• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• The Korean Journal of Elementary Counseling
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• v.8 no.1
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• pp.33-50
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• 2009

The purpose of this study was to develop a PBL-based career education program and to examine its effectiveness on school children's career maturity. It's specifically meant to prepare a career education program to assist students to get an accurate grip on their aptitude, interest and personality and explore various sorts of occupations in the course of solving authentic and contextual career-related problems. After children's developmental characteristics and needs were analyzed, task analysis was implemented, and the objectives were defined. And then the core of the program, PBL problems were developed, and the validity of the problems were verified Evaluation plans and tools were prepared to assess children's problem-solving process and presentation, and an online learning space was designed. The program that consisted of 10-minute 21 sessions was provided to fifth-grade elementary schoolers for eight weeks. The findings of the study were as follows: The experimental group that participated in the PBL-based career education program showed a more significant improvement than the control group that didn't in career attitude and three career attitude subfactors involving planness, disposition and compromise. And the former made a more significant progress than the latter in career ability and its subfactors including vocational comprehension, self-understanding and decision-making skills as well. As a result of making a content analysis to make up for the survey, the students reported that they were able to get an objective understanding of themselves and acquire diverse and profound knowledge on work and the business world in the middle of solving the given PBL problems related to different areas in group and giving a presentation. In conclusion, a PBL based career education program developed by this researcher encouraged the students to have an objective self-understanding, to have a dynamic interactive discussion with their group members. Therefore the program had a positive impact on boosting the career attitude and career ability of the elementary schoolers. The findings suggested that in the field of elementary career education, autonomous learning attitude and subjecthood are the crucial factors to stimulate school children to explore and create their own future.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• 한국벤처창업학회:학술대회논문집
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• 2007.04a
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• pp.375-404
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• 2007

When we look into the market economy of our country recently, we learn that the mind of consumption after IMF crisis is very shrunk and the market is led into a serious slump of consumption. For an approach to survive the contraction of the market and the market competition, enterprises command a variety of sales promotion strategy, out of which presentation is a sales promotion strategy to give the same product. The price-discounted strategy through the provision of donation commodity may induce the temporarily-discounted commodity not to be sold to the consumers or make a damage of the images of the brand, or arouse the price war against other companies, or lower the sense of the quality of the commodity. Therefore, it is necessary for a company to meet the end users' demand and also maintain the evaluation of the quality on the consumers' products highly. Therefore, in this study, we have attempted to study and analyze the consumers' satisfaction level and reliability on the donation goods in order to suggest the orientation of the presentation promotion strategy in accordance with the changes of the sales market. In addition, we tried to understand how the recognition, consumers' satisfaction level and reliability on the presentation goods had on the repurchase. With such objectives in this study, we could make an analogy of the following significance and suggestion of study. Firstly, in order to survive a serious competition market, enterprises must execute the product presentation along with diverse events instead of commanding the sales promotion strategy through a simple product presentation. This strategy can be an alternative to lower the danger a person-to-person product presentation may bring about. That is to say, we shall not lower the quality and value of the products but enhance a new image to customers through a product donation occasion together with an event as a new marketing pioneering method. Secondly, during the period of the current economic depression, if a company provides the consumers with an opportunity free of charge through the present special event period and the practical events, it will affect the advertising effect of the goods, the introduction of the customers and customers' repurchase. For this purpose, the company has to heighten customers' preferences by selecting the items customers are liable to prefer and closely analyze the consumer's response and market for such an objective. Thirdly, with the internet age, as the market has a tendency to increase in the number of consumers who do shopping in the internet, the marketing strategy has to build up the strategy of the presentation product instead of a simple offline strategy. For example, a company shall have to draw attention or attraction from end users who intend to do shopping through the online by a product planning expo or a presentation product corner. Fourthly, the excessive sale promotion strategy of presentation products may bring about even a reverse effect on the value of the goods or consumers' attitude as seen above. Therefore, a company has to relay 'the value as to the price' to the consumers instead of the sales promotion strategy of donation products just for a temporary sales volume. Conclusively, even if we put the value with a reasonable price through the presentation product strategy in the past, we shall have construct the strategy by providing some plus factors in the price such as the provision of the upgraded products or services instead of just presentation, or the invitation of the events related to diverse events or culture arts from now on.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.43-72
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• 2009

