroposterior and left-to-right directions in the prostate, the Planning MRI was found to have on average 3.82cm, 2.38cm and 4.59cm respectively and the diagnostic MRI was found to have on average 3.37cm, 2.76cm and 4.51cm respectively. All three prostate diameters changed and the change was significant in the Planning MRI. On average, the anteroposterior prostate diameter decrease by 0.38cm(13 %). The mean right-to-left and craniocaudal diameter increased by 0.08cm(1.6 %) and 0.45cm(13 %), respectively. Conclusion : Based on the results of this study, it was found that the total volumes of prostate in the Planning MRI and the diagnostic MRI were not significantly different. However, there was a change in the shape and partial volume of prostate due to the insertion of prostate balloon tube to the rectum. Thus, if the Planning MRI images were used when conducting the fusion of CT/MRI images, it would be possible to include the target in the CTV without a loss as much as the increased volume in the transition zone. Also, it would be possible to reduce the radiation dose delivered to the rectum through separating more clearly the reduction of peripheral zone volume. Therefore, the author of this study believes that acquisition of Planning MRI image should be made to ensure target delineation and localization accuracy.

• Journal of Distribution Science
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• v.10 no.4
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• pp.47-53
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• 2012

Businesses make use of advertising strategy using models to give consumers efficient product information. Modern advertisements often make use of models for greater reminiscence to create messages and remind viewers of the product. The purpose of this study was to examine the characteristics of each type of model. The subjects were 230 college students in their twenties or older, and the material was collected from October 20, 2011 to November 5, 2011 to examine the effects of model characteristics on buying intention as well as attitude toward a brand. A questionnaire survey was used; investigators gave one copy to each interviewee. The study investigated the characteristics of each model using a questionnaire of each 40 copies with five kinds of photographs. The characteristics of models had great influence on buying intention and attitude toward the brand: First, factor 2 (being honest and virtuous and having good credit and a good press assessment) and factor 3 (being interesting and a good communicator and creating good memories) had great influence on buying intention. Factor 2 was explained by reliability, and factor 3 by the efficiency of the model in creating a feeling. Second, factors 1 (being attractive, smart, unique, friendly, loved by others, and popular), 2, and 3 influenced attitude toward brand. Factor 1 encapsulated the outgoing characteristics of a model, factor 2 was based on reliability, and factor 3 was based on the efficiency of the model in creating a feeling. The model's positive effects on buying intention and attitudes toward brand shall be examined. For their positive influence on buying intention, reliability and efficiency shall be given attention. For their positive influence on attitude toward brand, creating a good impression, having outgoing characteristics, being reliable, and efficiency shall be given attention. The findings were as follows: Model characteristics influencing buying intention were similar to those influencing attitude toward brand. The differences were as follows. First, reliability and efficiency influenced buying intention. When customers were asked to consider the influence on buying intention of an advertisement, regardless of the strength of the buying intention, they considered these two characteristics. Customers decided to buy based not only on the credibility of the product as presented in the advertisement but also the transmission of the contents of the advertisement. Second, outgoing characteristics, reliability, and efficiency influenced attitude toward a brand. The attitude toward a brand was said to be the attitude toward the business. The attitude is produced even after buying, so businesses view it as very important. The attitude might vary depending upon the model used rather than the brand. Therefore, a model with outgoing characteristics was thought to be important. Therefore, attitude toward a brand whose model influenced buying intention as well as attitude toward brand had outgoing characteristics. The result is that an image the model was related to attitude toward the brand. As such, customers would buy the goods advertised. However, an outgoing image of a model was also important to create a positive attitude toward a business brand. For instance, talent Park Gyeong-Rim's photo was used to promote cosmetics about 10 years ago. When she worked as a model of cosmetics products, she had to make compensation for losses and damages because she made a mistake on a talk show program. At that time, customers who had bought the cosmetics product asked for refunds of several billion won. As such, models who are said to be the face of the businesses they represent can play an important role. To advertise in the most attractive and effective way, the current image of a model should be investigated by examining current activities and news articles after selecting the model, and the model's efficiency and attitude toward the brand should be examined. Factors that stimulate customers' buying decisions can be used to plan advertisement that have positive influence on a brand. This study had the limitation of investigating mainly college students and there were insufficient copies of the questionnaire. The investigation was not done widely but in detail so that a concrete investigation could not be done. Further studies shall supplement these shortcomings and discuss new directions.

