• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.1-20
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• 2003

This paper aims to examine the contribution that the ERVET System, composed of ERVET and real service centers, has made to both governing and enhancing regional innovation system in Emilia Romagna, Italy. ERVET and real service centers both establish and perform plans for regional development and innovation. But they also try to provide varieties of real services for local firms, mostly small and medium-sized firms. Attempting to promote innovation networks between industries, universities and administrative bodies, the ERVET System has become a core intermediary agency of Emilia Romagna in both governing regional innovation system and enhancing regional innovation capabilities. Based on the case of the ERVET System, we propose a policy recommendation. As local governments in Korea have still been less autonomous but hierarchical, it would be difficult for them to make the decision effectively on regional innovation and development initiatives. In this context, we suggest that regional development agencies need to be established on the basis of benchmarking advanced cases in Europe and North America such as the ERVET System.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.461-470
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• 2017

In Korea, starting with the Government 3.0 Policy, the utilization of public data as an important driving force to promote economic growth has been highlighted as a major issue. However Korea is currently only able to open and provide accumulated data stored in the public domain. To resolve this issue, we need to not only open and provide public information, but also to create new information by linking the data and developing related services. Thus, this study analyzes the linkability of public information and provides lists of the linkable public data. In order to do this, we first have performed preconditioning processes on the accessibility and workability of the data. Next, we have deduced the major keywords in public data through analyzing the morphemes, and then the core keywords (Top 10) and their linkable keyword lists through an analysis of social networks. Based on the outcome of this study, a subsequent study will deduce new information by linking the public data and creating various services and information contents. Furthermore, not only conceptual but also practical linking measures need to be created, and a related law must be prepared.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.177-189
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• 2020

To newly discover the placeness of Xita Koreatown in Shenyang, this study establishes the conceptual structure of urban inclusivity based on the actor-network theory and the main discourse of inclusive cities. It then applies a framework to the relevant space for analysis. We conduct the case study by first identifying a historical timeline by dividing the age from the founding of New China to the present into sprouting and developing stages of Xita Koreatown, extracting major actors out of time, and finally creating a network graph for each of the six periods representing changes in the region. Throughout this process, we not only analyze the aspect of transition in the urban inclusivity of Xita Koreatown but also prospect the feasibility of an inclusive city for the area. The results of this study are as follows. First, the number and type of actors constituting Xita Koreatown have constantly increased significantly since the establishment of diplomatic relations between China and South Korea. The related actor-networks have also continued to expand in all indicators of urban inclusivity. Secondly, the agency of human actors such as Korean-Chinese, locals, and both South and North Koreans, representing the specificity of Xita Koreatown, has continuously improved. Lastly, due to the increase of cultural exchanges and related policy actors, the actor-network in this region has achieved an unprecedented leap forward. In conclusion, the urban inclusivity of Xita Koreatown in Shenyang shows significant growth in quality, with expectations of further improvement.

• Journal of KIISE:Information Networking
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• v.34 no.2
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• pp.120-133
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• 2007

A multicast tree includes several, possibly a large number of, paths connecting source-receiver pairs, and network failure may disable part of the multicast tree. Reconstruction of the entire multicast tree to recover from a component failure is highly undesirable, because some group members have to suffer service disruptions even though the communication paths to/from them are not affected by the failure. To limit reconfiguration region and to maximize the likelihood of successful reconfiguration, we propose and evaluate a pre-planned reconfiguration policy for QoS multicast sessions. Specifically, we equip a reconfiguration path (RP) with each end-to-end path that connects a source-receiver pair in the multicast tree, and reserve resources in advance along the RPs. Efficient resource-sharing techniques are applied to reduce the amount of resources reserved for RPs but not used in the absence of failures. This way, we prevent uncontrolled competition among different multicast sessions which may simultaneously try to recover from failures. We evaluate the performance of the proposed scheme using simulation on randomly-generated networks. We use the shortest-path routing for QoS multicast sessions, and simulate both source-based and shared multicast trees. The evaluation results indicates that successful pre-planned reconfiguration can be achieved for all group members with reasonable overhead. Our scheme is also shown to adapt well to dynamic changes of group membership.

• Journal of Digital Convergence
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• v.16 no.4
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• pp.95-105
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• 2018

This study empirically test the roles of network closure and structural hole on radical innovation in technological knowledge exchange network in Gumi cluster. In doing so, we build 2,550 firm network, transforming association*firm(2-mode) to firm*firm(1-mode) network data. In addition, in order to investigate firms' attributes, we conduct survey for 101 firms in Gumi cluster using random sampling, and finally collect 86 firm samples. For analysis, we use ridge regression since network density and efficiency, indices of network closure and structural hole respectively, has a high level of multicollinearity. The findings show that structural hole has a significant and positive impact on radical innovation, but network closure has a significant and negative impact on radical innovation. This study contributes to present an empirical evidence of debate on network closure and structural hole based on past conceptual discussions and literature review and further goes a long way towards strategy formulation to establish social capital in accomplishing radical innovation. Further research is required that pays closer attention to features of technological knowledge, innovation types and interaction between network closure and structural hole, directing efforts to structural characteristics of various networks.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.106-115
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• 2003

Diverse multimedia services will be deployed at hand on 3G-and-beyond multi-service CDMA systems in order to satisfy different quality of service (QoS) according to traffic types. In order to use appropriate resources efficiently the call admission control (CAC) as a major resource control mechanism needs to be used to take care of efficient utilization of limited resources. In this paper, we propose a QoS-aware CAC (QCAC) that is enabled to provide service fairness and service differentiation in accordance with priority order and that applies the different thresholds in received power considering different QoS requirements such as different bit error rates (BER) when adopting total received power as the ceil load estimation. The proposed QCAC calculates the different thresholds of the different traffic types based on different required BER applies it for admission policy, and can get service fairness and differentiation in terms of call dropping probability as a main performance metric. The QCAC is aware of the QoS requirement per traffic type and allows admission discrimination according to traffic types in order to minimize the probability of QoS violation. Also the CAC needs to consider the resource allocation schemes such as complete sharing (CS), complete partitioning (CP), and priority sharing(PS) in order to provide fairness and service differentiation among traffic types. Among them, PS is closely related with the proposed QCAC having differently calculated threshold per each traffic type according to traffic priority orders.

• Korean journal of communication and information
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• v.45
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• pp.220-254
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• 2009

Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.10a
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• pp.1-11
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• 2003

The objectives of this paper are to overview present status of soil pollution in Korea, to review the current policies and management strategies for soil pollution prevention and remediation of contaminated sites, and to suggest some recommendations to be considered toward more efficient policies. Soils in Korea are contaminated mainly by industrial facilities, landfills, underground storage tanks, abandoned/inactive mines, military camps, and other sources. Concentrations of most of soil pollutants were similar to the background levels, except for a few heavily contaminated sites such as industrial sites or abandoned/inactive mines. The Soil Environment Conservation Act (SECA), which was effective from 1995, provides a comprehensive legal framework for both preventing soil pollution and remedying contaminated sites in Korea. The Act includes various management policies such as the designation of standards and soil pollution policy area, soil monitoring networks, management of suspected contamination sources, and extended 'polluter-pays' principle. To make current policies more efficient and reasonable, some policies or strategies such as the establishment of national priority list, more detailed standards, risk-based cleanup goal, fund raise, soil erosion problem, and finally, integrity between soil and groundwater management frameworks may need to be pursued in the long term.