• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.175-192
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• 2022

Artificial intelligence-based natural language processing technology is playing an important role in helping users write English-language documents. For academic documents in particular, the English proofreading services should reflect the academic characteristics using formal style and technical terms. But the services usually does not because they are based on general English sentences. In addition, since existing studies are mainly for improving the grammatical completeness, there is a limit of fluency improvement. This study proposes an automatic academic English editing methodology to deliver the clear meaning of sentences based on the use of technical terms. The proposed methodology consists of two phases: misspell correction and fluency improvement. In the first phase, appropriate corrective words are provided according to the input typo and contexts. In the second phase, the fluency of the sentence is improved based on the automatic post-editing model of the bidirectional recurrent neural network that can learn from the pair of the original sentence and the edited sentence. Experiments were performed with actual English editing data, and the superiority of the proposed methodology was verified.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.15-22
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• 2017

Purpose - Retail companies are turning from one type of retailer to multiple business categories through various reasons, such as taking advantage of existed types of retailers' channel distribution, information and know-how, and entering into new types of retailers. However, there is few research conducted about multiple type of retailers. Research design, data, and methodology - In this research, the references, data and new stores on E-mart will be collected. The dissertation, annual report, statistical data, land-book of E-mart will be also collected to confirm whether E-mart has made any acquisition towards another company. Results - There is a tendency to new stores expansion, store enlargement and prolonging the opening preparation of new stores, based on the core of new stores expansion of E-mart as a general supermarket type of retailers. Based on general supermarket type of retailers, E-mart begins to diversify its retail company's type of retailers. Conclusions - As a general supermarket which is the most important type of retailers, E-mart is expanding into SSM type of retailers to seek new power of growth while slowdown growth is shown in general supermarket type of retailers. The expansion into SSM type of retailers would be a wise option as a retail company, E-mart is able to keep growing in the future.

• The Journal of Society for e-Business Studies
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• v.14 no.3
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• pp.39-57
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• 2009

As electronic commerce becomes more common and the data volume of e-catalog increases, a systematic approach to data quality management is being required. Upon the necessity, we propose a process-based framework for e-catalog data quality management. This is the methodology for data management and improvement activities continuously performed to satisfy the expectation of industry to e-catalog systems. In the framework, contents for quality management consist of data, quality management items, and quality management processes. These are again subdivided according to organization levels, i.e, user, data administrator, and chief information officer.

• East Asian Journal of Business Economics (EAJBE)
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• v.1 no.1
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• pp.17-21
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• 2013

Purpose: Forecasting of petroleum consumption is useful in planning and management of petroleum production and control of air pollution. Research Design, Data and Methodology: ARMA models, sometimes called Box-Jenkins models after the iterative Box-Jenkins methodology usually used to estimate them, are typically applied to auto correlated time series data. Results: Petroleum consumption modeling plays a role key in big urban air pollution planning and management. In this study three models as, MLFF, MLFF with GARCH (1,1) and ARMA(1,1), have been investigated to model the petroleum consumption forecasts. Certain standard statistical parameters were used to evaluate the performance of the models developed in this study. Based upon the results obtained in this study and the consequent comparative analysis, it has been found that the MLFF with GARCH (1,1) have better forecasting results.. Conclusions: Survey of data reveals that deposit of government policies in recent yeas, petroleum consumption rises in Tehran and unfortunately more petroleum use causes to air pollution and bad environmental problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.430-460
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• 2004

This study presented a personalization system that adopted a methodology which is applicable for digital content recommendation and executed by the Internet service providers. The system made a recommendation to the users on the basis of their preferences, while most techniques for recommending digital content have focused on considering the similarity of content. In addition, it developed a method of evaluation to determine the priority of recommendations and adopted measures when selecting a set of recommendations. To experiment the feasibility and effectiveness of the presented methodology, a prototype system was developed and was applied to an English newspaper on the Internet.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.63-76
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• 2020

In the 21st century, informatization is playing a huge role in people's lives. Korea is experiencing the tremendous changes in social structure and lifestyle caused by informatization. This paper focuses on economic phenomena rather than discussion on social structure due to informatization. We check whether the Goodwin model, which can comprehensively express economic growth, economic cycle, and income distribution, is suitable for the Korean economy in the information age. This model is simulated by selecting a quantitative economic methodology that estimates coefficients from time series data of the Korean economy. The simulation results confirmed that the Goodwin model is suitable for analyzing functional income distribution in Korea.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.145-154
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• 2004

Class extraction of object or component based software development methodology is the major factor for software quality. Each method has the class definition and extraction method however there are some troubles when the beginners try. Especially, the conceptual gap results to make the class extraction hard. This research suggests three diagrams to support it. They are Information diagram, Behavio diagram and Management diagram. They specify which services a stakeholder wants, which information to support the service, which actions to solve the service and who has the responsibility for those. Any analysis process which takes class extraction can utilize these diagrams.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.59-77
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• 2004

Even though B2B EC is becoming popular, there have been not so much studies about performance evaluation methodology for B2B systems. In this paper, after analyzing buyer-carts systematically focusing on the buyer's interactional efforts on the typical buying processes of each buyer-cart, we propose a quantitative performance evaluation model. For this, we categorize buyer-carts in B2B EC as s-cart, i-cart, and b-cart depending upon its residing sites: seller, intermediary, and buyer sites. And after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we derive a performance evaluation model by calculating detail sub-processes from the desired features' viewpoints. By setting variables from a survey on the actual condition of using buyer-carts in companies in Korea, we try to evaluate the performance of buyer-carts in B2B EC. In this paper, we suggest a new methodology of performance evaluation for B2B systems, and show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.195-214
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• 2013

Case-based reasoning is a methodology for solving problems more quickly and efficiently by bringing the most similar case of a given problem from past cases and transforming it to fit the current situation. The most important performance indicator of case-based reasoning is the number of cases, so it is difficult to apply the methodology for the area which has not enough cases. In this paper, we proposed a method to exchange cases based on the Semantic Web in order to overcome the problems. Inparticular, we separated cases into sub-cases to make it possible creating new cases by combining the appropriate sub-cases even if there was no proper full case. In order to achieve that, we designed an ontology that connects a case and its sub-cases, represents detailed similarity rules that compare sub-cases, and represents the rules for the combination of sub-cases. Moreover, we designed and implemented a semantic distributed case-based reasoning framework where a case requester can request sub-cases via the Web from case providers and integrates sub-cases into a new case by using the ontology.