• The KIPS Transactions:PartD
• /
• v.10D no.3
• /
• pp.459-470
• /
• 2003

It is required to research on high-dimensional index structures for efficiently retrieving high-dimensional data because an attribute vector in data warehousing and a feature vector in multimedia database have a characteristic of high-dimensional data. For this, many high-dimensional index structures have been proposed, but they have so called ‘dimensional curse’ problem that retrieval performance is extremely decreased as the dimensionality is increased. To solve the problem, the cell-based filtering (CBF) scheme has been proposed. But the CBF scheme show a linear decreasing on performance as the dimensionality. To cope with the problem, it is necessary to make use of parallel processing techniques. In this paper, we propose a parallel CBF scheme which uses a horizontally-partitioned technique as declustering. In order to maximize the retrieval performance of the proposed parallel CBF scheme, we construct our parallel CBF scheme under a SN (Shared Nothing) cluster architecture. In addition, we present a data insertion algorithm, a rage query processing one, and a k-NN query processing one which are suitable for the SN cluster architecture. Finally, we show that our parallel CBF scheme achieves better retrieval performance in proportion to the number of servers in the SN cluster architecture, compared with the conventional CBF scheme.

• The Journal of the Korea Contents Association
• /
• v.14 no.1
• /
• pp.364-373
• /
• 2014

The relationship between a service provided via the information system and user satisfaction has been thought of as an important factor for the development of a new service for the information system. In this study, the twelve new key services that are applicable to national R&D report system were derived by web environment changes in step with IT technology developments in order to support the new service for the user. The twelve new key services are as follows; semantic search service for national R&D report, associated report service, RSS service, mesh-up service, topic-map service, open API service, personalized service, collective intelligence service, SNS service, unstructured data service, detailed search service, mailing service. To assess the quality attribute of the twelve new key services in the national R&D report system, a survey was performed. In conclusion, a stepwise service plan for the national R&D report system was proposed which would use the satisfaction coefficient and the results of the service classification. The following step-by-step service should be developed by in this way. The unstructured data service, personalized service, associated report service, topic-map service, open API service, and the collective intelligence service are needed to develop the first step and RSS service, mesh-up service, semantic search service for the national R&D report, mailing service, detailed search service, and SNS service are needed to develop the second step.

• Journal of Distribution Science
• /
• v.12 no.2
• /
• pp.49-57
• /
• 2014

Purpose - Theorists and researchers in the area of customer satisfaction generally agree that product satisfaction intervenes between expectancy disconfirmation and various post-purchase cognitive states including attitude and behavioral intention. Studies in a variety of settings have supported the effect of expectation and its disconfirmation on satisfaction, but only a small number of studies address the cognitive consequences of satisfaction decisions and none report data on choice processes such as brand selection. This study examines the influence of satisfaction and its determinants on behavioral intention and product preference in eight coffee shops across the country. Generally it was found in both overall and summed attribute analyses that satisfaction was a function of expectation and disconfirmation, that intention was a function of satisfaction, and that preference was influenced by satisfaction and disconfirmation, the latter having the greater effect. Research design, data, and methodology - The main objective of this study was to assess the dimensions of consumer selection and satisfaction in choosing a coffee shop. In order to achieve this objective, a study of coffee shops across the country was conducted. This study comprised in-depth questionnaires distributed to coffee shop customers. A survey was conducted from September 1, 2011 to September 30, 2011, involving franchise coffee shop, independently owned coffee shop, and roastery coffee shop customers. Results - Hypothesis 1-1, which states that coffee shop choice attributes differ based on the type of coffee shop, is accepted. It has a significance level of 0.05, according to choosing properties of coffee shop by convenience of transportation, varieties of beans, residence of the owner (manager), information, and relationships. Hypothesis 1-2, which states that satisfaction with the choice factor differs depending on the type of coffee shops, is accepted. The P-values for cleanliness and varieties of beans were 0.04 and 0.00, respectively, and have a significance level of 0.05, according to the satisfaction with the chosen coffee shop. Hypothesis 2-1, which states that the importance of the choice attributes in coffee shop selections differs based on the demographic characteristics of the customers, is accepted. According to the t-test result, convenience of parking and residence of the owner (manager) are significant. Hypothesis 2-2, which states that satisfaction with the choice factor will differ depending of the type of coffee shop, is accepted. According to the t-test result, convenience of parking and residence of the owner (manager) are significant. Conclusions - This study has shown that intention to revisit a certain shop is most likely correlated to satisfaction in all cases. In order to offer subsequent developments for coffee shops, this study also identifies relations between customer satisfaction and selection by finding significant factors. In order to maximize customers' satisfaction, coffee shops should analyze and satisfy customers' needs and wants in terms of coffee service. While the findings do not generalize beyond the mall sampling procedure used here, we have hopefully identified a close approximation of the process of satisfaction decisions used by consumers generally.

