• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.51.1-51.1
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• 2015

OLED commercialization has been led in mobile market by Samsung since 2007, but more suppliers in Korea, China and Japan are joining the market. However, there remain some challenges in expanding its application to large size TV and flexible displays, especially in competition with dominant LCD products. This talk will discuss future prospects of the OLED technology after brief review of the progress.

• The Korean Journal of Food And Nutrition
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• v.14 no.4
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• pp.360-366
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• 2001

This brief review is organized to integrate methodology of carotenoids chemistry from the author's experimental conceps. The majors include classification of carotenoids. extraction·phase separation, purification. crystalyzation, identification, quantitation, spectroscopic properties, organic reactions, and analytical methods of carotenoproteins. The goal is not write a important conceps of carotenoid but to provide a technical methods that may be useful to researchers of natural products chemistry.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2001.09a
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• pp.21-50
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• 2001

EC's/Japanese environmental regulation drive the Pb-free/Halogen-free application. Most Japanese electronics companies are preparing the green products. All items concerning to Pb-free/Halogen-ree technology should be coparallely designed and developed. More works need to clear the unknowns on Pb-free materials. Need of consensus on materials and standards. EBM (Environmental Benign Manufacturing)

• KSBB Journal
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• v.17 no.2
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• pp.115-120
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• 2002

Biofiltration is a bioprocess treating volatile organic compounds (VOCs) in order to convert the VOCs to harmless products. This review on biofiltration is intended to provide an engineering concept such as removal efficiency, maximum load, elimination capacity and so on. Besides, modeling concept of biofilter is also supplied for designing biofilter system. Quantitative data generated in our research group is shown to explain the engineering concept as well as the modeling idea.

• Korean Management Science Review
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• v.6 no.2
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• pp.89-96
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• 1989

본 논문에서는 제품의 유효기간이 짧고, 그 수요분포가 정규분포 함수로 주어지는 다품목 생산롯트의 크기를 결정하는 문제가 다루어진다. 총 생산량의 제약하에 2기간 동안의 생산재고 비용을 최소화하는 조건으로부터 적정 기초 재고수준과 롯트 크기를 구하는 효율적 해법이 제시된다. 특수 형태의 하나로 단일품목의 경우에 대한 최적 조건식도 아울러 주어진다.

• KSBB Journal
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• v.15 no.5
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• pp.415-422
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• 2000

Enzymatic resolution is becoming increasingly important in the production of optically active pharmaceutical drugs and is now challenging the traditional synthetic methods for production of a variety of chiral intermediates and products. This article reviews the recent advances in chirotechnology using enzymes as a catalyst to resolve chiral compounds. The review focuses on the recent trends in chirotechnology and the application of enzymes to the production of industrially valuable pharmaceutical drugs.

• Knowledge Management Research
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• v.14 no.4
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• pp.87-98
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• 2013

Along with the recent development of Social Network Service (SNS), such as Facebook and Twitter, social commerce market is expanding rapidly. As much, understanding consumers' purchase intention in social commerce becomes important. This study attempted to investigate the factors of consumers' purchase intention, and the effects of these determinants(price discount, perceived risk and product review) on consumer's purchasing intension in social commerce networks. Also, the interaction effects between these factors on consumer's purchasing intension were studied. The results showed that the effect of perceived risk on consumer's purchase intention found to be significantly negative. The interaction effect between price discount and perceived risk, and the interaction effect between price discount and review were meaningful on consumers' purchase intention. It indicates that the important factor for consumers to purchase products in social commerce is not just price discount but perceived risk, and that review which consumers think is manipulated has negative effect on purchase intention.

• Environmental Engineering Research
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• v.25 no.1
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• pp.18-28
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• 2020

In this paper the authors provide comparative evaluation of current research that used liquefaction and pyrolysis method for bio-oil production from various types of biomass. This paper review the resources of biomass, composition of biomass, properties of bio-oil from various biomass and also the utilizations of bio-oil in industry. The primary objective of this review article is to gather all recent data about production of bio-oil by using liquefaction and pyrolysis method and their yield and properties from different types of biomass from previous research. Shortage of fossil fuels as well as environmental concern has encouraged governments to focus on renewable energy resources. Biomass is regarded as an alternative to replace fossil fuels. There are several thermo-chemical conversion processes used to transform biomass into useful products, however in this review article the focus has been made on liquefaction and pyrolysis method because the liquid obtained which is known as bio-oil is the main interest in this review article. Bio-oil contains hundreds of chemical compound mainly phenol groups which make it suitable to be used as a replacement for fossil fuels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5120-5142
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• 2018

Social media enables customers to share their views, opinions and experiences as product reviews. These product reviews facilitate customers in buying quality products. Due to the significance of online reviews, fake reviews, commonly known as spam reviews are generated to mislead the potential customers in decision-making. To cater this issue, review spam detection has become an active research area. Existing studies carried out for review spam detection have exploited feature engineering approach; however limited number of features are considered. This paper proposes a Feature-Centric Model for Review Spam Detection (FMRSD) to detect spam reviews. The proposed model examines a wide range of feature sets including ratings, sentiments, content, and users. The experimentation reveals that the proposed technique outperforms the baseline and provides better results.