• Journal of Distribution Science
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• v.8 no.3
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• pp.49-56
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• 2010

At the initial stage of Internet advertising, banner advertising came into fashion. As the Internet developed into a central part of daily lives and the competition in the on-line advertising market was getting fierce, there was not enough space for banner advertising, which rushed to portal sites only. All these factors was responsible for an upsurge in advertising prices. Consequently, the high-cost and low-efficiency problems with banner advertising were raised, which led to an emergence of keyword advertising as a new type of Internet advertising to replace its predecessor. In the beginning of 2000s, when Internet advertising came to be activated, display advertisement including banner advertising dominated the Net. However, display advertising showed signs of gradual decline, and registered minus growth in the year 2009, whereas keyword advertising showed rapid growth and started to outdo display advertising as of the year 2005. Keyword advertising refers to the advertising technique that exposes relevant advertisements on the top of research sites when one searches for a keyword. Instead of exposing advertisements to unspecified individuals like banner advertising, keyword advertising, or targeted advertising technique, shows advertisements only when customers search for a desired keyword so that only highly prospective customers are given a chance to see them. In this context, it is also referred to as search advertising. It is regarded as more aggressive advertising with a high hit rate than previous advertising in that, instead of the seller discovering customers and running an advertisement for them like TV, radios or banner advertising, it exposes advertisements to visiting customers. Keyword advertising makes it possible for a company to seek publicity on line simply by making use of a single word and to achieve a maximum of efficiency at a minimum cost. The strong point of keyword advertising is that customers are allowed to directly contact the products in question through its more efficient advertising when compared to the advertisements of mass media such as TV and radio, etc. The weak point of keyword advertising is that a company should have its advertisement registered on each and every portal site and finds it hard to exercise substantial supervision over its advertisement, there being a possibility of its advertising expenses exceeding its profits. Keyword advertising severs as the most appropriate methods of advertising for the sales and publicity of small and medium enterprises which are in need of a maximum of advertising effect at a low advertising cost. At present, keyword advertising is divided into CPC advertising and CPM advertising. The former is known as the most efficient technique, which is also referred to as advertising based on the meter rate system; A company is supposed to pay for the number of clicks on a searched keyword which users have searched. This is representatively adopted by Overture, Google's Adwords, Naver's Clickchoice, and Daum's Clicks, etc. CPM advertising is dependent upon the flat rate payment system, making a company pay for its advertisement on the basis of the number of exposure, not on the basis of the number of clicks. This method fixes a price for advertisement on the basis of 1,000-time exposure, and is mainly adopted by Naver's Timechoice, Daum's Speciallink, and Nate's Speedup, etc, At present, the CPC method is most frequently adopted. The weak point of the CPC method is that advertising cost can rise through constant clicks from the same IP. If a company makes good use of strategies for maximizing the strong points of keyword advertising and complementing its weak points, it is highly likely to turn its visitors into prospective customers. Accordingly, an advertiser should make an analysis of customers' behavior and approach them in a variety of ways, trying hard to find out what they want. With this in mind, her or she has to put multiple keywords into use when running for ads. When he or she first runs an ad, he or she should first give priority to which keyword to select. The advertiser should consider how many individuals using a search engine will click the keyword in question and how much money he or she has to pay for the advertisement. As the popular keywords that the users of search engines are