• The Journal of Korean Academy of Prosthodontics
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• v.47 no.4
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• pp.365-375
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• 2009

Statement of problems: Stress analysis on implant components of the combined screw- and cement-retained implant prosthesis has not investigated yet. Purpose: The purpose of this study was to assess the load distribution characteristics of implant prostheses with the different prosthodontic retention types, such as cement-type, screw-type and combined type by using 3-dimensional finite element analysis. Material and methods: A 3-dimensional finite element model was created in which two SS II implants (Osstem Co. Ltd.) were placed in the areas of the first premolar and the first molar in the mandible, and three-unit fixed partial dentures with four different retention types were fabricated on the two SS II implants. Model 1 was a cement-retained implant restoration made on two cement-retained type abutments (Comocta abutment; Osstem Co. Ltd.), and Model 2 was a screw-retained implant restoration made on the screw-retained type abutments (Octa abutment; Osstem Co. Ltd.). Model 3 was a combined type implant restoration made on the cement-retained type abutment (Comocta abutment) for the first molar and the screw-retained type abutment (Octa abutment) for the first premolar. Lastly, Model 4 was a combined type implant restoration made on the screw-retained type abutment (Octa abutment) for the first molar and the cement-retained type abutment (Comocta abutment) for the first premolar. Average masticatory force was applied on the central fossa in a vertical direction, and on the buccal cusp in a vertical and oblique direction for each model. Von-Mises stress patterns on alveolar bone, implant body, abutment, abutment screw, and prosthetic screw around implant prostheses were evaluated through 3-dimensional finite element analysis. Results: Model 2 showed the lowest von Mises stress. In all models, the von Mises stress distribution of cortical bone, cancellous bone and implant body showed the similar pattern. Regardless of loading conditions and type of abutment system, the stress of bone was concentrated on the cortical bone. The von-Mises stress on abutment, abutment screw, and prosthetic screw showed the lower values for the screw-retained type abutment than for the cement-retained type abutment regardless of the model type. There was little reciprocal effect of the abutment system between the molar and the premolar position. For all models, buccal cusp oblique loading caused the largest stress, followed by buccal cusp vertical loading and center vertical loading. Conclusion: Within the limitation of the FEA study, the combined type implant prosthesis did not demonstrate more stress around implant components than the cement type implant prosthesis. Under the assumption of ideal passive fit, the screw-type implant prosthesis showed the east stress around implant components.

• The Korean Journal of Air & Space Law and Policy
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• v.23 no.2
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• pp.67-92
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• 2008

