• Journal of Information Management
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• v.35 no.4
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• pp.81-105
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• 2004

In this study, the way of the automatic text categorization on web-based query was implemented. X2 methods based on the Supported Vector Machine were used to test the efficiency of text categorization on queries. This test is carried out by the model using the Synonymy List. 713 synonyms were extracted manually from the tested documents. As the result of this test, the precision ratio and the recall ratio were decreased by -0.01% and by 8.53%, respectively whether the synonyms were assigned or not. It also shows that the Value of F1 Measure was increased by 4.58%. The standard deviation between the recall and precision ratio was improve by 18.39%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.535-540
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• 2006

This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.8 no.1
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• pp.197-227
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• 1997

The main purpose of this study is ① to settle and to analyze the classification of the Internet Search Engine comparitively, and ② to build the compatible model of Internet Search Engine classification in order to seek information on the Internet resources. specially in the branch of the Computers and Internet areas. For this study, four Internet Search Engine (Excite, 1-Detect, Simmany, Yahoo Korea!), Inspec Classification and two distionaries were used. The major findings and result of analysis are summarized as follows : 1. The basis of the classification is the scope of topics, the system logic, the clearness, the efficiency. 2. The scope of topics is analyzed comparitively by the number of items from each Search Engine. In the result, Excite is the most superior of the four 3. The system logic is analyzed comparitively by the casuality balance and consistency of the items from each Search Engine. In the result, Excite is the most superior of the four 4. The clearness is analyzed comparitively by the clearness and accuracy of items, the recognition of the searchers. In the result, Excite is the most superior of the four. 5 The efficiency is analyzed comparitively by the exactness of indexing and decreasing the effort of the searchers. In the result, Yahoo Korea！ is the most superior of the four. 6 The compatible model of Internet Search Engine classification is estavlished to uplift the scope of topics, the system logic, the clearness, and the efficiency. The model divides the area mainly based upon the topics and resources using‘bookmark’and‘shadow’concept.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.27-32
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• 2004

A XML Document has a structure which may be irregular The irregular document structure is difficult for users to know exactly. In this paper, we propose the XML document model and the structure retrieval method for efficient management and structure retrieval of XML documents. So we use fixed-sized LETID having the information of element, describe the structured information retrieval algorithm for parent and child element to represent the structured information of XML documents. Using this method, we represent the structured information of XML document efficiently. We can directly access to specific clement by simple operation, and process various queries. We expect the method to support various structured retrieval of specific element such as parent, child. and sibling elements.

• Journal of Integrative Natural Science
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• v.2 no.4
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• pp.243-251
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• 2009

This paper surveys some researches to accomplish on bioinformatics. These researches wish to propose a database architecture combining a general view of bioinformatics data as a graph of data objects and data relationships, with the efficiency and robustness of data management and query provided by indexing and generic programming techniques. Here, these invert the role of the index, and make it a first-class citizen in the query language. It is possible to do this in a structured way, allowing users to mention indexes explicitly without yielding to a procedural query model, by converting functional relations into explicit functions. In the limit, the database becomes a graph, in which the edges are these indexes. Function composition can be specified either explicitly or implicitly as path queries. The net effect of the inversion is to convert the database into a hyperdatabase: a database of databases, connected by indexes or functions. The inversion approach was motivated by their work in biological databases, for which hyperdatabases are a good model. The need for a good model has slowed progress in bioinformatics.

• ETRI Journal
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• v.44 no.3
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• pp.413-425
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• 2022

The study of literary texts is one of the earliest disciplines practiced around the globe. Poetry is artistic writing in which words are carefully chosen and arranged for their meaning, sound, and rhythm. Poetry usually has a broad and profound sense that makes it difficult to be interpreted even by humans. The essence of poetry is Rasa, which signifies mood or emotion. In this paper, we propose a poetry classification-based approach to automatically extract similar poems from a repository. Specifically, we perform a novel Rasa-based classification of Hindi poetry. For the task, we primarily used lexical features in a bag-of-words model trained using the support vector machine classifier. In the model, we employed Hindi WordNet, Latent Semantic Indexing, and Word2Vec-based neural word embedding. To extract the rich feature vectors, we prepared a repository containing 37 717 poems collected from various sources. We evaluated the performance of the system on a manually constructed dataset containing 945 Hindi poems. Experimental results demonstrated that the proposed model attained satisfactory performance.