frequently using are expensive in terms of a unit cost per click, the advertisers without much money for advertising at the initial phrase should pay attention to detailed keywords suitable to their budget. Detailed keywords are also referred to as peripheral keywords or extension keywords, which can be called a combination of major keywords. Most keywords are in the form of texts. The biggest strong point of text-based advertising is that it looks like search results, causing little antipathy to it. But it fails to attract much attention because of the fact that most keyword advertising is in the form of texts. Image-embedded advertising is easy to notice due to images, but it is exposed on the lower part of a web page and regarded as an advertisement, which leads to a low click through rate. However, its strong point is that its prices are lower than those of text-based advertising. If a company owns a logo or a product that is easy enough for people to recognize, the company is well advised to make good use of image-embedded advertising so as to attract Internet users' attention. Advertisers should make an analysis of their logos and examine customers' responses based on the events of sites in question and the composition of products as a vehicle for monitoring their behavior in detail. Besides, keyword advertising allows them to analyze the advertising effects of exposed keywords through the analysis of logos. The logo analysis refers to a close analysis of the current situation of a site by making an analysis of information about visitors on the basis of the analysis of the number of visitors and page view, and that of cookie values. It is in the log files generated through each Web server that a user's IP, used pages, the time when he or she uses it, and cookie values are stored. The log files contain a huge amount of data. As it is almost impossible to make a direct analysis of these log files, one is supposed to make an analysis of them by using solutions for a log analysis. The generic information that can be extracted from tools for each logo analysis includes the number of viewing the total pages, the number of average page view per day, the number of basic page view, the number of page view per visit, the total number of hits, the number of average hits per day, the number of hits per visit, the number of visits, the number of average visits per day, the net number of visitors, average visitors per day, one-time visitors, visitors who have come more than twice, and average using hours, etc. These sites are deemed to be useful for utilizing data for the analysis of the situation and current status of rival companies as well as benchmarking. As keyword advertising exposes advertisements exclusively on search-result pages, competition among advertisers attempting to preoccupy popular keywords is very fierce. Some portal sites keep on giving priority to the existing advertisers, whereas others provide chances to purchase keywords in question to all the advertisers after the advertising contract is over. If an advertiser tries to rely on keywords sensitive to seasons and timeliness in case of sites providing priority to the established advertisers, he or she may as well make a purchase of a vacant place for advertising lest he or she should miss appropriate timing for advertising. However, Naver doesn't provide priority to the existing advertisers as far as all the keyword advertisements are concerned. In this case, one can preoccupy keywords if he or she enters into a contract after confirming the contract period for advertising. This study is designed to take a look at marketing for keyword advertising and to present effective strategies for keyword advertising marketing. At present, the Korean CPC advertising market is virtually monopolized by Overture. Its strong points are that Overture is based on the CPC charging model and that advertisements are registered on the top of the most representative portal sites in Korea. These advantages serve as the most appropriate medium for small and medium enterprises to use. However, the CPC method of Overture has its weak points, too. That is, the CPC method is not the only perfect advertising model among the search advertisements in the on-line market. So it is absolutely necessary that small and medium enterprises including independent shopping malls should complement the weaknesses of the CPC method and make good use of strategies for maximizing its strengths so as to increase their sales and to create a point of contact with customers.