Recently, user-created content (UCC) have emerged as popular medium of on-line participation among users. The Internet environment has been constantly evolving, attracting active participation and information sharing among common users. This tendency is a significant deviation from the earlier Internet use as an one-way information channel through which users passively received information or contents from contents providers. Thanks to UCCs online users can now more freely generate and exchange contents; therefore, identifying the critical factors that affect content-generating activities has increasingly become an important issue. This paper proposes a set of critical factors for stimulating contents generation and sharing activities by Internet users. These factors were derived from the theories of folklores such as tales and songs. Based on some shared traits of folklores and UCC content, we found four critical elements which should be heeded in constructing UCC contents, which are: context of culture, context of situation, skill of generator, and response of audience. In addition, we selected three major UCC websites: a specialized contents portal, a general internet portal, and an official contents service site, They have different use environments, user interfaces, and service policies, To identify critical factors for generating, sharing and transferring UCC, we traced user activities, interactions and flows of content in the three UCC websites. Moreover, we conducted extensive interviews with users and operators as well as policy makers in each site. Based on qualitative and quantitative analyses of the data, this research identifies nine critical factors that facilitate contents generation and sharing activities among users. In the context of culture, we suggest voluntary community norms, proactive use of copyrights, strong user relationships, and a fair monetary reward system as critical elements in facilitating the process of contents generation and sharing activities. Norms which were established by users themselves regulate user behavior and influence content format. Strong relationships of users stimulate content generation activities by enhancing collaborative content generation. Particularly, users generate contents through collaboration with others, based on their enhanced relationship and specialized skills. They send and receive contents by leaving messages on website or blogs, using instant messenger or SMS. It is an interesting and important phenomenon, because the quality of contents can be constantly improved and revised, depending on the specialized abilities of those engaged in a particular content. In this process, the reward system is an essential driving factor. Yet, monetary reward should be considered only after some fair criterion is established. In terms of the context of the situation, the quality of contents uploading system was proposed to have strong influence on the content generating activities. Among other influential factors on contents generation activities are generators' specialized skills and involvement of the users were proposed. In addition, the audience response, especially effective development of shared interests as well as feedback, was suggested to have significant influence on contents generation activities. Content generators usually reflect the shared interest of others. Shared interest is a distinct characteristic of UCC and observed in all the three websites, in which common interest is formed by the "threads" embedded with content. Through such threads of information and contents users discuss and share ideas while continuously extending and updating shared contents in the process. Evidently, UCC is a new paradigm representing the next generation of the Internet. In order to fully utilize this innovative paradigm, we need to understand how users take advantage of this medium in generating contents, and what affects their content generation activities. Based on these findings, UCC service providers should design their websites as common playground where users freely interact and share their common interests. As such this paper makes an important first step to gaining better understand about this new communication paradigm created by UCC.

• Cartoon and Animation Studies
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• s.43
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• pp.285-320
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• 2016

Cartoons and Animation are convergent arts created with a composite application of language arts described in the form of literary texts and sounds, plastic arts visualized in the form of artistic paintings, and film arts produced in the form of moving pictures. An academic university major in cartoons and animation studies established in late 20th century however, did not satisfactorily meet the needs in academic research and development and the free expression of artistic creation was limited. In order to systematize the major in cartoons and animation studies, an convergent approach to establish and clarify following are in demand : the terms and definitions, the historical developments, the research areas and methods, the major education and related jobs and start-ups. New culture and arts industries including cartoons, animation, moving images, and games contents are not yet listed in the industries listing service jointly provided online by the portal site Naver.com and Hyung-Seol publishing company. Above all, cartoons and animation are inseparably related to each other that even if one uses the term separately and independently, the meaning may not be complete. So a new combined term "Animatoon" can be established for the major in cartoons and animation studies and also used for its degree with concentrations of cartoons, animation, moving images, games, and etc. In the Introduction, a new combined term Animatoon is defined and explained the use of this term as the name of the major and degree in cartoons and animation studies. In the body, first, the Historical Developments classified Animatoon in the ancient times, the medieval times, and the modern times and they are analyzed with the help of esthetics and arts using examples of mural frescos, animal painting, religion cartoons, caricatures, cartoons, satire cartoons, comics, animation, 2 or 3 dimensional webtoons, and K-toons. Second, the Research Areas of Animatoon reviewed the theories, genres, artworks, and artists and the Research Methods of Animatoon presented the curriculum that integrated the courses in humanities, science technologies, culture and arts, and etc. Third, the Major Education considered Animatoon education in children, young adults, students of the major and the Related Jobs and Start-Ups explored various jobs relating to personal creation of artwork and collective production of business-oriented artwork. In the Conclusion, the current challenges of Animatoon considered personalization of the artists, specialization of the contents, diversification of the types, and liberalization of the art creation. And the direction of improvement advocated Animatoon to be an academic field of study, to be an art, to be a culture, and to be an industry. The importance of cartoons and animation along with videos and games rose in the 21st century. In order for cartoons and animation to take a leading role, make efforts in studying Animatoon academically and also in developing Animatoon as good contents in the cultural industries.