The purpose of this paper is to research the requirements and effect of the document of carriage in respect of the carriage of cargo by air under the Montreal Convention of 1999, IATA Conditions of Carriage for Cargo, and the judicial precedents of Korea and foreign countries. Under the Article 4 of Montreal Convention, in respect of the carriage of cargo, an air waybill shall be delivered. If any other means which preserves a record of the carriage are used, the carrier shall, if so requested by the consignor, deliver to the consignor a cargo receipt. Under the Article 7 of Montreal convention, the air waybill shall be made out by the consignor. If, at the request of the consignor, the carrier makes it out, the carrier shall be deemed to have done so on behalf of the consignor. The air waybill shall be made out in three original parts. The first part shall be marked "for the carrier", and shall be signed by the consignor. The second part shall be marked "for the consignee", and shall be signed by the consignor and by the carrier. The third part shall be signed by the carrier who shall hand it to the consignor after the goods have been accepted. Under the Article 5 of Montreal Convention, the air waybill or the cargo receipt shall include (a) an indication of the places of departure and destination, (b) an indication of at least one agreed stopping place, (c) an indication of the weight of the consignment. Under the Article 10 of Montreal Convention, the consignor shall indemnify the carrier against all damages suffered by the carrier or any other person to whom the carrier is liable, by reason of the irregularity, incorrectness or incompleteness of the particulars and statement furnished by the consignor or on its behalf. Under the Article 9 of Montreal Convention, non-compliance with the Article 4 to 8 of Montreal Convention shall not affect the existence of the validity of the contract, which shall be subject to the rules of Montreal Convention including those relating to limitation of liability. The air waybill is not a document of title or negotiable instrument. Under the Article 11 of Montreal Convention, the air waybill or cargo receipt is prima facie evidence of the conclusion of the contract, of the acceptance of the cargo and of the conditions of carriage. Under the Article 12 of Montreal Convention, if the carrier carries out the instructions of the consignor for the disposition of the cargo without requiring the production of the part of the air waybill or the cargo receipt, the carrier will be liable, for any damage which may be accused thereby to any person who is lawfully in possession of that part of the air waybill or the cargo receipt. According to the precedent of Korea Supreme Court sentenced on 22 July 2004, the freight forwarder as carrier was not liable for the illegal delivery of cargo to the notify party (actual importer) on the air waybill by the operator of the bonded warehouse because the freighter did not designate the boned warehouse and did not hold the position of employer to the operator of the bonded warehouse. In conclusion, as the Korea Customs Authorities will drive the e-Freight project for the carriage of cargo by air, the carrier and freight forwarder should pay attention to the requirements and legal effect of the electronic documentation of the carriage of cargo by air.

• Tuberculosis and Respiratory Diseases
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• v.44 no.2
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• pp.241-250
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• 1997

Objective : Although the prevalence of pulmonary tuberculosis has decreased progressively after the national control program for tuberculosis began, nowadays the number of MDRTB is increasing seriously. MDRTB tends to be poor responsive to current antituberculosis regimens. It is mainly due to poor compliance, high rate of side reaction of secondary drugs, and limitation in number of available drugs. The purpose of present study is to evaluate the clinical features of pulmonary tuberculosis patients admitted in one national tuberculosis hospital and to expose the problems pertaining to current remedies, to increase the treatment efficacy for pulmonary tuberculosis including MDRTB in the end. Method : Retrospective analysis of 336 pulmonary tuberculosis patients admitted in National Masan Tuberculosis Hospital was done. Contents of analysis were patients profile, the first diagnosed time and medical institutes, family history, residence, previous treatment history, chief complaints at the time of admission, lesion site on chest X -ray film, combined deseases, side reaction to antibuberculosis drugs, used drugs before admission and the results of drug sensitivity test. Results : The ratio between male and female was 4 : 1. Age showed relatively even distribution from 3rd to 6 th decades. 64.6% of the patients was diagnosed at public health center. Weight loss was the most common complaint at admission. Bilateral lesions on chest X-ray films were 59.8%. 130patients had combined desease, of which DM was the most common(37.7%). 95patients had family history, of which parents were the most common(41.7%). According to the time of first diagnosis, 31 patients were diagnosed before 1980, and after then the number of patients was increased by degrees. Residence overwhelmed in pusan and gyung-nam province. 258 patients got previous treatment history, of which 112 patients(43.4%) had more than 3 times and only 133 patients(51.6%)got regular medication. 97 patients used more than other 3 drugs in addition to INH, EMB, RFP and PZA before admission. 154 patients were informed with the results of drug sensitivity test. of which 77 patients had resistance to more than 5 drugs. Gastrointestinal problem was the most common in side reaction to drugs. Conclusion : In the case of weight loss of unknown cause, tuberculosis should be suspected. In first treatment, sufficient and satisfactory explanation for tuberculosis is necessary and treatment period should not be stict to 6 month-short term therapy. In retreatment, new drugs should not be added to used drugs even though drug sensitivity results show sensitivity to some of them. Proper time for surgical intervention should not be delayed.