• Journal of Music and Human Behavior
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• v.5 no.1
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• pp.67-90
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• 2008

This case used MI techniques that give an imagery experience to depressed client's mental resource, and that makes in to verbalism. Also those images are supportive level therapy examples that apply to positive variation. MI is simple word of 'Music and Imagery' with one of psychology cure called GIM(Guided Imagery and Music). It makes client can through to the inner world and search, confront, discern and solve with suitable music. Supportive Level MI is only used from safety level music. Introduction of private session can associate specification feeling, subject, word or image. And those images are guide to positive experience. The First session step of MI program is a prelude that makes concrete goal like first interview. The Second step is a transition that can concretely express about client's story. The third step is induction and music listening. And it helps to associate imagery more easily by used tension relaxation. Also it can search and associate about various imagery from the music. The last step is process that process drawing imagery, talking about personal imagery experience in common with therapist that bring the power by expansion the positive experience. Client A case targets rapport forming(empathy, understanding and support), searching positive recourse(child hood, family), client's emotion and positive support. Music must be used simple tone, repetition melody, steady rhythm and organized by harmony music of what therapist and client's preference. The client used defense mechanism and couldn't control emotion by depression in 1 & 2 sessions. But the result was client A could experience about support and understanding after 3 sessions. After session 4 the client had stable, changed to positive emotion from the negative emotion and found her spontaneous. Therefore, at the session 6, the client recognized that she will have step of positive time at the future. About client B, she established rapport forming(empathy, understanding and support) and searching issues and positive recognition(child hood, family), expression and insight(present, future). The music was comfortable, organizational at the session 1 & 2, but after session 3, its development was getting bigger and the main melody changed variation with high and low of tune. Also it used the classic and romantic music. The client avoids bad personal relations to religious relationship. But at the session 1 & 2, client had supportive experience and empathy because of her favorite, supportive music. After session 3, client B recognized and face to face the present issue. But she had avoidance and face to face of ambivalence. The client B had a experience about emotion change according depression and face to face client's issues After session 4. At the session 5 & 6, client tried to have will power of healthy life and fairly attitude, train mental power and solution attitude in the future. On this wise, MI program had actuality and clients' issues solution more than GIM program. MI can solute the issue by client's based issue without approach to unconsciousness like GIM. Especially it can use variety music and listening time is shorter than GIM and structuralize. Also can express client's emotion very well. So it can use corrective and complement MI program to children, adolescent and adult.

• 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.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.455-463
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• 2010

In this paper, we present an approach to sentence boundary detection for web documents that builds on statistical-based methods and uses rule-based correction. The proposed system uses the classification model learned offline using a training set of human-labeled web documents. The web documents have many word-spacing errors and frequently no punctuation mark that indicates the end of sentence boundary. As sentence boundary candidates, the proposed method considers every Ending Eomis as well as punctuation marks. We optimize engine performance by selecting the best feature, the best training data, and the best classification algorithm. For evaluation, we made two test sets; Set1 consisting of articles and blog documents and Set2 of web community documents. We use F-measure to compare results on a large variety of tasks, Detecting only periods as sentence boundary, our basis engine showed 96.5% in Set1 and 56.7% in Set2. We improved our basis engine by adapting features and the boundary search algorithm. For the final evaluation, we compared our adaptation engine with our basis engine in Set2. As a result, the adaptation engine obtained improvements over the basis engine by 39.6%. We proved the effectiveness of the proposed method in sentence boundary detection.

• English Language & Literature Teaching
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• no.5
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• pp.49-62
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• 1999

Education systems throughout the world encourage their students to learn languages other than their native one. In Australia, our Education Boards provide students with the opportunity to learn European and Asian languages. French, German, Chinese and Japanese are the most popular languages studied in elementary and high schools. This choice is a reflection of Australias European heritage and its geographical position near Asia. In most non-English speaking countries, English is the foreign language most readily available to students. In Korea, the English language is actively promoted by the Education Department and, in less official ways, by companies and the public. It is impossible to be anywhere in Korea without seeing the English language alongside or intermingled with Korean. When I ask students why they are learning English, I receive answers that include the word globalization and the importance of English throughout the world. When I press further and ask why they personally are learning English, the students mention passing exams, usually high school tests or TOEIC, and the necessity of passing the latter to obtain a good job. Seldom do I ever hear anything about communication: about the desire to talk with other people in English, to read novels or poetry in English, to understand movies or pop-songs in English, to chat on the Internet in English, to search for information on the Internet in English, or to email pen-pals in English. Yet isnt communication the only valid reason for learning a language? We learn our native language to communicate with those around us. Shouldnt we set the same goal for learning a foreign language? In my opinion communication, whether it is reading and writing or speaking and listening, must be central to language learning. Learning a language to pass examinations is meaningless unless those examinations are a reliable indicator of the ability of the student to communicate. In previous eras, most communication in a foreign language was through reading novels or formal letters. This required a thorough knowledge of grammar and a large vocabulary. Todays communication is much less formal. Telephone conversations, tele-conferences, faxes and emails allow people to communicate regularly and informally. Reading materials are also less formal as popular novels and newspapers are available world-wide. Movies and popular songs have added to the range of informal communication available. Finally travel has ensured that people from different cultures will meet easily and regularly. This informal communication requires less emphasis on grammar and vocabulary and more emphasis on comprehension and confidence to speak. Placing communication central to language learning has important implications for the Education system and for teachers.

