• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.23-38
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• 2012

There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.

• Journal of Information Technology Application
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• v.2 no.1
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• pp.55-81
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• 2000

An Electronic Document Management System(EDMS) is an electronic system solution that is used to create, capture, distribute, edit, store and manage documents and related structured data repositories throughout an organization. Recently, documents of any type, such as text, images, and video files, and structured databases can be controlled and managed by an office automation system and an EDMS. Thus, many organizations are already using these information technologies to reduce process cycle-times. But what the organizations are missing is a integrated system the current workflow or office automation system and provides immediate access to and automatic routing of the organization's mission-critical information. This study tried to find out the user's requirements for integrating current information system and relatively new technology, electronic document management system in order to improve business operations, productivity and quality, and reduces waste. integration of electronic document management system(EDMS) and office automation system and proper use of these technological will improve organization's processes, and compress the process cycle-times. For this study a case study was done by a project team in cooperation with a government organization(say A company). Through this case study valuable electronic document management and office automation system requirement have been identified and reported for providing a system model in order to design an Integrated EDMS(IMDMS).

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.509-524
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• 1998

정보시스템 개발노력의 상당수는 실패로 끝나고 있다. 최근 통계에 따르면 정보시스템 개발 프로젝트의 반은 실패로 끝난다고 한다［kaplan, 1998］. 이와 같은 높은 실패율은 시스템 개발을 위한 노력을 체계적으로 투입하지 못하고 개발 프로젝트를 관리하기 위한 노력을 단위프로젝트 차원에서만 집중시키는데서 연유한다고 생각된다. 다시 말해 장기적인 관점에서 개발조직의 역량 향상이라는 보다 근본적인 목표를 간과하고 있는 것이다. 이러한 점에 착안하여 소프트웨어 엔지니어링 분야에서는 정보시스템 개발과 관련'한 개발 조직의 능력을 향상시키기 위한 다양한 접근방법이 제시되고 있다. 개발조직의 개발 프로세스 성숙도를 진단하기 위한 측정도구로 개발된 카네기멜론대학의 CMM(Capability Maturity Model)과 ISO 에서 정의한 표준인 SPICE (Software Process Improvement and Capability dEtermination) 모델이 그 대표적인 예에 속한다. 그러나 이와 같은 모델들은 개발조직의 프로세스 개선을 위한 방향과 요건은 제시하고 있지만, 이를 조직 내에서 구현하기 위한 구체적인 방법이나 수단은 제시해주지 못하고 있다. 따라서 이러한 접근방법 역시 소프트웨어 엔지니어링 역량 이나 개발경험이 일천한 우리 현실에서는 부분적인 성과 이상을 기대하기는 어려웠다. 본 연구에서는 이와 같은 문제점이 개발 프로젝트와 관련된 경험이나 지식을 효과적으로 추출하고, 획득하고, 체계화하고, 시스템화하여 조직 내에서 활용하려는 노력이 부족한기 때문이라고 본다. 이에 본 연구에서는 개발조직의 역량 향상을 위한 지식관리적 접근 방법의 세가지 유형을 제시하기로 한다.>$Ca^{2＋}$ 는 뿌리에서, $Mg^{2＋}$ 는 잎에서 많았으며, $PO_4$$^{-}$ 는 과실과 줄기에서 많았다. 배지간에 따른 차이는 나타나지 않았으며, $K^{+}$, $Ca^{2＋}$ 및 $Mg^{2＋}$ 는10:0에서, $PO_4$$^{-}$ 는 8:2에서 각각 많았다.해 제품을 판매하였으며, 기업 및 제품이미지 제고를 위한 고객에 대한 서비스도 강화하고 있었다. 통신기기업체내지 소프트웨어 산업으로의 진출이 가능할 수 있도록 상호진출을 허용할 필요가 있다고 본다. 이를 위해서 우리 나라 정부 역시 미국처럼 새로운 통신개혁법을 만들 필요가 있다. 새로운 통신개혁법의 핵심적인 사항으로서 첫째, 통신과 CATV간의 상호진입을 허용, 둘째, 통신사업자가 통신관련 기기산업에 참여할 수 있는 규제완화를 허용, 셋째, 유아단계에 있는 소프트웨어 및 컨테트산업을 육성하는데 산업육성책 수립 등을 적극적으로 추진하여야 할 것이다. 그리고 현재 국내 재벌기업들로 구성되어 있는 기반산업을 지원하는 기술개발 지원체제와 육성정책을 소프트웨어 및 컨텐트의 응용산업으로 개편할 필요성도 제시되며, 이를 위해 범부처 차원에서 소프트웨어 및 컨텐트 육성정책을 지원하는 종합적인 대책을 마련해야 한다고 본다.서, Li-K, Li-Na탄산염에 대하여 부 식거동을 검토한 결과, 가압하에서 내식성이 향상되는 것이 발견되었다. 이유로서는 가압하에서 용융탄산엽의 증가된 산화력으로 보다 치밀한 내식성 산화물 피막이 형성되기 때문으로 생각되고 있다. 또