• Journal of Global Scholars of Marketing Science
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• v.18 no.1
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• pp.33-58
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• 2008

Previous research has presupposed that the evaluation of consumer who received any recovery after experiencing product failure should be better than the evaluation of consumer who did not receive any recovery. The major purposes of this article are to examine impacts of product defect failures rather than service failures, and to explore effects of recovery on postrecovery product attitudes. First, this article deals with the occurrence of severe and unsevere failure and corresponding service recovery toward tangible products rather than intangible services. Contrary to intangible services, purchase and usage are separable for tangible products. This difference makes it clear that executing an recovery strategy toward tangible products is not plausible right after consumers find out product failures. The consumers may think about backgrounds and causes for the unpleasant events during the time gap between product failure and recovery. The deliberation may dilutes positive effects of recovery efforts. The recovery strategies which are provided to consumers experiencing product failures can be classified into three types. A recovery strategy can be implemented to provide consumers with a new product replacing the old defective product, a complimentary product for free, a discount at the time of the failure incident, or a coupon that can be used on the next visit. This strategy is defined as "a rewarding effort." Meanwhile a product failure may arise in exchange for its benefit. Then the product provider can suggest a detail explanation that the defect is hard to escape since it relates highly to the specific advantage to the product. The strategy may be called as "a strengthening effort." Another possible strategy is to recover negative attitude toward own brand by giving prominence to the disadvantages of a competing brand rather than the advantages of its own brand. The strategy is reflected as "a weakening effort." This paper emphasizes that, in order to confirm its effectiveness, a recovery strategy should be compared to being nothing done in response to the product failure. So the three types of recovery efforts is discussed in comparison to the situation involving no recovery effort. The strengthening strategy is to claim high relatedness of the product failure with another advantage, and expects the two-sidedness to ease consumers' complaints. The weakening strategy is to emphasize non-aversiveness of product failure, even if consumers choose another competitive brand. The two strategies can be effective in restoring to the original state, by providing plausible motives to accept the condition of product failure or by informing consumers of non-responsibility in the failure case. However the two may be less effective strategies than the rewarding strategy, since it tries to take care of the rehabilitation needs of consumers. Especially, the relative effect between the strengthening effort and the weakening effort may differ in terms of the severity of the product failure. A consumer who realizes a highly severe failure is likely to attach importance to the property which caused the failure. This implies that the strengthening effort would be less effective under the condition of high product severity. Meanwhile, the failing property is not diagnostic information in the condition of low failure severity. Consumers would not pay attention to non-diagnostic information, and with which they are not likely to change their attitudes. This implies that the strengthening effort would be more effective under the condition of low product severity. A 2 (product failure severity: high or low) X 4 (recovery strategies: rewarding, strengthening, weakening, or doing nothing) between-subjects design was employed. The particular levels of product failure severity and the types of recovery strategies were determined after a series of expert interviews. The dependent variable was product attitude after the recovery effort was provided. Subjects were 284 consumers who had an experience of cosmetics. Subjects were first given a product failure scenario and were asked to rate the comprehensibility of the failure scenario, the probability of raising complaints against the failure, and the subjective severity of the failure. After a recovery scenario was presented, its comprehensibility and overall evaluation were measured. The subjects assigned to the condition of no recovery effort were exposed to a short news article on the cosmetic industry. Next, subjects answered filler questions: 42 items of the need for cognitive closure and 16 items of need-to-evaluate. In the succeeding page a subject's product attitude was measured on an five-item, six-point scale, and a subject's repurchase intention on an three-item, six-point scale. After demographic variables of age and sex were asked, ten items of the subject's objective knowledge was checked. The results showed that the subjects formed more favorable evaluations after receiving rewarding efforts than after receiving either strengthening or weakening efforts. This is consistent with Hoffman, Kelley, and Rotalsky (1995) in that a tangible service recovery could be more effective that intangible efforts. Strengthening and weakening efforts also were effective compared to no recovery effort. So we found that generally any recovery increased products attitudes. The results hint us that a recovery strategy such as strengthening or weakening efforts, although it does not contain a specific reward, may have an effect on consumers experiencing severe unsatisfaction and strong complaint. Meanwhile, strengthening and weakening efforts were not expected to increase product attitudes under the condition of low severity of product failure. We can conclude that only a physical recovery effort may be recognized favorably as a firm's willingness to recover its fault by consumers experiencing low involvements. Results of the present experiment are explained in terms of the attribution theory. This article has a limitation that it utilized fictitious scenarios. Future research deserves to test a realistic effect of recovery for actual consumers. Recovery involves a direct, firsthand experience of ex-users. Recovery does not apply to non-users. The experience of receiving recovery efforts can be relatively more salient and accessible for the ex-users than for non-users. A recovery effort might be more likely to improve product attitude for the ex-users than for non-users. Also the present experiment did not include consumers who did not have an experience of the products and who did not perceive the occurrence of product failure. For the non-users and the ignorant consumers, the recovery efforts might lead to decreased product attitude and purchase intention. This is because the recovery trials may give an opportunity for them to notice the product failure.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• 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.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.109-122
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• 2016