• Korean journal of communication and information
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• v.66
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• pp.59-86
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• 2014

This study explored how rumor is diffused via Twitter and how the characteristics of rumor affect the interactivity among users in the Korea-U.S. FTA case. A key word search located three issues as major ones related to the Korea-U.S. FTA: appendectomy myth, collapse of health insurance, and increases in medicine prices. The arousal of rumor has two dimensions: fact and expression. The fact arousal was the highest in the issue of 'appendectomy myth', and the expression arousal the highest in 'increases in medicine prices'. The rumor diffusion took the 'explosive wave' in the issue of appendectomy myth, the 'latent wave' in the issue of increase in medicine prices, and the 'repetitive wave' in the issue of collapse of health insurance. Correlation analyses revealed a high correlation between the arousal intensity of rumor and the user interactivity in the issue of collapse of health insurance. The study showed that Twitter took a role of diffusing negative messages about the Korea-U.S. FTA. Results implies that government officials and journalists pay attention to Twitter for sensing the public opinion when building policies and managing crises.

• Journal of Distribution Science
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• v.13 no.12
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• pp.73-84
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• 2015

Purpose - Various social issues have arisen since the beginning of the 21st century therefore, enterprises that disregarded social issues have become unsustainable, and social enterprises have appeared to address these issues. A social enterprise is a social mission-focused organization that uses a market-based strategy and has a vulnerable business structure. To be self-sustainable, a social enterprise should make consumers aware of the value that it provides and secure its profitability through consumer consumption. From this perspective, this study investigates the relationship between perceived value (utilitarian and hedonic) and loyalty, and examines how memory and attitudes play mediating roles between perceived value and loyalty. For these purposes, the author developed a structural model consisting of several variables. In this model, perceived value, which was utilitarian and hedonic, was proposed to affect the memory and attitudes toward social enterprise products, thus increasing loyalty. Therefore, memory and attitudes were proposed as core mediating variables between perceived value and loyalty. Research design, data, and methodology - To analyze the proposed model, data were collected from 582 respondents and analyzed using SPSS 21.0 and AMOS 21.0. To test unidimensionality and the nomological validity of the measures of each construct, we employed a scale refinement procedure. The results of the reliability test with Cronbach's α and confirmatory factor analysis warranted the unidimensionality of the measures for each construct. In addition, the nomological validity of the measures was warranted from the results of the correlation analysis. The result of the overall model analysis demonstrated a good fit (χ²=529.881, df=144, χ²/df=3.680, p-value=0.000, GFI=0.905, NFI=0.948, CFI=0.961, RMR=0.036, RMSEA=0.068). Results - The findings are summarized as follows. First, the hedonic and utilitarian value of social enterprise products had positive effects on memory and attitudes. Second, the hedonic value of social enterprise products more strongly affects memory and attitudes than utilitarian value. Third, memory and attitudes had positive effects on loyalty. Lastly, memory had a stronger effect on loyalty than attitudes. Conclusions - The purchase rate of social enterprises' products increases only if the products are included in the "information search" and "alternative evaluation" processes in consumers' purchase decision-making processes. Therefore, a social enterprise must actively promote the fact that it pursues a social value, and shares both the hedonic and utilitarian values of its products. Accordingly, because hedonic value has a more significant impact on a company and attitudes, a social enterprise should develop hedonic values for product consumption, thereby leading consumers who care about value consumption to purchase its products. Moreover, a social enterprise must maintain good memories and attitudes for consumers because memory does not change over time, although attitude does. The limitations of this study and suggestions for future research are as follows. This study viewed "consumer loyalty" as the success factor of social enterprises, thereby considers an "increase in sales" as the success factor. Therefore, in future studies, diverse factors, including social contribution and word-of-mouth intention, should be regarded. In addition, future studies need to thoroughly review and make assurances about the relationship between memory and attitude.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.173-183
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• 2003

