• Journal of Intelligence and Information Systems
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• 제22권1호
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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.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• 제7권3호
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• pp.181-194
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• 2002

Parasitism is a one-sided relationship between two organisms in which one benefits at the expense of the other. Parasitic dinoflagellates, particularly species of Amoebophrya, have long been thought to be a potential biological agent for controlling harmful algal bloom(HAB). Amoebophrya infections have been reported for over 40 species representing more than 24 dinoflagellate genera including a few toxic species. Parasitic dinoflagellates Amoebophrya spp. have a relatively simple life cycle consisting of an infective dispersal stage (dinospore), an intracellular growth stage(trophont), and an extracellular reproductive stage(vermiform). Biology of dinospores such as infectivity, survival, and ability to successfully infect host cells differs among dinoflagellate host-parasite systems. There are growing reports that Amoebophrya spp.(previously, collectively known as Amoebophrya ceratii) exhibit the strong host specificity and would be a species complex composed of several host-specific taxa, based on the marked differences in host-parasite biology, cross infection, and molecular genetic data. Dinoflagellates become reproductively incompetent and are eventually killed by the parasite once infected. During the infection cycle of the parasite, the infected host exhibits ecophysiologically different patterns from those of uninfected host in various ways. Photosynthetic performance in autotrophic dinoflagellates can be significantly altered following infection by parasitic dinoflagellate Amoebophrya, with the magnitude of the effects over the infection cycle of the parasite depending on the site of infection. Parasitism by the parasitic dinoflagellate Amoebophrya could have significant impacts on host behavior such as diel vertical migration. Parasitic dinoflagellates may not only stimulate rapid cycling of dissolved organic materials and/or trace metals but also would repackage the relatively large sized host biomass into a number of smaller dinospores, thereby leading to better retention of host's material and energy within the microbial loop. To better understand the roles of parasites in plankton ecology and harmful algal dynamics, further research on a variety of dinoflagellate host-parasite systems is needed.

• Korean Journal of Agricultural and Forest Meteorology
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• 제13권4호
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• pp.176-184
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• 2011

Cold air on sloping surfaces flows down to the valley bottom in mountainous terrain at calm and clear nights. Based on the assumption that the cold air flow may be the same as the water flow, current models estimate temperature drop by regarding the cold air accumulation at a given location as the water-like free drainage. At a closed catchment whose outlet is blocked by man-made obstacles such as banks and roads, however, the water-like free drainage assumption is no longer valid because the cold air accumulates from the bottom first. We developed an empirical model to estimate quantitatively the effect of cold pool on nocturnal temperature in a closed catchment. In our model, a closed catchment is treated like a "vessel", and a digital elevation model (DEM) was used to calculate the maximum capacity of the cold pool formed in a closed catchment. We introduce a topographical variable named "shape factor", which is the ratio of the cold air accumulation potential across the whole catchment area to the maximum capacity of the cold pool to describe the relative size of temperature drop at a wider range of catchment shapes. The shape factor is then used to simulate the density profile of cold pool formed in a given catchment based on a hypsometric equation. The cold lake module was incorporated with the existing model (i.e., Chung et al., 2006), generating a new model and predicting distribution of minimum temperature over closed catchments. We applied this model to Akyang valley (i.e., a typical closed catchment of 53 $km^2$ area) in the southern skirt of Mt. Jiri National Park where 12 automated weather stations (AWS) are operational. The performance of the model was evaluated based on the feasibility of delineating the temperature pattern accurately at cold pool forming at night. Overall, the model's ability of simulating the spatial pattern of lower temperature were improved especially at the valley bottom, showing a similar pattern of the estimated temperature with that of thermal images obtained across the valley at dawn (0520 to 0600 local standard time) of 17 May 2011. Error in temperature estimation, calculated with the root mean square error using the 10 low-lying AWSs, was substantially decreased from $1.30^{\circ}C$ with the existing model to $0.71^{\circ}C$ with the new model. These results suggest the feasibility of the new method in predicting the site-specific freeze and frost warning at a closed catchment.

