• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Distribution Science
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• v.10 no.11
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• pp.89-99
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• 2012

Purpose - Mobile devices, especially mobile terminals capable of telecommunication and wireless connectivity, are leading the advancements in consumer electronics. Digital convergence drives the functions of various devices, such as cellular phones, MP3 players, personal digital assistants, and gaming, into a single device. This trend would continue and applications such as digital audio and video streaming (including personalized content delivery mechanisms) would soon be on a handheld device. As customers want mobile convergence devices, manufacturers are driving new initiatives in the emerging mobile device market. Given the roles played by device design and service content in user satisfaction of a mobile convergence device, this study focuses on identifying and measuring the constructs for the process by which user satisfaction is achieved. This study synthesizes the expectation-disconfirmation paradigm with empirical theories in user satisfaction. Device and service levels are separated, and nine key constructs for user satisfaction of mobile convergence devices are proposed. Insight into this process could help web-based businesses to improve user satisfaction, thus enhancing the effectiveness of e-commerce for sellers and buyers. Research design, data, methodology - This study draws on three users of mobile convergence devices as examples. To test there search model and hypotheses, survey questionnaires were sent to 607 mobile device users. Mobile device users were initially identified from several members, and subjects were randomly drawn. Data from 577 survey responses were finally analyzed. The unit of measurement and analysis in this research study is at a personal level. Results - The measurements for the constructs were developed and tested in a two-phase study. In the first phase, the device and service dimensions were identified, and instruments for measuring them were developed and tested. In the second phase, using the salient dimensions of the device and service as the formulating first-order factors, instruments were developed and empirically tested to measure satisfaction of the device and service. In measuring satisfaction of mobile convergence devices, the critical tasks are to identify the key constructs of such user satisfaction and to develop validated instruments to measure them. Hence, the results of this study have immediate implications for businesses and for research in user satisfaction of mobile convergence devices. Conclusions - This study provides reliable instruments for operationalizing key constructs in the analysis of user satisfaction of mobile convergence devices within the expectation-disconfirmation paradigm. Hence, convergence device makers will be able to examine whether their websites meet their customers' expectations by examining the device aspect of the mobile convergence device customers, and the service aspect expectations and disconfirmation. Moreover, the introduction of expectation and disconfirmation constructs brings the marketing aspect of convergence devices into focus for such retailers, an aspect crucial to the effective design of websites for online businesses. In addition,this study provides the metrics required to initiate future studies on user satisfaction of mobile convergence devices.

• Archives of design research
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• v.15 no.1
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• pp.191-202
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• 2002

As family types have been diverse, patterns of living and living space became diverse as much as users are. Therefore, it is needed to provide various remodeled design of living space corresponding to changes of users'living patterns, and to provide these remodeling process to users directly on the web. In this paper, use scenario for the Internet-based Virtual Apartment Remodeling Simulator is researched as an export system to remodel space in accordance with users diverse lifestyle paradigm and the website is developed. The study consists of four parts. First, the general concept of remodeling, including the range and types of remodeling, are defined, and the misleading terms in this field are reviewed and organized by secondary research Second, fixed factors and variable factors are differentiated in the complex building for residence and business that was decided as a basic building type in this study. Third, there needed a database for consulting, final material, pre-estimation real estimation for simulation of remodeling. This database was introduced along with floor plan and elevation. Finally, the remodeling simulator is presented by the case study developed on the web. The system structure and use scenario are also presented. In order to present and inspect design alternatives, prototype was produced. The Final simulator was enhanced by defeating problems regarding interface efficiency and missing information of existing online site.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Internet Computing and Services
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• v.6 no.4
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• pp.125-139
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• 2005

Mobile e-business is in wide use with the rapid growth of wireless internet users. To meet the growing requests for mobile e-business the productivity of mobile applications has been demanded. The WAPSiteGen, introduced in this paper, automatically generates a 3-tier WAP application that needs a new application database or that already has an application database to increase the productivity. The WAPSiteGen generates the EJB components that handle business logic and the JSP Web components that process user-made queries and the WAP Push feature. For a presentation layer, it also generates the HTML forms for an application manager and the WML decks for end users, which consists of many cards. The WAPSiteGen enhances extendibility, reusability and portability of generated 3-tier applications by comprising such component technologies as EJB and JSP. Furthermore, it supports the WAP Push services for generated applications that provide necessary information to wherever and at whenever a user wants. Since the applications generated by the WAPSiteGen provide the information on an interested entity as well as the information on all the directly or indirectly related entities to the interested one, it shows faster information accessibility. In this paper, we explain the functionality and implementation of the WAPSiteGen and then show its merits by comparing the WAPSiteGen to commercial WAP application generators.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.425-438
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• 1999