• Korean Journal Plant Pathology
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• v.3 no.3
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• pp.210-216
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• 1987

A computer program written to predict blast occurrence based on micro climatic events was developed and tested as an on-site microcomputer in field plots in 1984 and 1985. A microcomputer unit operating on alkaline batteries; continuously monitored air temperature, leaf wetness, and relative humidity; interpreted the microclimate information in relation to rice blast development and displayed daily values (0-8) of blast units of severity (BUS). Cumulative daily BUS values (CBUS) were highly correlated with blast development on the two susceptible cultivars, M-201 and Brazos grown in field plots. When CBUS values were used to predict the logit of disease proportions, the average coefficients of determination $(R^2)$ between these two factors were 71 to $91\%$, depending on cultivar and year. This was a significant improvement when compared to 61 to $79\%$ when days were used as a predictor of logit disease severity. The ability of CBUS to predict logit disease severity was slightly less with Brazos than M-201. This is significant inasmuch as Brazos showed field resistance at mid-sea­son. The results in this study indicate that the model has the potential for future use and that the model could be improved by incorporating other variables associated with host plants and pathogen races in addition to the key environmental variables.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.111-119
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• 2011

The noise prediction model, KRON-2006, in South Korea has been developed for obtaining the average noise level. The model is based on an outdoor sound propagation method based on ISO9613 and ASJ Model-1998 and supports the analysis of the linear noise source, such as highway, for obtaining Leq. Because of that, the model can't obtain Lmax, Lmin from the time series noise profile based on traffic at every moment. In order to address this problem, the real time noise prediction model based on traffic simulation using GIS model and algorithm is proposed. It can predict the vehicle point noise level based on vehicle type, speed generated from traffic simulation by using headway and obtain Lmax, Lmin as integrating the noise profile generated from it at every moment. An evalution of the noise prediciton model using field measurements finds good agreement between predicted and measured noise levels at 1m, 8m, 15m from curb of the near side lane.

• Journal of Korean Library and Information Science Society
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• v.38 no.4
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• pp.463-480
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• 2007

This study examines the design and utilization of video storyboard surrogates in the digital video libraries. To do this, first we constructed the arrangement model of key-frames for storyboard based on the FRBR model, image communication and PRECIS Indexing theories and evaluated the model using 6 sample videos and 26 participants. The study results show that the video storyboard surrogates based on the arrangement model has a higher accuracy value in terms of summary extraction than that of the sequential video storyboard. Moreover, watching both types of video storyboard one after another, especially browsing the sequential video storyboard first and then the arrangement model-based one, produces a remarkable increase in accuracy value of summary extraction. The study proposes two methods of utilizing the video storyboard surrogates in the digital video libraries: Designing a video browsing interface where users can use the sequential storyboard as a default and then the arrangement model-based one for re-watching; and utilizing the arrangement model-based storyboard as structured match sources of image-based queries.

• International Journal of Contents
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• v.14 no.1
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• pp.1-6
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• 2018

Text, as one of the most influential inventions of humanity, has played an important role in human life since ancient times. The rich and precise information embodied in text is very useful in a wide range of vision-based applications such as the text data extracted from images that can provide information for automatic annotation, indexing, language translation, and the assistance systems for impaired persons. Therefore, natural-scene text detection with active research topics regarding computer vision and document analysis is very important. Previous methods have poor performances due to numerous false-positive and true-negative regions. In this paper, a fully-convolutional-network (FCN)-based method that uses supervised architecture is used to localize textual regions. The model was trained directly using images wherein pixel values were used as inputs and binary ground truth was used as label. The method was evaluated using ICDAR-2013 dataset and proved to be comparable to other feature-based methods. It could expedite research on text detection using deep-learning based approach in the future.