• Journal of Korean Society of Forest Science
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• 제110권4호
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• pp.630-647
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• 2021

We determined the current problem of the restoration deposit-estimation system, stipulated by the Mountainous Districts Management Act, using the Delphi technique. Consequently, we proposed a standard model for forest land restoration to derive a reasonable deposit-estimation system. With the result of the Delphi survey, the inappropriateness of land-use type and slope gradient classifications was shown; the insufficiency of standard works was a significant problem in the current system. A way to solve these problems was devised, to reorganize the current land-use type into the subject of the site. The specific subjects included the following: (i) to permit or report forest land-use change and temporary use of forest land, (ii) to report temporary use of forest land, (iii) to permit stone collection or sale for mineral mining, and (iv) to allow sediment collection. The current slope gradient subdivision into (a) θ<10°, (b) 10°≦θ<15°, (c) 15°≦θ<20°, (d) 20°≦θ<25°, (e) 25°≦θ<30°, and (f) θ≧30° and the reorganization of 17 standard works into 22 standard works were deemed as solutions, along with seven additional works. We developed 24 standard models for the forest land restoration project based on the aforementioned results. The deposits estimated by these models ranged from 34,185,000 (Korean) won to 607,403,000 won. If additional works, premiums, discounts, and supervision fees are added to the models, the deposit increases to an estimated 668,143,000 won subject to permission for stone collection or sale and mineral mining. Experts agree on the distribution of the restoration deposits estimated by these models at a high level in the Delphi survey. Our findings are expected to contribute to securing the appropriateness of the restoration cost deposited for the smooth performance of the vicariously executed restoration project.

• Korean Journal of Environment and Ecology
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• 제38권4호
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• pp.388-404
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• 2024

The focus of conserving plant diversity at the national level includes endemic species restricted to specific regions. This study thus aimed to investigate and evaluate the current distribution status of the Pulsatilla tongkangensis Y.N. Lee & T.C. Lee, one of Korea's endemic plants. The study also examined the vegetation environment of its habitat and assessed the structure of each population. Furthermore, the performance variable of each population was comparatively evaluated, and its annual growth characteristics were also observed. The distribution area of the P. tongkangensis is largely divided into limestone cliffs, ridge rocks, mountain peaks in limestone regions, and sandy soil areas resulting from weathering. Plants in the same distribution area were categorized based on their geographical location, which reflected their respective habitats. According to the population structure evaluated using the number of measured leaves numbers, the plants were categorized into stable and relatively unstable populations. A relatively young population was observed at the top of mountains and rocky ridges of limestone areas and sandy soil areas resulting from weathering. The number of mature individuals was the highest in the population observed around limestone cliffs. In contrast, the population near the top of the limestone mountain range had more leaves , but the plants were of short stature and had the fewest inflorescences. The individuals distributed in limestone cliffs grew, produced, and dispersed seeds for an extended period following establishment. The growth of individuals was limited due to environmental factors in the habitat of distribution areas, including ridges, mountain tops in limestone regions, and sandy soil areas resulting from weathering. It was assessed to have a comparatively brief life cycle compared to that of the plants found on limestone cliffs. P. tongkangensis began flowering in early spring, and both fruit maturation and seed dispersal were completed before the onset of summer. The habitats were determined to receive around seven hours of sunlight per day during the summer, which was considered suitable for establishing a life cycle for the P. tongkangensis, a species requiring strong sunlight for growth to establish and success in a dry environment. Considering the status data gathered from this study, the P. tongkangensis was classified as an endangered species (EN). In addition, the collected data are expected to provide important information for the IUCN Red List of Threatened Species. Therefore, we proposed that the P. tongkangensis holds significant value as a core distribution site, given the observation of species with diverse characteristics on limestone cliffs in Pyeongchang-gun and Jeongseon-gun, Gangwon-do.

• Journal of Intelligence and Information Systems
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• 제25권1호
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.