In recent days network computing technologies have bee developed rapidly and the extended use of Internet applications for enterprises such as internet/extarnet in and between enterprises has been increased enormously. Therefore the business in the future will be executed by virtual enterprise. Virtual enterprises which is based on information sharing between enterprises are composed of work processes related to information exchange between virtual enterprises, the team members who are representatives of the organizations that are participated in the actual business of virtual enterprises, and members who are representatives of the organizations that are participated in the actual business of virtual enterprises, and environment that are provided by supporting CALS(continuous Acquisition and Life cycle Support or commerce At light Speed). Supporting system of IDE(Integrated Data Environment)for CALS implementation that is provided as an environment of virtual enterprises has to ensure the autonomies of local data and to provide the accessibility of heterogeneous database of enterprises on network transparently for giving user a single global view of data. This paper introduce the design and implementation of the database broker system that can be accessed data transparently by the suers of participated enterprises in the integrated data environment supporting virtual enterprises. The system uses java/CORBA technology in Web environment and Object Query language (OQL) to process the queries of relational database system, object-oriented database system, and file information.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.229-234
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• 2008

XBRL is fundamentally defined as a structure that enterprises expand based on KGAAP 2.1 developed by the Korea branch of XBRL. Each enterprise selects its type of business and must check and choose the tag suitable to each enterprise. Since a complicated part such as expanding tag exists, there is a difficulty to prepare document through the step of tag expansion and data input. Although the expressive way of style provides the standards using the presentation structure and label structure provided fundamentally by XBRL, there is a complicated problem of using XBRL Processor. The electronic public disclosure system of the Financial Supervisory Service (DART) and Korea Exchange (KIND, KEDIS) use the Markup Language of SGML, XML and XBRL as format language. The procedure of defining document and process method vary in accordance with the characteristics of each language. This study analyzes the effect by step in accordance with format language of each electronic disclosure system and studies a direction of format language.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.264-274
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• 2006

Recently, a variety of organizations including enterprises tend to try to use reporting tools as a data analysis tool for decision making support because reporting tools are capable of formatting data flexibly. Traditional reporting tools have thin-client structure in which all of dynamic documents are generated in the server side. This structure enables reporting tools to avoid repetitive process to generate dynamic documents, when many clients intend to access the same dynamic document. However, generating dynamic documents for data analysis doesn't consider a number of potential readers and increases requests to the server by making clients input various parameters at short intervals. In the structure of the traditional reporting tools, the increase of these requests leads to the increase of processing load in the server side. Thus, we present the reporting tool that can generate dynamic documents at the client side. This reporting tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the client side.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.6
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• pp.969-981
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• 2010

This study explains the consumer acceptance of smart clothing using the extended Technology Acceptance Model (TAM); in addition, it compares the difference in the path hypotheses of the perceived group and nonperceived group from the aspect of the extended TAM. A total of 815 copies of questionnaire were collected from a web-based survey in March 2009. Structural equation modeling was used to examine the entire pattern of intercorrelations among the constructs and to test related propositions using an AMOS 5.0 package. The fitness of the extended TAM explains the process of the adaptation of smart clothing. Technology Innovation (TI) and Clothing Involvement (CI) were confirmed as antecedent variables to affect TAM. In the perceived group, Technology Innovation (TI) and Clothing Involvement (CI) showed significant impacts on the Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) while Technology Innovation (TI) did not influence the Perceived Ease of Use (PEOU) in the non-perceived group. Perceived Ease of Use (PEOU) influenced the Perceived Usefulness (PU) and indirectly influenced Attitude (A) through the Perceived Usefulness (PU) in both groups. In addition, Perceived Usefulness (PU) did not influence Acceptance Intention (AI) but indirectly affected Acceptance Intention (AI) through Attitude (A). Therefore, Attitude (A) was found to be an important parameter in the adaptation of smart clothing in both groups. This finding implies that consumers first perceive the usefulness of smart clothing, then take favorable attitudes towards the smart clothing, and finally have the intention to adopt it. Strategies for publishing and informing consumers of the functions of smart clothing and usefulness in life are necessary; in addition, understanding what useful values they expect from the clothing is also crucial.