• Journal of KIISE:Software and Applications
• /
• v.33 no.4
• /
• pp.365-377
• /
• 2006

Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein interaction is intrinsic to most cellular processes, prediction of protein interaction is an important issue in post-genomic biology where abundant interaction data have been produced by many research groups. In this paper, we present an associative feature mining method to predict implicit protein-protein interactions of Saccharomyces cerevisiae from public protein interaction data. We discretized continuous-valued features by maximal interdependence-based discretization approach. We also employed feature dimension reduction filter (FDRF) method which is based on the information theory to select optimal informative features, to boost prediction accuracy and overall mining speed, and to overcome the dimensionality problem of conventional data mining approaches. We used association rule discovery algorithm for associative feature and rule mining to predict protein interaction. Using the discovered associative feature we predicted implicit protein interactions which have not been observed in training data. According to the experimental results, the proposed method accomplished about 96.5% prediction accuracy with reduced computation time which is about 29.4% faster than conventional method with no feature filter in association rule mining.

• Journal of the Korean Society for information Management
• /
• v.34 no.1
• /
• pp.51-71
• /
• 2017

This study conducted a survey to measure recognition distance between the materials which are located separately in a children's library targeting 200 elementary school lower grade students, higher grade students, and school parents(adults). And compared recognition distance between the elements of materials of individual visitor group with multidimensional scaling and K-mean group analysis. Multidimensional Scaling (MDS) is a technique for projecting the cognitive state in space by evaluating the similarity or attribute of the analysis target. Even though it is mainly used for market diagnosis in marketing, It can also be applied to present an ideal physical layout plan by analyzing the distance. As a result of analysis, the main discoveries are as follows. First, elementary school students cognize child, baby and computer materials should be adjacent as a same group. But recognition of adults(school parents) is reflected by differing from elementary school students vastly. They cognize that computer materials should be formed as a special group separated from child and baby's materials. Second, elementary school higher graders and adults(school parents) groups also want to separate their main reading materials from baby's book, therefore They both want to secure silent reading space separating from baby. Third, as a result to confirming how this recognition distance system of materials is reflected in a real children's library through three children's libraries in Y-gu, Incheon, there is no library with structure according perfectly with a recognition system of a particular class, but a recognition system of adults and elementary school students is partially reflected because baby, child and computer materials, and baby and child materials are commonly separated and placed. It is difficult to insist that a recognition system of a visitor group, especially a recognition system of children is absolute consideration conditions in material placement of a children's library. However, understanding cognition of the user groups can be an important evidentiary factors to offer differentiated service space according to visitors and effective placement of the elements of library resources.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.9 no.2
• /
• pp.194-205
• /
• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

• Management & Information Systems Review
• /
• v.33 no.5
• /
• pp.1-34
• /
• 2014