Morphological analysis is the most widely used method for extracting nouns from Korean texts. For every Eojeol, in order to extract nouns from it, a morphological analyzer performs frequent dictionary lookup and applies many morphonological rules, therefore it requires many operations. Moreover, a morphological analyzer generates all the possible morphological interpretations (sequences of morphemes) of a given Eojeol, which may by unnecessary from the noun extraction`s point of view. To reduce unnecessary computation of morphological analysis from the noun extraction`s point of view, this paper proposes a method for Korean noun extraction considering noun occurrence characteristics. Noun patterns denote conditions on which nouns are included in an Eojeol or not, which are positive cues or negative cues, respectively. When using the exclusive information as the negative cues, it is possible to reduce the search space of morphological analysis by ignoring Eojeols not including nouns. Post-noun syllable sequences(PNSS) as the positive cues can simply extract nouns by checking the part of the Eojeol preceding the PNSS and can guess unknown nouns. In addition, morphonological information is used instead of many morphonological rules in order to recover the lexical form from its altered surface form. Experimental results show that the proposed method can speed up without losing accuracy compared with other systems based on morphological analysis.

• Journal of Korean Home Economics Education Association
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• v.14 no.2
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• pp.37-52
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• 2002

This study was made on the concerns and implementation of the ICT(Inormation and Communication Technology)-utilized lesson by home economics teacher. The objective of this study is to investigate the stages of concern and the level of use of the ICT-utilized lesson by home economics teachers in Kyunggi Province through the concerns based adoption model(CBAM) and to provide assistance for ICT-utilizing lesson to be efficiently adopted to home economics. This study made selected 200 schools by random sampling among 233 middle schools which have two or more home economic teachers and 21 or more classes in Kyunggi Province which has a total of 395 middle schools and mail-surveyed on 400 home economics teachers by means of questionnaire. The stages of concern. the levels of use and the types of implementation were used as instruments in this survey. The results of this study on the stages of concern. the levels of use and the type of implementation of the ICT-utilized lesson by home economics teachers in Kyunggi Province were as following: First. the highest point of the concern of home economics teachers of ICT-utilized lesson was the stage of awareness. the second highest point was the stage of management. the 3rd stage. and the stage of information. the lst stage. Second. the highest level of implementation of ICT-utilized lesson by home economics teachers was the level of mechanical use. the 3rd stage(30.4％), which followed by the level of orientation. the 1st stage(22.5％). and the level of nonuse(16.7％). the level of rountine use. the 4th stage(13.7％) the level of integration. the 5th stage(11.8％). the level of preparation 2(3.9％). and the level of renewal. the 6th stage(1.0％) Third, information search was the most in the type of ICT-use and in the course of lesson CD-ROM was used the most.. During ICT-utilized lesson. most of teachers used computer one to two hours a week mainly in the lessons of clothing life and eating life. Home economics teachers took the most training of how to use word-processor(68.6％) during computer education. and 60 teachers(66.0％) gave positive response about the effect of computer education on teacher's learning. Finally. the biggest problem with ICT-use in the teacher's learning was the long preparation time for lesson. and problem with ICT-utilized lesson was the burden of time and effort spent to buy needed materials and to recompose the existing materials for the lesson. Therefore. so as to adopt ICT-utilized lesson efficiently into school it is needed that active promotion for the lesson should be made to teachers. training teachers to raise their ability to use computer and various kinds of software should be expanded. and school authorities' financial and administrative assistance should be given for the smooth proceeding of the lesson.