• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• 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.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Asian Journal of Turfgrass Science
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• v.17 no.1
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• pp.1-12
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• 2003

Research was Initiated to investigate germination characteristics of cool-season grasses (CSG). Several turfgrasses were tested in different experiments. Experiments I and III were conducted under a room temperature condition of 16$^{\circ}C$ to 23 $^{\circ}C$ and under a constant light condition at 25 $^{\circ}C$, respectively. An alternative environment condition that is a requirement for a CSG germination test by International Seed Testing Association (ISTA) was applied in the Experiment II, consisting of 8-hr light at 25 $^{\circ}C$ and 16-hr dark at 15 $^{\circ}C$. In each experiment, data such as early germinating vigor, germination speed and germination rate were evaluated. Six turfgrass entries were comprised of two varieties each from Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.), respectively. Significant differences were observed in early germinating vigor, germination speed and germination rate. Early germinating vigor as measured by days to 70% seed germination was variable according to environment conditions, turfgrasses and varieties. It was less than 6 days in PR and 6 to 9 days in TF. However, KB resulted in 11 to 13 days under an alternative condition and 11 to 28 days under a room temperature condition. The germination speed was fastest in PR of 7 to 10 days and slowest in KB of 14 to 21 days. However, intermediate speed of 10 to 14 days was associated with TF. There were considerable variations in germination rate among turfgrasses according to different conditions. Generally, PR and TF germinated well, regardless of environment conditions. However, a great difference was observed among KB varieties, when compared with others. Under a room temperature condition, total germination rate was 71.0% in Midnight and 77.7% in Award. And it increased under an alternative condition, which was 81.7% and 91.7% in Award and Midnight, respectively. However, the poorest rate was found under a constant temperature condition, resulting in 18.0% in Award and 15.3% in Midnight. These results suggest that an intensive germination test required by ISTA be needed prior to the decision of seeding rate, including early germinating vigor and germination speed as well as total germination rate. KB is very sensitive to environment conditions and thus its variety selection should be based on a careful expertise.

• Tuberculosis and Respiratory Diseases
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• v.49 no.6
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• pp.724-732
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• 2000

Background : In patients with severe chronic lung diseases even a small pneumothorax can result in life-threatening respiratory distress. It is important to treat the attack by chest tube drainage until the lung expands. Pneumothorax with a persistent air leak that does not resolve under prolonged tube thoracostomy suction is usually treated by open operation to excise or oversew a bulla or cluster of blebs to stop the air leak. Pleurodesis by the instillation of chemical agents is used for the patient who has persistent air leak and is not good candidate for surgical treatment. When the primary trial of pleurodesis with common agent fails, it is uncertain which agent should be used f or stopping the air leak by pleurodesis. It is well known that inappropriate drainage of hemothorax results in severe pleural adhesion and thickening. Based on this idea, some reports described a successful treatment with autologous blood instillation for pneumothorax patients with or without residual pleural space. We tried pleurodesis with autologous bood for pneumothorax with persistent air leak and then we evaluated the efficacy and safety. Methods : Fifteen patients who had persistent air leak in the pneumothorax complicated from the severe chronic lung disease were enrolled. They were not good candidates for surgical treatment and doxycycline pleurodesis failed to stop up their air leaks. We used a mixture of autologous blood and 50% dextrose for pleurodesis. Effect and complications were assessed by clinical out∞me, chest radiography and pulmonary function tests. Results : The mean duration of air leak was 18.4${\pm}$6.16 days before ABP (autologous blood and dextrose pleurodesis) and $5.2{\pm}1.68$ days after ABP. The mean severity of pain was $2.3{\pm}0.70$ for DP(doxycycline pleurodesis) and $1.7{\pm}0.59$ for ABDP (p<0.05). There was no other complication except mild fever. Pleural adhesion grade was a mean of $0.6{\pm}0.63$. The mean dyspnea scale was $1.7{\pm}0.46$ before pneumothrax and $2.0{\pm}0.59$ after ABDP (p>0.05). The mean $FEV_1$ was $1.47{\pm}1.01$ before pneumothorax and $1.44{\pm}1.00$ after ABDP (p>0.05). Except in 1 patient, 14 patients had no recurrent pneumothorax. Conclusion : Autologous blood pleurodesis (ABP) was successful for treatment of persistent air leak in the pneumothorax. It was easy and inexpensive and involved less pain than doxycycline pleurodesis. It did not cause complications and severe pleural adhesion. We report that ABP can be considered as a useful treatment for persistent air leak in the pneumothorax complicated from the severe chronic lung disease.