This study suggests internal and external virtuous behavior in organization influenced employees' organizational citizenship behavior (OCB), organizational loyalty and emotional exhaustion through mediated effect of affective commitment and collective self-esteem. Virtue in organization has received attention as critical attribute of positive organizational scholarship. Cameron(2003) defined the study of virtue as a study of the capacity, attributes, and reserve in organization that facilitates the expression of positive deviance among organization member. Accordingly, this study presumed that virtuous behaviors within organization positively associate with OCB, and organizational loyalty through affective commitment whereas the virtuous behaviors negatively influence emotional exhaustion. On the other hand, we assumed that external virtuous behaviors positively associate with OCB and organizational loyalty and negatively associate with emotional exhaustion individually. In study 1, we conducted interview with Korean employees created items for internal and external virtue, and implemented empirical study for 253 employees of domestic companies in study 2. This study contributes to the empirical investigation on how internal virtue (i.e. the employees' virtue for their organization) and external virtue (i.e. the organization's virtue for society), used as independent variables, influence employees' organizational citizenship behavior (OCB), organizational loyalty and emotional exhaustion after creating items for the two virtuous behaviors through qualitative research.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.5 no.3
• /
• pp.47-68
• /
• 2010

In this study, a unit of regional tourism as a cluster of innovative strategies that can be an assumption that the activation of tourism clusters building on local festivals and participated to review the empirical aims. The purpose of this study was to achieve literature and empirical research were given recognition for the cultural festival in Chungnam, Chungcheong-do you want to go to the local cultural festival linked to the tourist attractions, the cluster characteristics, participation motives, the festival satisfaction, revisit the decision, recommendation of the The analysis was carried out degrees. To this end, local cultural festivals and attractions, Chungnam 150 spectators in the survey was conducted, the statistical analysis using SAS 9 statistical package program was analyzed. Used for statistical analysis, frequency analysis, factor analysis, reliability analysis, multiple regression analysis. Festival of the cluster attribute satisfaction and revisit four on the most direct impact on the competitive conditions were not. Festival in regard to motivation and satisfaction with intrinsic motivation, extrinsic motivation in returning to the doctor more were affected. The condition is the element intrinsic motivation, extrinsic motivation is a race condition was the biggest influence. Therefore, the element condition Satisfaction Festival, a race condition in four to revisit the biggest indirect impact can be seen.

• The KIPS Transactions:PartB
• /
• v.16B no.3
• /
• pp.225-232
• /
• 2009

Author name disambiguation is essential for improving performance of document indexing, retrieval, and web search. Author name disambiguation resolves the conflict when multiple authors share the same name label. This paper introduces a novel approach which exploits ontologies and WordNet-based category utility for author name disambiguation. Our method utilizes author knowledge in the form of populated ontology that uses various types of properties: titles, abstracts and co-authors of papers and authors' affiliation. Author ontology has been constructed in the artificial intelligence and semantic web areas semi-automatically using OWL API and heuristics. Author name disambiguation determines the correct author from various candidate authors in the populated author ontology. Candidate authors are evaluated using proposed WordNet-based category utility to resolve disambiguation. Category utility is a tradeoff between intra-class similarity and inter-class dissimilarity of author instances, where author instances are described in terms of attribute-value pairs. WordNet-based category utility has been proposed to exploit concept information in WordNet for semantic analysis for disambiguation. Experiments using the WordNet-based category utility increase the number of disambiguation by about 10% compared with that of category utility, and increase the overall amount of accuracy by around 98%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.24 no.5
• /
• pp.417-424
• /
• 2006

Despite of many researches related to create 3D digital maps, it is still time-consuming and costly because a large part of 3D digital mapping is conducted manually. To circumvent this limitation, we proposed methodologies to create 3D digital maps with 3D symbols automatically. For this purpose, firstly, the 3D symbol library to represent 3D objects as 3D symbols was constructed. In this library, we stored the attribute and geometry information of 3D objects which define types and shapes of symbols respectively. These information were used to match 3D objects with 3D symbols and extracted from 2D digital maps and LiDAR(Light Detection and Ranging) data. Then, to locate 3D symbols into a base map automatically, we used predefined parameters such as the size, the height, the rotation angle and the center of gravity of 3D objects which are extracted from LiDAR data. Finally, the 3D digital map in urban area was constructed and the results were tested. Through this research, we can identify that the developed algorithms can be used as effective techniques for 3D digital mapping.