• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.1-25
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• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• The Journal of Information Systems
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• v.22 no.2
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• pp.51-83
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• 2013

Personal creativity is critically important for organizations seeking to survive and thrive in today's highly turbulent business environments. Organizations must effectively identify and mobilize the creative resources of their members. When organizational members perceive a work environment that restricts or fails to encourage individual creative expression, a gap may exist between the level of individual creative potential and the actual amount of individual creativity practiced within the organization. In this situation, this paper will examine the impact of role conflict, role ambiguity, creative self-efficacy, and personal initiative on personal creativity. Creative self-efficacy is the subjective belief in one's personal ability to be creative, that is, a personal assessment of one's own creative potential. A strong internal belief in one's ability to successfully engage in creative behaviors is generally considered an important part of the creative process. Personal Initiative refers to behaviors, mainly directed toward work and organizational issues, that are characterized by the following aspects: self-starting, proactive, and persistent in overcoming barriers. Creativity-related creative self-efficacy and personal initiative are critical components to understand motivation that coordinates the relationship between perception and behavior of individual employees. Based on role theory, researchers have focused on role conflict and role ambiguity as the two key ingredients of role stress. Role ambiguity is defined as an evaluation about the lack of salient information needed to perform a role effectively. Role conflict results from two or more sets of incompatible demands involving work-related issues. Employees are usually pursued work-roles more than one in work-focused organization. Too many work-roles and perceived uncertainties at employee's work can be obstacles to personal creativity. In an analysis of results, while role conflict is not negatively related significantly to creative self-efficacy, role ambiguity is negatively related significantly to creative self-efficacy. While role conflict is significantly related to personal creativity, role ambiguity is negatively related significantly to personal creativity. Creative self-efficacy mediates the relationship among role conflict, role ambiguity, and employee creativity. Personal initiative mediates the relationship between creative self-efficacy and employee creativity. This paper shows that creative self-efficacy and personal initiative are the driving force behind personal creativity. Organizations can get some implications of creative-related role conflict and role ambiguity that employees have experienced. As a result, organizations must not only encourage creativity of employees by greater involvement but also encourage their input towards their-focused own works and tasks. And employees should be developed to pace with the organizational needs and development. Management must enable employees to think of new ideas and practices that promotes personal creativity.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.155-166
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• 2012

The rapid development of information technology and emergence of the internet have created a borderless business environment and intensified market competition. Riding on the globalization trend, companies have been gradually leveraging information technology in order to shorten their manufacturing processes, enhance productivity with lower costs and prompt delivery to meet the customers' needs. To achieve these targets and maintain competitive advantage, companies have been introducing enterprise resource planning (ERP). This study distributed and collects the questionnaire which is suitable for the research goals during 25 days from march 12th, 2012, to April 6th, 2012. Totally 226 employees answer the questionnaires by the method of direct visiting interview. The results are as follows; In the relationship between management performance and ERP-introducing factors, the moderating effect of internal performance has significant influence by statistical analysis. Our findings suggest that a better understanding of the contribution of ERP systems to business performance and introducing ERP system.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.744-747
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• 2008

Quantity information focused on a design drawing plays a critical role in a decision making related to cost for project participants during project life cycles. Related participants absolutely depend on quantity take-off working which produces the quantity information by hand, and then a worker's mistake often causes many errors. The difference of quantity by the know-how of the person in charge of the estimation also occurs. In addition, the worker passes through the whole quantity take-off processes again in case of re-working for quantity take-off produced by a change order. The requirements about the automated estimation increase because of the needs for the accurate quantity take-off and dealing with the change order and recently, the studies about the automated estimation working process based on 34 cad model from 3d cad modeler are attempted in various viewpoints. However, the existing studies reach the limits such as common quantity data type framework for getting Quantity information. Focused on a certain 34 cad modeler and BIM based automation of estimation using it Therefore, the objective of this study is to develop the a series of system which can extract, analyze, and verify Quantity Data Type in modeler to automate quantity take-off originated from various 3d cad modelers as a foundation study for BIM based automation of estimation framework.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.211-222
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• 2009

