• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.23-38
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• 2012

Massive Multiplayer Online Role Playing Games(MMORPGs) headed by some Korean game companies such as NC Soft, NHN, and Nexon have exploded in recent years. However, it becomes one of the major challenges for the MMORPG developers to design their games to appeal to gamers since only a few MMORPGs succeed whereas they require a huge amount of initial investment. Under this background, our study derives the major elements for designing MMORPG from the literature, and identifies the ones critical to the users' satisfaction and their willingness to pay among the derived elements. Though most previous studies on the design elements of MMORPG have used analytic hierarchy process(AHP), our study adopts artificial neural network(ANN) as the tool for identifying key success factors in designing MMORPG. The results of our study show that the elements of the game contents quality have a bigger effect on the user's satisfaction, whereas the ones of the value-added systems have a bigger effect on the user's willingness to pay. They also show that user interface affects both the user's satisfaction and willingness to pay most. These results imply that the strategies for the development of MMORPG should be aligned with its goal and market penetration strategy. They also imply that the satisfaction and revenue generation from MMORPG cannot be achieved without convenient and easy control environment. It is expected that the new findings of our study would be useful forthe developers or publishers of MMORPGs to build their own business strategies.

• Archives of design research
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• v.20 no.3 s.71
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• pp.29-38
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• 2007

The competition to capture a larger slice of the market in Mobile Communication business is increasing among companies. In order to achieve and maintain a competitive advantage in the Asian market, it is critical to continue to develop new technology. Understanding the underlying distinctive characteristics and needs of each market and the cultural backgrounds that drive those needs is a necessary focus. Companies with marketing strategies based on a correct understanding of market needs will capture dominant positions in the market. The purpose of this study is to identify those differences in user behavior and cultural tendencies among different people in different countries in the mobile telecommunication market. This research is based on an on-line survey in three countries (Korea, China, and Japan). Below are the contents of the survey on the mobile phone based on: 1) User behavior 2) Design preference 3) Purchasing behavior 4) User awareness on manufacturer brand. Through the analysis of this questionnaire it is possible to identify the differences and similarities among countries dearly. 1) Cultural trends and perceptions related to mobile phone usage were largely caused by differences in the state of technology, policies and business strategies of mobile sonics carriers and manufacturers, and national tendencies, of each country. 2) Korean and Japanese users produced similar responses to the questions related to advanced technology, whereas Korean and Chinese users responded similarly to national tendency-related questions. 3) To the questions related to business strategies of mobile service carriers and manufacturers, users in all three countries displayed markedly different responses. Once again, accurate analysis of the differences and similarities related to mobile phone usage in each country will help the companies in this industry to gain a competitive edge in the market. This study should not stop at simple comparison but be a framework for giving companies a dear future direction for technological development.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.95-105
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• 2013

Recently, SME's Collaboration activities have become one of a vital factor for sustaining competitive edge. This is because of the rapidly changing and competitive market environment, and also to leverage performance by overcoming obstacles of having limited internal resources. Discussing about the effects and relationships of the firm's collaboration activities and its outputs are not new. However, as ICT and various technologies have been diffused into the traditional industries, boundaries and practice capabilities within the industries are becoming ambiguous. Thus contents of the products/services and their development methods are also go and come over the industries. Although many researchers suggested the relations of SME's collaboration activities and innovation performances, most of the previous literatures are focusing on broad perspectives of firm's environmental factors rather than considering various SME's idiosyncrasy factors such as their major product and customer types at once. Therefore, the purpose of this paper is to analyze how SME(Small Medium Enterprise)'s external collaboration activities by their idiosyncrasy act as an input to types of innovation performance. In order to analyze collaboration effects in detail, we defined factors that can represent the SME's business environment - Perceived importance of using external resources, Perceived importance of external partnership, Collaboration and Collaboration levels of Major Product types, Customer types and lastly the Firm Sizes. We have also specifically divided the performance of innovation types as product innovation and process innovation based on existing research. In this study, the empirical analysis is based on Probit Regression Model to observe the correlations with the impact of each SME's business environment and their activities. For the empirical data, 497 samples were collected which, this sample data was extracted from the 'Korean Open Innovation Survey' performed by ETRI(Korean Electronics Telecommunications Research Institute) in 2010. As a result, empirical test results indicated that the impact of collaboration varies depend on the innovation types (Product and Process Innovation). The Impact of the collaboration level for the product innovation tend to be more effective when SMEs are developing for a final product, targeting on for individual customers (B2C). But on the other hand, the analysis result of the Process innovation tend to be higher than the product innovation, when SMEs are developing raw materials for their partners or to other firms targeting on for manufacturing industries(B2B). Also perceived importance of using external resources has effected to both product and process innovation performance. But Perceived importance of external partnership was statistically insignificant. Interesting finding was that the service product has negative effects on for the process innovation performance. And Relationship between size of the firms and their external collaboration activities with their performance of the innovations indicated that the bigger firms(over 100 of employees) tend to have better for both product and process innovations. Finally, implications of the results can be suggested as performance of innovation can be varied depends on firm's unique business idiosyncrasy as well as levels of external collaboration activities. The Implication of this research can be considered for firms in selecting an appropriate strategy as well as for policy makers.