Recently, big data analysis has developed into a field of interest to individuals and non-experts as well as companies and professionals. Accordingly, it is utilized for marketing and social problem solving by analyzing the data currently opened or collected directly. In Korea, various companies and individuals are challenging big data analysis, but it is difficult from the initial stage of analysis due to limitation of big data disclosure and collection difficulties. Nowadays, the system improvement for big data activation and big data disclosure services are variously carried out in Korea and abroad, and services for opening public data such as domestic government 3.0 (data.go.kr) are mainly implemented. In addition to the efforts made by the government, services that share data held by corporations or individuals are running, but it is difficult to find useful data because of the lack of shared data. In addition, big data traffic problems can occur because it is necessary to download and examine the entire data in order to grasp the attributes and simple information about the shared data. Therefore, We need for a new system for big data processing and utilization. First, big data pre-analysis technology is needed as a way to solve big data sharing problem. Pre-analysis is a concept proposed in this paper in order to solve the problem of sharing big data, and it means to provide users with the results generated by pre-analyzing the data in advance. Through preliminary analysis, it is possible to improve the usability of big data by providing information that can grasp the properties and characteristics of big data when the data user searches for big data. In addition, by sharing the summary data or sample data generated through the pre-analysis, it is possible to solve the security problem that may occur when the original data is disclosed, thereby enabling the big data sharing between the data provider and the data user. Second, it is necessary to quickly generate appropriate preprocessing results according to the level of disclosure or network status of raw data and to provide the results to users through big data distribution processing using spark. Third, in order to solve the problem of big traffic, the system monitors the traffic of the network in real time. When preprocessing the data requested by the user, preprocessing to a size available in the current network and transmitting it to the user is required so that no big traffic occurs. In this paper, we present various data sizes according to the level of disclosure through pre - analysis. This method is expected to show a low traffic volume when compared with the conventional method of sharing only raw data in a large number of systems. In this paper, we describe how to solve problems that occur when big data is released and used, and to help facilitate sharing and analysis. The client-server model uses SPARK for fast analysis and processing of user requests. Server Agent and a Client Agent, each of which is deployed on the Server and Client side. The Server Agent is a necessary agent for the data provider and performs preliminary analysis of big data to generate Data Descriptor with information of Sample Data, Summary Data, and Raw Data. In addition, it performs fast and efficient big data preprocessing through big data distribution processing and continuously monitors network traffic. The Client Agent is an agent placed on the data user side. It can search the big data through the Data Descriptor which is the result of the pre-analysis and can quickly search the data. The desired data can be requested from the server to download the big data according to the level of disclosure. It separates the Server Agent and the client agent when the data provider publishes the data for data to be used by the user. In particular, we focus on the Big Data Sharing, Distributed Big Data Processing, Big Traffic problem, and construct the detailed module of the client - server model and present the design method of each module. The system designed on the basis of the proposed model, the user who acquires the data analyzes the data in the desired direction or preprocesses the new data. By analyzing the newly processed data through the server agent, the data user changes its role as the data provider. The data provider can also obtain useful statistical information from the Data Descriptor of the data it discloses and become a data user to perform new analysis using the sample data. In this way, raw data is processed and processed big data is utilized by the user, thereby forming a natural shared environment. The role of data provider and data user is not distinguished, and provides an ideal shared service that enables everyone to be a provider and a user. The client-server model solves the problem of sharing big data and provides a free sharing environment to securely big data disclosure and provides an ideal shared service to easily find big data.