Electronic publishing has influenced, and in some ways changed, information seeking, reading patterns and citation behaviours. This study collected the Cited Half-Lives, the indicator implies the life-span of scholarly journals, from JCR Social Science edition the before and after of the prevalence of electronic journals, and observed if there are some changes in these two periods. The analysis results of eight disciplines show that the average Cited Half-Lives increased in 2007 than in 1994 for seven disciplines except the demography. Especially in the four disciplines of economics, education, finance and sociology, the average Cited Half-Lives increased significantly. This results show that the concentration, researchers cite more recent articles and concentrate their citations on fewer ones, is lightening and the dispersion of citations is actually increasing. With the online availability of articles and journals the old online materials can be often accessed, used and cited more frequently, the more growth potential of Cited Half-Lives are made in a digital environment. Further research needs to investigate if the phenomenon will become more obvious in various disciplines after a few years.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.511-520
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• 2011

In this paper, we introduce a multiuser (MU) scheduling method for multiuser amplify-and-forward relay systems, which selects both the transmission mode, i.e., either one- or two-hop transmission, and the desired user via two steps. A closed-form expression for the average achievable rate of the proposed scheduling is derived under two transmission modes with MU scheduling, and its asymptotic solution is also analyzed in the limit of large number of mobile stations. Based on the analysis, we perform our two-step scheduling algorithm: the transmission mode selection followed by the user selection that needs partial feedback for instantaneous signal-to-noise ratios (SNRs) to the base station. We also analyze the average SNR condition such that the MU diversity gain is fully exploited. In addition, it is examined how to further reduce a quantity of feedback under certain conditions. The proposed algorithm shows the comparable achievable rate to that of the optimal one using full feedback information, while its required feedback overhead is reduced below half of the optimal one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.432-440
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• 2011

For the 4th generation mobile communication, LTE-advanced system needs the broad frequency band up to 100MHz for providing the data rate of maximum 1Gpbs. However, it is very difficult to secure the broad frequency band in the current frequency allocation situation. So, carrier aggregation was proposed as the solution, in which several fragmented frequency bands are used at the same time. Basically, multiple parallel receivers are required to get the information data from the different frequency bands but this conventional multi-chain receiver system is very inefficient. Therefore, in this paper, we like to study the single chain system that is able to receive the multi-band signals in a single receiver based on the time division multiplexing (TDM) reception method. This proposed TDM receiver efficiently manage to receive the multi-band signals in time domain and handle the baseband signals with one DSP board. However, the serious distortion could be generated by the sampling timing offset (STO) in the TDM-based system. Therefore, we like to analyze STO effects in the TDM-based system and propose a compensation method using estimated STO. Finally, it is shown by simulation that the proposed method is appropriate for the single chain receiver and show good compensation performance.

• Journal of The Korean Association of Information Education
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• v.11 no.3
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• pp.339-347
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• 2007

Along with developments of information and communication technologies, internet has spread not only all over the society, but also our everyday life deeply. Recently, requirements for e-learning using internet in the educational aspect have a great influence on the changes of school educations. Cyber Home Learning System, in particular, has been implemented throughout the nation for the purpose of reducing private expenditure for education and promoting substantial improvements in quality of public education. However, there have been exposed many problems with respect to quality of operations and managements of the system comparing to its quantitative growth, and so, at this point in time, researcher conducted analysis of actuality of perceptions of both elementary and middle school teachers with a focus on the case of S System in K province. To test this, total 278 participants were sampled from the elementary schools (139 teachers) and the middle schools (139 teachers) located in K province and were asked to complete a survey and the results therefrom were analyzed accordingly. Results from the analyses revealed that elementary school teachers responded more positively than other respondents in the most areas, including supply of a variety of learning contents of S System, quality of contents, and providing for helps insomuch as to complement school works, etcetera. In addition, researcher has found out that, to make the system become all the more efficient, it shall be required to establish a strategy in order to induce students' interest in the system, as well as to construct infrastructure for facilitating the use of computer. And that there are also needs for continuous supports from both the school and the education authority concerned, and for method of flexible operation of curriculum.