• Information Systems Review
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• v.11 no.1
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• pp.161-179
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• 2009

Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.113-145
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• 2008

Marketing for the distribution industry is making an ongoing progress in the changes of customers, the competitive environment, and the internal marketing environment. Integrated marketing communication activities are required for the enhancement of efficiency in the market.oriented activities. In this study, IMC is defined as "a notion that a market oriented business integrated marketing communication means, conducting and evaluating marketing activities with consistent messages in order to communicate with customers based on databases." In this study, an IMC planning model for the improvement of marketing efficiency in the distribution industry was derived from a pilot study. This model may be broken down into the following phases: IMC goals setting, situational analysis (customer analysis, competition analysis and company analysis), customer data analysis, contact management, budgeting, the establishment of an IMC strategy, the IMC mix and execution, an evaluation system, and feedback. In consideration of the characteristics of the distribution industry, this study was accompanied by a vocational study on IMC means employed by, in particular, department stores and other distributors such as: advertising, sales promotion, sales promotion advertising, direct marketing, public relations, personal selling, the Internet, mobile, visual merchandising, words of mouth. In addition, this study also covered the correlation among variables such as IMC activities of distributors, the process of forming customer's brand attitudes, brand loyalty and repurchase intention. This research would enhance the utilization of IMC. The analysis on customer's brand attitudes toward the IMC activities of distributors requires the simultaneous consideration of how they are linked to purchase as well as their attitudes toward both distributors and stores. The formation of brand loyalty and repurchase intention is related to the integration of marketing communication and the maintenance of consistency in contents, which requires integrated brand communication (IBC) strategies. IBC is a concept of using IMC means to manage the brand in a continuing and consistent manner and measuring their effect, which is a process to establish enterprise.level brand identity and maximize brand loyalty and repurchase intention by integrating IMC means. For an empirical analysis in this study, an online questionnaire survey was conducted among those department store customers from 20's to 50's who reside either in the Seoul and Gyeonggi areas and have made purchase at department stores. In this study, the research model consisted of four theoretical variables: IMC activities, IMC attitudes, brand loyalty, and repurchase intention, on which variables a pilot study was conducted. A number of hypotheses were constructed on the relations between IMC activities and IMC attitudes, between IMC attitudes and repurchase intention, and between brand loyalty and repurchase intention. The test of the hypotheses may be summarized as follows: Firstly, the test of the hypothesis concerning the relation between IMC attitudes and IMC activities - advertising, sales promotion, direct marketing, public relations, personal selling, the Web, mobile, visual merchandising, and word of mouth - indicates that advertising, sales promotion, direct marketing, public relations, personal selling, mobile, visual merchandising, and word of mouth have significant impact on IMC activities. In addition to the result similar to those of previous studies that such marketing communication means as word of mouth, advertising, personal selling and sales promotion, in particular, play very important roles, a notable finding of this study is that visual merchandising performed by department stores is shown to have very significant impact on IMC activities. On a separate note, it is also noteworthy that Internet marketing activities engaged by department stores are not shown to have significant impact on IMC attitudes. Secondly, the test of the hypothesis on the relation between IMC attitudes and brand loyalty attests that IMC attitudes for the distribution industry significantly affect brand loyalty. Thirdly, the test of the hypothesis concerning the relation between IMC attitudes and repurchase intention confirms that IMC attitudes for the distribution industry significantly affect repurchase intention. Fourthly, the test of the hypothesis concerning the relation between brand loyalty and repurchase intention indicates that brand loyalty significantly affect repurchase intention. A comprehensive view of these findings points to the conclusion that the IMC activities for the distribution industry do affect IMC attitudes, brand loyalty, and repurchase intention.

