• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.600-619
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• 2006

According to recent technical advances on sensors and mobile devices, processing of data streams generated by the devices is becoming an important research issue. The data stream of real values obtained at continuous time points is called streaming time-series. Due to the unique features of streaming time-series that are different from those of traditional time-series, similarity matching problem on the streaming time-series should be solved in a new way. In this paper, we propose an efficient algorithm for streaming time- series matching problem that supports normalization transform. While the existing algorithms compare streaming time-series without any transform, the algorithm proposed in the paper compares them after they are normalization-transformed. The normalization transform is useful for finding time-series that have similar fluctuation trends even though they consist of distant element values. The major contributions of this paper are as follows. (1) By using a theorem presented in the context of subsequence matching that supports normalization transform[4], we propose a simple algorithm for solving the problem. (2) For improving search performance, we extend the simple algorithm to use $k\;({\geq}\;1)$ indexes. (3) For a given k, for achieving optimal search performance of the extended algorithm, we present an approximation method for choosing k window sizes to construct k indexes. (4) Based on the notion of continuity[8] on streaming time-series, we further extend our algorithm so that it can simultaneously obtain the search results for $m\;({\geq}\;1)$ time points from present $t_0$ to a time point $(t_0+m-1)$ in the near future by retrieving the index only once. (5) Through a series of experiments, we compare search performances of the algorithms proposed in this paper, and show their performance trends according to k and m values. To the best of our knowledge, since there has been no algorithm that solves the same problem presented in this paper, we compare search performances of our algorithms with the sequential scan algorithm. The experiment result showed that our algorithms outperformed the sequential scan algorithm by up to 13.2 times. The performances of our algorithms should be more improved, as k is increased.

• Journal of Life Science
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• v.23 no.11
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• pp.1317-1324
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• 2013

High-molecular weight glutenin subunits (HMW-GS) have been shown to play a crucial role in determining the processing properties of the wheat grain. We have produced marker-free transgenic rice plants containing a wheat Glu-1Bx7 gene encoding the HMG-GS from the Korean wheat cultivar 'Jokyeong' using the Agrobacterium-mediated co-transformation method. The Glu-1Bx7-own promoter was inserted into a binary vector for seed-specific expression of the Glu-1Bx7 gene. Two expression cassettes comprised of separate DNA fragments containing only Glu-1Bx7 and hygromycin phosphotransferase II (HPTII) resistance genes were introduced separately to the Agrobacterium tumefaciens EHA105 strain for co-infection. Each EHA105 strain harboring Glu-1Bx7 or HPTII was infected to rice calli at a 3:1 ratio of Glu-1Bx7 and HPTII, respectively. Then, among 216 hygromycin-resistant $T_0$ plants, we obtained 24 transgenic lines with both Glu-1Bx7 and HPTII genes inserted into the rice genome. We reconfirmed integration of the Glu-1Bx7 gene into the rice genome by Southern blot analysis. Transcripts and proteins of the wheat Glu-1Bx7 were stably expressed in the rice $T_1$ seeds. Finally, the marker-free plants harboring only the Glu-1Bx7 gene were successfully screened at the $T_1$ generation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.

• The Korean Journal of Food And Nutrition
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• v.16 no.1
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• pp.46-53
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• 2003

Panax ginseng leaf tea was developed for the functional benefit of health, preference and convenience. The leaves of 4-year-old ginseng were selected in July and August. The ginseng leaf was treated by three methods : heat processed tea(HPT), aged tea(AGT) and hot-air dried tea(DRT). The contents and compositions of their crude saponin of ginseng leaves were measured. 1. The content of crude saponin of HPT was the higher than other treatments. The content of HPT was 18.72∼18.82％, ACT 18.24∼18.29％ and DRT 17.02∼17.17％. 2. The harvest time and treatment methods were not affect the composition of ginsenoside in ginseng leaf tea. The ginsenoside-Re was shown the highest value as 1.97∼2.15. And ginsenoside-Rd was 1.48∼1.79, -Rg$_1$ 1.33∼1.58 and -Rb, -Rb$_2$, -Rc in the order. 3. The content of protopanaxadiol(PD) and protopanaxatriol(PT) was shown that DRT was 1.11∼1.13, HPT 1.09～l.12 and AGT 0.92∼1.02. The content of PD and PT were shown similar result at any harvest time. 4. The contents of crude saponin extracted by hot-water at 5 min was the higher ratios in HPT and harvested in July than other treatments. The content of crude saponin of ginseng leaf harvested in July was 15.88% and HPT was 16.88%. The order of contents of ginsenoside were -Re, -Rd, -Rg$_1$, -Rb$_1$, -Rb$_2$, and - Rc. The extraction ratio of crude saponin extracted by the circulated extraction method in 8 hours and 5 min extraction were 81.74∼84.38％. And HPT of ginseng leaf harvested in July was the highest value 84.3％ but the extraction ratio of ginsenoside was 78.00～88.13%. But the extraction ratio of ginsenoside was similar trend in all treatments.