• The Journal of Korean Academy of Prosthodontics
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• v.46 no.2
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• pp.125-136
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• 2008

Statement of problem: Since the concept of osseointegration in dental implants was introduced by $Br{{\aa}}nemark$ et al, high long-term success rates have been achieved. Though the use of dental implants have increased dramatically, there are few studies on domestic implants with clinical and objective long-term data. Purpose: The aim of this retrospective study was to provide long-term data on the $Neoplan^{(R)}$ implant, which features a sandblasted and acid-etched surface and external connection. Material and methods: 96 $Neoplan^{(R)}$ implants placed in 25 patients in Yonsei University Hospital were examined to determine the effect of the factors on marginal bone loss, through clinical and radiographic results during 18 to 57 month period. Results: 1. Out of a total of 96 implants placed in 25 patients, two fixtures were lost, resulting in 97.9% of cumulative survival rate. 2. Throughout the study period, the survival rates were 96.8% in the maxilla and 98.5% in the mandible. The survival rates were 97.6% in the posterior regions and 100% in the anterior regions. 3. The mean bone loss for the first year after prosthesis placement and the mean annual bone loss after the first year for men were significantly higher than that of women (P<0.05). 4. The group of partial edentulism with no posterior teeth distal to the implant prosthesis showed significantly more bone loss compared to the group of partial edentulism with presence of posterior teeth distal to the implant prosthesis in terms of mean bone loss for the first year and after the first year (P<0.05). 5. The mean annual bone loss after the first year was more pronounced in posterior regions compared to anterior regions (P<0.05). 6. No significant difference in marginal bone loss was found in the following factors: jaws, type of prostheses, type of opposing dentition, and submerged /non-submerged implants (P<0.05). Conclusion: On the basis of these results, the factors influencing marginal bone loss were gender, type of edentulism, and location in the arch, while the factors such as arch, type of prostheses, type of opposing dentition, submerged / non- submerged implants had no significant effect on bone loss. In the present study, the cumulative survival rate of the $Neoplan^{(R)}$ implant with a sandblasted and acid-etched surface was 97.9% up to a maximum 57-month period. Further long-term investigations for this type of implant system and evaluation of other various domestic implant systems are needed in future studies.

• Journal of the Korean Chemical Society
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• v.40 no.6
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• pp.427-435
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• 1996