• Journal of Korean Society of Archives and Records Management
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• v.3 no.1
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• pp.69-92
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• 2003

Registration and description of records are important elements of processing which provide with the background information of production of records and business-related information. They also enable to search and use the records. In this paper, I examined the Korean registration and description system defined in the Public Records Management Act which directs the records creating agency to register records in creating offices and directs the "professional archives" to make "basic registrations" and "detailed registrations" of the records. In the analysis and comparison of two different registration and description systems with the known international standards of records and archives management, such as ISO15489 and ISAD(G), I intended to evaluate the Korean records and archives management system and suggested recommendations for the renovation of the Korean recordskeeping system. Despite we have unique office business procedures and the culture of officialdom, and despite we have developed our system based on the established business procedures and office culture, it would be preferable to adopt or follow the international standards and established best practices. After the comparative analysis, I recommended some innovations in the filed of registration and description. For instance, in the basic registration. we would better to install an item of "simple contents summary." We may also need the multiple-level description. The fonds level description and the series level description should be introduced to our archival automated management system. We need to establish a Korean standard of description adopting the rules of the ISAD(G) and ISAAR(CPF). Essential requirements for electronic records management, such as contextual and structural information, should be incorporated in the new standard. Documentation of records disposition also should be reinforced to guarantee the authenticity of records and to ensure control of the records. To implement the recommendations for the standard, we need to amend the Public Records Management Act and its Regulations and Rules. Also it is imperative to redesign the GARS integrated archival automated management system.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.159-175
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• 2021

This study attempted to analyze the relationship between influencer's characteristic factors such as professionalism, authenticity, and interactivity and content quality factors consisting of accuracy, completeness, and diversity on brand attitude and purchase attitude through trust and self-consistency. To reveal the structural relationship between main variables, a survey was conducted on 201 users. An EFA, CFA, and reliability analysis were performed to confirm reliability and validity. And structural equation was conducted to verify hypothesis. The main results are as follows. First, it was found that professionalism and interactivity had a significant positive effect on trust. And, accuracy, completeness, and variety were all found to have a significant positive effect on trust. Second, in the relationship between individual characteristic factors and self-consistency, it was found that professionalism and authenticity had a significant positive effect on self-consistency. In addition, in the relationship between content quality and self-consistency, accuracy, completeness, and diversity were found to have a positive effect on self-consistency along with trust. Third, in the relationship between trust and self-consistency on brand attitude and purchase intention, both trust and self-consistency were found to have a statistically significant positive effect on brand attitude. It was found that only self-consistency and brand attitude had a statistically significant positive effect on purchase intention. These findings showed that when users perceive professionalism and interaction with influencer, trust increases, and professionalism and progress increase self-consistency with influencer. In addition, in the case of content quality, it was found that trust and self-consistency responded positively when perceived content quality through content accuracy, completeness, and diversity. Also, trust and self-consistency increased attitudes toward brands and could influence consumption behavior such as purchase intention. Therefore, for effective marketing performance using influencer's influence in the field of influencer marketing, which has a strong information delivery on products and brands, not only personal characteristics such as professionalism, authenticity, and interactivity, but also quality of content should be considered. The above research results are expected to suggest implications for marketing strategies and practices as one available basic data to exert the expected effect of marketing using influencer.