• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.745-751
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• 2004

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM(Max and Min Model), Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly In this paper we propose a new soft evaluation method for web Information retrieval using local context analysis feedback model. We also show through performance comparison that local contort analysis feedback is more efficient and effective than MMM, Paice and P-norm.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.659-665
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• 2001

Relevance feedback is the most popular query reformulation strategy in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.9-14
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• 2002

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.179-187
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• 1999

Purpose : This paper introduces a computationally inexpensive context-dependent classification of multi-echo MRI with Bayes compound decision model. In order to produce accurate region segmentation especially in homogeneous area and along boundaries of the regions, we propose a classification method that uses contextual information of local enighborhood system in the image. Material and Methods : The performance of the context free classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at he local neighborhood level. In order to improve the classification accuracy, we use the contextual information which resolves ambiguities in the class assignment of a pattern based on the labels of the neighboring patterns in classifying the image. Since the data immediately surrounding a given pixel is intimately associated with this given pixel., then if the true nature of the surrounding pixel is known this can be used to extract the true nature of the given pixel. The proposed context-dependent compound decision model uses the compound Bayes decision rule with the contextual information. As for the contextual information in the model, the directional transition probabilities estimated from the local neighborhood system are used for the interaction parameters. Results : The context-dependent classification paradigm with compound Bayesian model for multi-echo MR images is developed. Compared to context free classification which does not consider contextual information, context-dependent classifier show improved classification results especially in homogeneous and along boundaries of regions since contextual information is used during the classification. Conclusion : We introduce a new paradigm to classify multi-echo MRI using clustering analysis and Bayesian compound decision model to improve the classification results.

• Journal of Information Management
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• v.38 no.3
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• pp.59-80
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• 2007

In this study, we analyzed the web site navigation of law school libraries in terms of global, local, context, support navigation. The recommendations for good web site design were as follows. First, global navigation should provide the consistent navigation and be able to access to the important site and function. Second, quick links of local navigation need to provide the movement of scroll bar. The number of menu and type of link in context navigation should provide the least number. Finally, the site map and index should provide with qualified contents and minimal errors.

• Korean Journal of English Language and Linguistics
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• v.3 no.1
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• pp.55-88
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• 2003

In this paper, I will review two main theories on presupposition projection and point out their problems, and suggest the directions of a better analysis. Satisfaction theory is based on the single idea that presuppositions must be satisfied in the local context for the interpretation of a sentence. Problems occur because the theory makes only a minimal requirement on the input context for interpretation. They include the problems of weak presuppositions, unmotivated local accommodation, and projection of satisfied presuppositions. Binding theory assumes that presuppositions are anaphoric elements which can be accommodated. I will show that the syntactic notion of binding is not motivated, and claim that presupposition projection is a matter of information. Finally, I suggest the directions for a better analysis.

• Journal of Korean Society for Quality Management
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• v.37 no.1
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• pp.1-9
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• 2009

Data envelopment analysis(DEA) has proved to be powerful for benchmarking and has been widely used in a variety of settings since the advent of it. DEA can be used in identifying the best performing units to be benchmarked against as well as in providing actionable measure for improvement of a organization's performance. However, the selection of performance benchmarks is a matter of both technical production possibilities and organizational policy considerations, managerial preferences and external restrictions. In that regards, DEA has a limited value in benchmarking because it focuses on only technical production Possibilities. This research proposes a new perspective in using DEA and a frame-work for benchmarking to select benchmarks that are both feasible and desirable in terms of organizational context. To do this, the concept of local and global efficiency is newly proposed. To show how useful the suggested concept and framework are, a case study is addressed.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.109-136
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• 2009

This study investigates English medium instruction (EMI) in an institution of higher education in Seoul, Korea to see whether this course creates cultural correction (reproduction of inequitable relations of power in EMI settings) or cultural continuity (opportunities for transporting students into a third space and enabling them to explore cultural diversity and to create new knowledge for themselves). A single site where EMI is carried out, a class on fairy tales and child education taught by a native English speaking professor, was chosen because it was hypothesized that the professor would display some of her unconscious dominant cultural orientation. The results of the study show that there more cases of cultural correction than there were of cultural continuity. Cases of cultural correction included lack of knowledge about the local context, fixing Korean classroom discourse as if it were American classroom discourse, and reproducing orientalism in the local educational setting. Cases of cultural continuity included using comparison to consider the cultural reality of the milieu, creating new knowledge for the local milieu, and learning as a dynamic ongoing process. Implications of this research are discussed including the important realization that EMI should be managed by subject specialists who are trained in language education and have knowledge of the students' needs and discourse in the L1 and in the local context.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1282-1290
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• 2017

Since the mitigation of fear of crime significantly enhances the consumptions in a city, studies focusing on urban safety analysis have received much attention as means of revitalizing the local economy. In addition, with the development of computer vision and machine learning technologies, efficient and automated analysis methods have been developed. Previous studies have used global features to predict the safety of cities, yet this method has limited ability in accurately predicting abstract information such as safety assessments. Therefore we used a Convolutional Context Neural Network (CCNN) that considered "context" as a decision criterion to accurately predict safety of cities. CCNN model is constructed by combining a stacked auto encoder with a fully connected network to find the context and use it in the CNN model to predict the score. We analyzed the RMSE and correlation of SVR, Alexnet, and Sharing models to compare with the performance of CCNN model. Our results indicate that our model has much better RMSE and Pearson/Spearman correlation coefficient.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.3
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• pp.9-18
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• 2014

Small and medium-sized local airports have suffered from chronic operating deficits due to many factors except for large airports in Incheon, Gimpo, Jeju and Gimhae. These small and medium-sized local airports have currently been degraded to inefficient airports handling the significantly lower airline demand than their carrying capacities. In this context, this study conducted a survey on the actual conditions of the airline demand in small and medium-sized local airports for the last 10 years after the opening of the Korea Train eXpress and investigated the causes and actual conditions of an increase and a decrease in the airline demand. In addition, it analyzed the functionality, convenience and economic feasibility, competition elements in comparison with other means of transportation, and the actual competitive conditions of local airports. It investigated facility improvements through a field visit for local airports and analyzed the performance rate of passenger demands and the use rate of terminal facilities according to a change in the airline demand. This study aimed to provide basic data in the architectural planning field, needed to establish a plan for the airport revitalization of local airports with the results of an analysis on the actual conditions of small and medium-sized local airports.