• Korean journal of food and cookery science
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• v.30 no.6
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• pp.663-669
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• 2014

We preprocessed and pickled Deodeok with Doenjang to improve its preservability and to distribute it widely, and we stored Deodeok for 3 weeks at $7^{\circ}C$ and measured its quality. The sample pre-treated with 20% of dextrin retained its early texture better than the samples pre-treated with other methods after 3 weeks of storage (p<0.05). The samples pre-treated with other controls showed propagation of microorganisms; but Doenjang pre-treated with 20% of dextrin or sugar showed less increase in the water content. The microorganisms count in samples pre-treated with other controls was 4.0 log CFU/g after 3 weeks of storage, but the microorganisms count in the sample pre-treated with 20% of dextrin was 2.2 log CFU/g; in other words, the propagation of microorganisms was minimized in the sample pre-treated with 20% of dextrin (p<0.05). In the investigation of the preferences, this D-20 sample showed maximum improvement in color, smell, taste, and other general preferences factors. Thus, the best processing method for the optimal quality maintenance of Deodeok is to sugarize it with 20% of dextrin before pickling with Doenjang. The product prepared using with this process can be preserved for 3 weeks at $37^{\circ}C$; that is, this product is expected to have a refrigerator shelf life of 3 months.

• Food Science of Animal Resources
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• v.29 no.6
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• pp.709-718
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• 2009

The purpose of this study was to search for physical treatments to reduce allergenicity of pork. Physical treatments such as heating, autoclave, microwave, sonication, and irradiation have been used for food processing or reduction of allergenicity. The porcine serum albumin (PSA), known as a major allergen in pork, was extracted after physical treatments. The antigenicity of pork extracts by heating (80 and $100^{\circ}C$ for 20 min), autoclave ($121^{\circ}C$ for 5, 10, and 30 min), and microwave (for 5 and 10 min) was significantly decreased. Especially, the binding ability of p-IgG to pork extracts by autoclave for 30 min showed the greatest decrease (about 3%) in physical treatments. However, the antigenicity of pork was unaffected by sonication and irradiation treatment. These results indicated that the autoclave treatment was the most effective method to reduce the antigenicity of pork.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.223-234
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• 2008

Recently the web service area provides the efficient integrated environment of the internal and external of corporation and enterprise that wants the introduction of it is increasing. Also the web service develops and the new business model appears, the domestic enterprise environment and e-business environment are changing caused by web service. The web service which provides the similar function increases, most the method which searches the suitable service in demand of the user is more considered seriously. When it needs to choose one among the similar web services, service consumer generally needs quality information of web service. The problem, however, is that the advertised QoS information of a web service is not always trustworthy. A service provider may publish inaccurate QoS information to attract more customers, or the published QoS information may be out of date. Allowing current customers to rate the QoS they receive from a web service, and making these ratings public, can provide new customers with valuable information on how to rank services. This paper suggests the agent-based quality broker architecture which helps to find a service providing the optimum quality that the consumer needs in a position of service consumer. It is able to solve problem which modify quality requirements of the consumer from providing the architecture it selects a web service to consumer dynamically. Namely, the consumer is able to search the service which provides the optimal quality criteria through UDDI browser which is connected in quality broker server. To quality criteria value decision of each service the user intervention is excluded the maximum. In the existing selection architecture, the objective evaluation was difficult in subjective class of service selecting of the consumer. But the proposal architecture is able to secure an objectivity with the quality criteria value decision where the agent monitors binding information in consumer location. Namely, it solves QoS information of service which provider does not provide with QoS information sharing which is caused by with feedback of consumer side agents.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.239-250
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• 2020

The purpose of this paper is to explore the influence of the "contextualization" effect of web celebrity live broadcast on the e-commerce platform on consumers' perception of product value, risk and purchase intention. Live in this paper, using Taobao shopping consumers as the research object, the survey method, questionnaire survey is adopted, the form through the questionnaire and distributed network, a live in order to further validation of web celebrity effect of contextualized actual influence on consumer purchase intention, questionnaire design the Likert scale, seven and recycling questionnaire analysis using the statistical software SPSS 23.0 and AMOS 22.0 after processing the data. After determining the reliability and validity of the questionnaire, the exploratory factor analysis was used to verify the hypothesis and calculate the actual adjustment degree of the "contextualization" effect of web celebrity live broadcasting on consumers' purchase intention. The research results of this paper are summarized as follows :(1) consumers' perceived value of products can significantly positively affect their purchase intention, while perceived risk has a significantly negative impact on their purchase intention; (2) consumers' trust and purchase intention to products are regulated by the "contextualization" of web celebrity live broadcast. Specifically, for web celebrity live broadcasting with good "contextualization" effect, the perceived value of consumer products has a positive impact on product trust, which is higher than that of web celebrity live broadcasting with poor "contextualization" effect. In terms of resolving consumers' perceived risks to products, web celebrity live broadcast with good "contextualization" effect is also significantly better than web celebrity live broadcast with poor "contextualization" effect. Based on empirical analysis, this paper concludes that web celebrity live broadcasting will become a new breakthrough for the sustainable growth of the e-commerce industry, and puts forward Suggestions on the e-commerce marketing mode and the transformation of web celebrity live broadcasting industry.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.