The structures of fully dehydrated $Ca^{2+}$- and $Cs^+$-exchanged zeolite X, $Ca_{35}Cs_{22}Si_{100}Al_{92}O_{384}$($Ca_{35}Cs_{22}$-X; a=25.071(1) $\AA)$ and $Ca_{29}Cs_{34}Si_{100}Al_{92}O_{384}$($Ca_{29}Cs_{34}$-X; a=24.949(1) $\AA)$, have been determined by single-crystal X-ray diffraction methods in the cubic space group Fd3 at $21(1)^{\circ}C.$ Their structures were refined to the final error indices $R_1$=0.051 and $R_2$=0.044 with 322 reflections for $Ca_{35}Cs_{22}$-X, and $R_1$=0.058 and $R_2$=0.055 with 260 reflections for $Ca_{29}Cs_{34}$-X; $I>3\sigma(I).$ In both structures, $Ca^{2+}$ and $Cs^+$ ions are located at five different crystallographic sites. In dehydrated $Ca_{35}Cs_{22}$-X, sixteen $Ca^{2+}$ ions fill site I, at the centers of the double 6-rings(Ca-O=2.41(1) $\AA$ and $O-Ca-O=93.4(3)^{\circ}).$ Another nineteen $Ca^{2+}$ ions occupy site II (Ca-O=2.29(1) $\AA$, O-Ca-O=118.7(4)') and ten $Cs^+$ ions occupy site II opposite single six-rings in the supercage; each is $1.95\AA$ from the plane of three oxygens (Cs-O=2.99(1) and $O-Cs-O=82.3(3)^{\circ}).$ About three $Cs^+$ ions are found at site II', 2.27 $\AA$ into sodalite cavity from their three-oxygen plane (Cs-O=3.23(1) $\AA$ and $O-Cs-O=75.2(3)^{\circ}).$ The remaining nine $Cs^+$ ions are statistically distributed over site Ⅲ, a 48-fold equipoint in the supercages on twofold axes (Cs-O=3.25(1) $\AA$ and Cs-O=3.49(1) $\AA).$ In dehydrated $Ca_{29}Cs_{34}$-X, sixteen $Ca^{2+}$ ions fill site I(Ca-O=2.38(1) $\AA$ and $O-Ca-O=94.1(4)^{\circ})$ and thirteen $Ca^{2+}$ ions occupy site II (Ca-O=2.32(2) $\AA$, $O-Ca-O=119.7(6)^{\circ}).$ Another twelve $Cs^+$ ions occupy site II; each is $1.93\AA$ from the plane of three oxygens (Cs-O=3.02(1) and $O-Cs-O=83.1(4)^{\circ})$ and seven $Cs^+$ ions occupy site II'; each is $2.22\AA$ into sodalite cavity from their three-oxygen plane (Cs-O=3.21(2) and $O-Cs-O=77.2(4)^{\circ}).$ The remaining sixteen $Cs^+$ ions are found at III site in the supercage (Cs-O=3.11(1) $\AA$ and Cs-O=3.46(2) $\AA).$ It appears that $Ca^{2+}$ ions prefer sites I and II in that order, and that $Cs^+$ ions occupy the remaining sites, except that they are too large to be stable at site I.

• The Korean Journal of Air & Space Law and Policy
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• v.21 no.1
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• pp.215-236
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• 2006

This article focused on the meaning of the 1979 Moon Treaty and its future. Although the Moon Treaty is one of the major 5 space related treaties, it was accepted by only 11 member states which are non-space powers, thus having the least enfluences on the field of space law. And this article analysed the relationship between the 1979 Moon Treay and 1967 Space Treaty which was the first principle treaty, and searched the meaning of the "Common Heritage of Mankind(hereinafter CHM)" stipulated in the Moon treaty in terms of international law. This article also dealt with the present and future problems arising from the Moon Treaty. As far as the 1967 Space Treaty is concerned the main standpoint is that outer space including the moon and the other celestial bodies is res extra commercium, areas not subject to national appropriation like high seas. It proclaims the principle non-appropriation concerning the celestial bodies in outer space. But the concept of CHM stipulated in the Moon Treaty created an entirely new category of territory in international law. This concept basically conveys the idea that the management, exploitation and distribution of natural resources of the area in question are matters to be decided by the international community and are not to be left to the initiative and discretion of individual states or their nationals. Similar provision is found in the 1982 Law of the Sea Convention that operates the International Sea-bed Authority created by the concept of CHM. According to the Moon Treaty international regime will be established as the exploitation of the natural resources of the celestial bodies other than the Earth is about to become feasible. Before the establishment of an international regime we could imagine moratorium upon the expoitation of the natural resources on the celestial bodies. But the drafting history of the Moon Treaty indicates that no moratorium on the exploitation of natural resources was intended prior to the setting up of the international regime. So each State Party could exploit the natural resources bearing in mind that those resouces are CHM. In this respect it would be better for Korea, now not a party to the Moon Treaty, to be a member state in the near future. According to the Moon Treaty the efforts of those countries which have contributed either directly or indirectly the exploitation of the moon shall be given special consideration. The Moon Treaty, which although is criticised by some space law experts represents a solid basis upon which further space exploration can continue, shows the expression of the common collective wisdom of all member States of the United Nations and responds the needs and possibilities of those that have already their technologies into outer space.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.