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.402-411
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• 2013

Mobile contents market is growing with the rapid adoption of smart-phones. Online access via mobile compared to PC-based online access, has distinctive service delivery characteristics which are ubiquitous connectivity and contextual offer. In addition, this study includes characteristics which are relatively disadvantageous for mobile services compared to PC-based services. These are response time and supporting non-verbal informations. This study investigates the influence of service delivery characteristics to perceived interactivity and mobile service attitude. The results show that mobile services' ubiquitous connectivity and contextual offer showed a positive relationship with the perceived interactivity of the mobile service. And the response time also showed a positive relationship with the perceived interactivity, but non-verbal information didn't. When the trade-off is met between response time and nonverbal information, mobile service developer should choose response time since it has positive effect on perceived interactivity and attitude.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.687-693
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• 2010

Information Technology Service Management (ITSM) System has been adopted and operated by many governments and public institutions to intensify their global competitiveness. Recently these organizations are facing many problems because of the increased demands and complexity of Information Technology (IT) service. Especially, difficulty with ITSM gets bigger and bigger because of increasing IT outsourcing. An expectation regarding ITSM is grown up when facing to solve problems. Therefore, this study suggests effective alternatives about ITSM organization structure for public sectors. The ITSM organization structures changes from traditional structures based on functions to new structures based on its goal, customer, and its process. In other words, ITSM organizational structure can be composed of Service Strategy directorate, Service Design directorate, Service Transition directorate, Service Operation directorate, and Service Improvement directorate. To ensure the effectiveness and the professionalism of ITSM in an organization, this paper specifies the roles of participants and the responsibilities for each unit. The proposed ITSM organization structures will be useful for public sectors.

• Convergence Security Journal
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• v.16 no.7
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• pp.101-111
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• 2016

The recent cyber threats are becoming real threats to our lives. This gloomy situation from cyber threats necessarily demands the establishment of the cyber threat information sharing system between the public and private area. Key countries, like the US, Japan and the UK, are stabilizing the cyber threat information sharing systems by founding exclusive organizations for sharing information and setting up and implementing relevant measures. In this thesis, I would like to propose the model for cyber threat information sharing in order to cope efficiently with the ever-intensifying cyber threats. My model would include key elements for the efficient information sharing, such as the clear designation of main operator of information sharing system, the management of collaboration system between the public and private sector, the build-up of the integrated and automated system and the supplementation of legal system including the grant of privilege, and so on.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 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 Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.51-60
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• 2003

In the radical char]go of the business environments that the existing facilities can not guarantee the business-frosts anymore, enterprises have been importing ERP system. In Korea, Sam-sung Electronics did it for the first tin in the latter half of 1994 and other enterprises succeeded. Currently, government and public enterprises as well as most of the large enterprises are employing ERP system to sharpen the competitiveness and to win the business transparency. On the other hand, it is harder for small and medium enterprises shaded by the large enterprises to be well-equipped with information system such as ERP, because they have already suffered from chronic financial difficulties and shortage of many resources. Most of all, they prefer the short-term project that does not need much tine for them to make decisions and to carry out fully. Grounded on the above factors, in this work, I suggest the suitable ERP model for the small and medium enterprises and the successful importing process of ERP, which is derived from the previous researches made by other masters' thesis. If necessary information and human resources are interchanged pertinently between local education institute and small and medium enterprise, the latter could not only deal with the confronted difficulties successfully inside and outside but attain the goal of being proficient in up-to-minute high technology. Besides, giving the students the opportunity of researching into the practice of the business they have not ever known, local universities could help their students accumulate knowledges and acquire ideas which could not be achieved in pure academic studies. When the above-mentioned procedure is over, the students might get the intellectual faculty to ponder on the future more concretely and enter a profession more carefully. In the result, we would raise up the percentage of the employment among the graduates. And active participation of university professors is the last important factor that assists the small and medium enterprises for introducing ERP system successfully. Their scholarly attainments play an important role in strengthening local economy and make the business competitiveness balanced between the capital and the local economy.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.91-110
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• 2011

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.