• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.11-23
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• 2009

HSDPA (High-Speed Downlink Packet Access) is a 3.5-generation asynchronous mobile communications service based on the third generation of W-CDMA. In Korea, it is mainly provided in through videophone service. Because of the diffusion of more powerful and diversified services, along with steep advances in mobile communications technology, consumers demand a wide range of choices. However, because of the variety of technologies, which tend to overflow the market regardless of consumer preferences, consumers feel increasingly confused. Therefore, we should not adopt strategies that focus only on developing new technology on the assumption that new technologies are next-generation projects. Instead, we should understand the process by which consumers accept new forms of technology and devise schemes to lower market entry barriers through strategies that enable developers to understand and provide what consumers really want. In the Technology Acceptance Model (TAM), perceived usefulness and perceived ease of use are suggested as the most important factors affecting the attitudes of people adopting new technologies (Davis, 1989; Taylor and Todd, 1995; Venkatesh, 2000; Lee et al., 2004). Perceived usefulness is the degree to which a person believes that a particular technology will enhance his or her job performance. Perceived ease of use is the degree of subjective belief that using a particular technology will require little physical and mental effort (Davis, 1989; Morris and Dillon, 1997; Venkatesh, 2000). Perceived pleasure and perceived usefulness have been shown to clearly affect attitudes toward accepting technology (Davis et al., 1992). For example, pleasure in online shopping has been shown to positively impact consumers' attitudes toward online sellers (Eighmey and McCord, 1998; Mathwick, 2002; Jarvenpaa and Todd, 1997). The perceived risk of customers is a subjective risk, which is distinguished from an objective probabilistic risk. Perceived risk includes a psychological risk that consumers perceive when they choose brands, stores, and methods of purchase to obtain a particular item. The ability of an enterprise to revolutionize products depends on the effective acquisition of knowledge about new products (Bierly and Chakrabarti, 1996; Rothwell and Dodgson, 1991). Knowledge acquisition is the ability of a company to perceive the value of novelty and technology of the outside (Cohen and Levinthal, 1990), to evaluate the outside technology that has newly appeared (Arora and Gambaradella, 1994), and to predict the future evolution of technology accurately (Cohen and Levinthal, 1990). Consumer innovativeness is the degree to which an individual adopts innovation earlier than others in the social system (Lee, Ahn, and Ha, 2001; Gatignon and Robertson, 1985). That is, it shows how fast and how easily consumers adopt new ideas. Innovativeness is regarded as important because it has a significant effect on whether consumers adopt new products and on how fast they accept new products (Midgley and Dowling, 1978; Foxall, 1988; Hirschman, 1980). We conducted cross-national comparative research using the TAM model, which empirically verified the relationship between the factors that affect attitudes - perceived usefulness, ease of use, perceived pleasure, perceived risk, innovativeness, and perceived level of knowledge management - and attitudes toward HSDPA service. We also verified the relationship between attitudes and usage intention for the purpose of developing more effective methods of management for HSDPA service providers. For this research, 346 questionnaires were distributed among 350 students in the Republic of Korea. Because 26 of the returned questionnaires were inconsistent or had missing data, 320 questionnaires were used in the hypothesis tests. In UK, 192 of the total 200 questionnaires were retrieved, and two incomplete ones were discarded, bringing the total to 190 questionnaires used for statistical analysis. The results of the overall model analysis are as follows: Republic of Korea x2=333.27(p=0.0), NFI=0.88, NNFI=0.88, CFI=0.91, IFI=0.91, RMR=0.054, GFI=0.90, AGFI=0.84, UK x2=176.57(p=0.0), NFI=0.88, NNFI=0.90, CFI=0.93, IFI=0.93, RMR=0.062, GFI=0.90, AGFI=0.84. From the results of the hypothesis tests of Korean consumers about the relationship between factors that affect intention to use HSDPA services and attitudes, we can conclude that perceived usefulness, ease of use, pleasure, a high level of knowledge management, and innovativeness promote positive attitudes toward HSDPA mobile phones. However, ease of use and perceived pleasure did not have a direct effect on intention to use HSDPA service. This may have resulted from the fact that the use of video phones is not necessary for everyday life yet. Moreover, it has been shown that attitudes toward HSDPA video phones are directly correlated with usage intention, which means that perceived usefulness, ease of use, pleasure, a high level of knowledge management, and innovativeness. These relationships form the basis of the intention to buy, contributing to a situation in which consumers decide to choose carefully. A summary of the results of the hypothesis tests of European consumers revealed that perceived usefulness, pleasure, risk, and the level of knowledge management are factors that affect the formation of attitudes, while ease of use and innovativeness do not have an effect on attitudes. In particular, with regard to the effect value, perceived usefulness has the largest effect on attitudes, followed by pleasure and knowledge management. On the contrary, perceived risk has a smaller effect on attitudes. In the Asian model, ease of use and perceived pleasure were found not to have a direct effect on intention to use. However, because attitudes generally affect the intention to use, perceived usefulness, pleasure, risk, and knowledge management may be considered key factors in attitude development from which usage intention arises. In conclusion, perceived usefulness, pleasure, and the level of knowledge management have an effect on attitude formation in both Asian and European consumers, and such attitudes shape these consumers' intention to use. Furthermore, the hypotheses that ease of use and perceived pleasure affect usage intention are rejected. However, ease of use, perceived risk, and innovativeness showed different results. Perceived risk had no effect on attitude formation among Asians, while ease of use and innovativeness had no effect on attitudes among Europeans.

• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.49-67
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• 2015

Recently, emerging the notion of big data and social media has led us to enter data's big bang. Social networking services are widely used by people around the world, and they have become a part of major communication tools for all ages. Over the last decade, as online social networking sites become increasingly popular, companies tend to focus on advanced social media analysis for their marketing strategies. In addition to social media analysis, companies are mainly concerned about propagating of negative opinions on social networking sites such as Facebook and Twitter, as well as e-commerce sites. The effect of online word of mouth (WOM) such as product rating, product review, and product recommendations is very influential, and negative opinions have significant impact on product sales. This trend has increased researchers' attention to a natural language processing, such as a sentiment analysis. A sentiment analysis, also refers to as an opinion mining, is a process of identifying the polarity of subjective information and has been applied to various research and practical fields. However, there are obstacles lies when Korean language (Hangul) is used in a natural language processing because it is an agglutinative language with rich morphology pose problems. Therefore, there is a lack of Korean natural language processing resources such as a sentiment lexicon, and this has resulted in significant limitations for researchers and practitioners who are considering sentiment analysis. Our study builds a Korean sentiment lexicon with collective intelligence, and provides API (Application Programming Interface) service to open and share a sentiment lexicon data with the public (www.openhangul.com). For the pre-processing, we have created a Korean lexicon database with over 517,178 words and classified them into sentiment and non-sentiment words. In order to classify them, we first identified stop words which often quite likely to play a negative role in sentiment analysis and excluded them from our sentiment scoring. In general, sentiment words are nouns, adjectives, verbs, adverbs as they have sentimental expressions such as positive, neutral, and negative. On the other hands, non-sentiment words are interjection, determiner, numeral, postposition, etc. as they generally have no sentimental expressions. To build a reliable sentiment lexicon, we have adopted a concept of collective intelligence as a model for crowdsourcing. In addition, a concept of folksonomy has been implemented in the process of taxonomy to help collective intelligence. In order to make up for an inherent weakness of folksonomy, we have adopted a majority rule by building a voting system. Participants, as voters were offered three voting options to choose from positivity, negativity, and neutrality, and the voting have been conducted on one of the largest social networking sites for college students in Korea. More than 35,000 votes have been made by college students in Korea, and we keep this voting system open by maintaining the project as a perpetual study. Besides, any change in the sentiment score of words can be an important observation because it enables us to keep track of temporal changes in Korean language as a natural language. Lastly, our study offers a RESTful, JSON based API service through a web platform to make easier support for users such as researchers, companies, and developers. Finally, our study makes important contributions to both research and practice. In terms of research, our Korean sentiment lexicon plays an important role as a resource for Korean natural language processing. In terms of practice, practitioners such as managers and marketers can implement sentiment analysis effectively by using Korean sentiment lexicon we built. Moreover, our study sheds new light on the value of folksonomy by combining collective intelligence, and we also expect to give a new direction and a new start to the development of Korean natural language processing.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.109-135
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• 2021

his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.15-29
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• 2021

The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.

• Journal of the Society of Disaster Information
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• v.8 no.1
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• pp.1-9
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• 2012

Informatization of society through the computer and the Internet, because large amounts of information production and exchange and new way of communicating is born. Passive way past the one-sided information flows actively interact to evolve in a manner of information producers and information consumers distinction and personal relationships that enhance the online Social Networking Service (SNS) has developed into the social structure of. Thus, the spread of information work closely with the social network structure spark social conflict may act as a factor, and systems and the environment, personal and cultural adaptation of speed to keep up with the rapid development of science and technology as the inability conflict and confusion should lead to even. This paper the characteristics of the information society, with a look at the evolution of social risk factors as the wavelength of information about this look at the role of private security sought to evaluate. Information Society in time and space by shrinking the area of human life that has brought the convenience and simplicity, whereas the non-performance due to the nature of anonymous raises many social side-effects are. This made the preparation of national regulatory measures, but for the protection of personal protection devices in the private sector has not yet been discussed. Way of life and property of the purchaser to protect an individual's private security will have to charge it.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.552-557
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• 2015

Recent performed by recognizing a user's location, various services have been tailored focus on short-range wireless communication technology. A beacon in which is attracting attention as next-generation technology. Beacon is a terminal by utilizing the frequency of the non-audible area can not be bluetooth and human sending and receiving terminals and information, Apple recently iBeacon like a low-power Bluetooth (BLE; bluetooth low energy) based beacon showing a tendency to rise into the mainstream there. Services using a beacon is basically installs the terminal in a certain place indoor. It is characterized by providing the user the services to catch the user's position, even automatically take a separate action. Various types of location-based service provided by the target interior space began to attract attention. A variety of location-based services are provided in the interior space in order to be successfully deployed and provide guidance to the interior space, the movement route and the like are essentially required to build various types of information. In this paper, for efficient indoor positioning by varying the signal strength of the beacon in such areas were measured and analyzed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2780-2792
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• 2010

In this study, we examine what components of e-learning environment affect e-learners' satisfaction. We focus on the task based approach to perceived website complexity(PWC). We study about the role of e-tutor using the internet, telephone, text message and e-mail etc. To test our model, we collected 235 data from online learners of Korea Culture & Content Agency using survey method. The research was conducted by SPSS15.0. Our results show that the relationship between PWC and e-learner satisfaction was negative. The rules of e-tutor are supporting e-learning service and facilitating recommendation intention. This study provides implications to design future e-learning service, understand user's herd behavior and evaluate learning process developed.