• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Korean Management Science Review
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• v.18 no.1
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• pp.135-145
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• 2001

In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.11-21
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• 2021

In order to explore the job crafting experience of millennial safety workers, this study conducted a qualitative case research with five safety workers of S Energy from March 26 to September 27, 2021 . As a result of the analysis, task crafting showed 'matching one's strong suit with a given task', 'expanding work knowledge using social network service (SNS)', and 'making changes in job performance methods for preemptive safety management activities'. Also, Cognitive crafting showed 'recognition of social vocation as a safety job', 'recognition of a role to grow as a safety management expert', and 'cognitive changes from means of organizational adaptation to enjoyment and energy of life'. At the same time, in relation crafting, 'establishment of amicable relationships through SNS in non-face-to-face and rapid communicating situations', 'safety management made through with mutual cooperations between business people', and 'reborn as a mutual safety net in business relationships' appeared. These can be used as basic data to accumulate the theoretical basis for job crafting research of millennial safety workers and to improve their job satisfaction. A follow-up study was proposed for safety workers with occupations of various kinds.

• Korean Journal of Construction Engineering and Management
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• v.7 no.3 s.31
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• pp.45-55
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• 2006

This study aims need set of mind to construction manager built a theory logic conceive decision making system and principles designed to create the administrative procedures that a company needs to integrate management and environmental concerns into its daily business practices. Integrate considerations of risk reduction and wise resource management into daily business decision making environmental that includes performance and cost. Seek to make better Dynamic time solutions that promote competitiveness set of management mind provide business with tools and methodologies management participation, psychology, philosophy effects of resource flows. A last of understand use of the decision making element principal as a guideline for evaluating and ranking approaches. The result of this study are summarized as follows; (1) setting for approach decision making of manager police, (2) dynamic of time and management mind (3) a primary factor out environment to decision making (4) methodologies of set up system for management mind (5) expectation effect of management mind.

• Korean Chemical Engineering Research
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• v.55 no.4
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• pp.497-502
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• 2017

Estimation of accident cost is a sound and great safety indicator on determining accurate occupational safety and health prevention. Just like in Korea, Heinrich ratio analysis of (1:4) between direct and indirect costs has been become widely used in safety management because of its simplicity. In this study four major categories of uninsured (indirect) cost items and 18 sub-categories of uninsured (indirect) cost items were identified. To determine and validate the importance and necessity of the results of a literature review an expert or professional surveyed had been analyses using the SPSS 18.0, where in the participants whose expertize is in the field of compensation and safety. Based on the results of survey all participants all uninsured (indirect) cost items classified was important and necessary when accidents occurred. Despite recognition of expert on the classification of uninsured (indirect) cost items, it is quite difficult to make generalization for all kind of costs in occupational accident case due to different nature of business for each industry.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.56-67
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• 2019

The aim of this study is to develop Artificial Intelligence (AI) based business models of media firms. We define AI and discuss 'AI activity model'. The practices of the efficiency model are home equipment-based personalization and media content recommendation. The practices of the expert model are media content commissioning, content rights negotiation, copyright infringement, and promotion. The practices of the effectiveness model are photo & video auto-tagging and auto subtitling & simultaneous translation. The practices of the innovation model are content script creation and metadata management. The related use cases from 2012 to 2017 are introduced along the four activity models of AI. In conclusion, we propose for media companies to fully utilize the AI for transforming from traditional to successful digital media firms.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• The Journal of Information Systems
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• v.7 no.1
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• pp.37-53
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• 1998

본 논문은 인적자원관리에 필수적인 전문가시스템의 개념에 대해서 논의하고 있다. 전문가시스템을 인적자원관리분야에 적용하기 위해서는 전문가시스템의 개발과 관련된 일반 적인 고려사항들 뿐만 아니라, 인적자원관리와 관련된 고유한 특성들이 고려되어야 한다. 본 논문에서는 인적자원관리 전문가시스템의 장점과 구조를 제시하였으며, 전문가시스템 개 발을 위한 단계별 구체적 활동을 논의하였다. 아울러, 규칙을 이용한 인적자원관리의 지식 표현법 및 예제를 통해서 인적자원관리정보시스템의 하부 시스템으로서의 전문가시스템의 특성에 대해서도 논의하였다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.5
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• pp.97-103
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• 2017

In this paper, we propose a method to investigate the safety consciousness of a analyst incident response. This study conducted a statistical survey on 154 analysts who hired as expert in environment monitoring organizations in South Korea. The results of the analyses showed that respondents had good awareness on the equipment incident response and complied with laboratory safety regulations very well. Secondly, respondents were aware of the importance in the order of equipment incident response, an analytical laboratory incident response, and the cause of a chemical substance associated incident in an analytical laboratory in regarding the regulation compliance for creating a safe laboratory environment and the securement of laboratory safety. Therefore, (it was identified that) it would be necessary to create a safe environment and integrate a safety management system.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.