• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.11-24
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• 2001

The interpretation of noun sequence is to find semantic relation between the nouns in noun sequence. To interpret noun sequence, semantic knowledge about words and relation between words is required. In this thesis, we propose a method to interpret a semantic relation between nouns in noun sequence. We extract semantic information from an machine readable dictionary (MRD) and corpus using regular expressions. Based on the extracted information, semantic relation of noun sequence is interpreted. And. we use verb subcategorization information together with the semantic information from an MRD and corpus. Previous researches use semantic knowledge extracted only from an MRD but our method uses an MRD. corpus. and subcategorizaton information to interpret noun sequences. Experimental result shows that our method improves the accuracy rate by +40.30% and the coverage rate by + 12.73% better than previous researches.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.2
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• pp.110-125
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• 2010

We present a novel scheme for generating line drawings from 2D images, aiming to facilitate effective visual communication. In contrast to conventional edge detectors, our technique imitates the human line drawing process to generate lines effectively and intuitively. Our technique consists of three parts: line extraction, line rendering, and user guidance. In line extraction, we extract lines by estimating a likelihood function to effectively find the genuine shape boundaries. In line rendering, we consider the feature scale and the blurriness of lines with which the detail and the focus-level of lines are controlled. We also employ stroke textures to provide a variety of illustration styles. User guidance is allowed to modify the shapes and positions of lines interactively, where immediate response is provided by GPU implementation of most line extraction operations. Experimental results demonstrate that our technique generates various kinds of line drawings from 2D images enabled by the control over detail, focus, and style.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.547-552
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• 2014

As social multimedia sites are getting popular such as Flickr and Facebook, the amount of image information has been increasing very fast. So there have been many studies for accurate social image retrieval. Some of them were web image classification using semantic relations of image tags and BoVW(Bag of Visual Words). In this paper, we propose a method to detect salient region in images using GBVS(Graph Based Visual Saliency) model which can eliminate less important region like a background. First, We construct BoVW based on SIFT algorithm from the database of the preliminary retrieved images with semantically related tags. Second, detect salient region in test images using GBVS model. The result of image classification showed higher accuracy than the previous research. Therefore we expect that our method can classify a variety of images more accurately.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.439-446
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• 2005

XML is the standard that can manage systematically WWW documents and increase retrieval efficiency. Because XML documents have the information of contents and that of structure in single document, users can get more suitable retrieval result by retrieving the information of content as well as that of logical structure. In this paper, we will propose a method to calculate the weights of XML tags so that the information of XML tag is used to index decision. A proposed method creates term vector and weight vector for XML tags, and calculates weight of tag by reflecting user's retrieval behavior (user's query). And it decides the weights of index terms of XML document by reflecting the weights of tags. And we will perform an evaluation of proposed method by comparison with existing researches using weights of paragraphs.

• Annual Conference of KIPS
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• 2003.11b
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• pp.853-856
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• 2003

바이오 텍스트 마이닝을 위한 정보 추출의 첫 단계는 생물학적 문헌으로부터의 유전자, 단백질, 세포조직 등과 같은 생물학적 개체명의 인식이다. 생물학적 개체명의 명명법상 특징이 매우 다양하고 저자의 개성에 의해 쉽게 좌우되어 단순히 규칙이나 학습 방법 만으로는 쉽게 개체명들을 인식할 수 없다. 또한, 생물학 관련 문헌에 나오는 가능한 모든 개체명과 이들의 모든 변형을 수록하는 것은 현실적으로 불가능하므로 이를 해결하기 위해 이미 알려진 개체명에 대해서 기본적으로 사전을 탐색하고 알려지지 않은 용어들을 규칙과 통계 기반 방법을 통하여 인식하는 것이 효과적이다. 그러나 만족할 만한 수준의 양질의 사전을 구축하는 것은 쉽지 않을 뿐만 아니라 많은 비용이 소요되며, 어느 순간 만족할 만한 성능을 낼 수 있는 사전을 구축했다. 할지라도 유지 관리 하는 것이 결코 쉬운 일이 아니며 마찬가지로 많은 비용을 필요로 하게 된다. 따라서, 잘 구축된 자원으로부터 필요한 정보를 추출하여 적절한 사전을 자동으로 구축하여 활용하는 방법을 사용할 경우, 사전 구축 및 관리에 드는 많은 비용을 줄이면서도 상당히 효과적인 성능을 얻을 수 있을 것이다. 본 연구에서는 바이오 텍스트 마이닝 엔진을 위한 생물학적 개체명 사전을 자동으로 구축하고 이를 쉽게 관리하도록 하는 도구를 개발하였다.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.343-356
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• 2011

When preparing test cases and running the test the existing GUI test tools require many tester's interventions. To cope with such problem this paper suggests a new method to build test cases for GUI test. This method identifies the potential control flows within the GUI and constructs the GUI map. The UIA library in .NET Framework is used to extract information about the GUI controls and the GUI map is constructed by the extracted information. Test scenarios are generated from the extracted information about the GUI controls using the grouping mechanism. Based on the grouping mechanism, various test scenarios which are test cases in GUI tests can be made by replacing a GUI control by another one in the same group. The existing GUI test tools do not support the concept of test coverage. Since, however, our method survey which part of the GUI map is executed or not during running the test, the test coverage can be measured by using the GUI map.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2101-2108
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• 2014

Automatic fall-detection algorithms using video-data are proposed. Six types of fall-feature parameters are defined applying the optical flows extracted from differential images to principal component analysis(PCA). One fall-detection algorithm is the simple threshold method that a fall is detected when a fall-feature parameter is over a threshold, another is to use the HMM, and the other is to combine the simple threshold and HMM. Comparing the performances of three types of fall-detection algorithm, the algorithm combining the simple threshold and HMM requires less computational resources than HMM and exhibits a higher accuracy than the simple threshold method.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.9-17
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• 2021

Humans are social animals that have gained information or social interaction through dialogue. In conversation, the mood of the word can change depending on the sensibility of one person to another. Relationships between characters in films are essential for understanding stories and lines between characters, but methods to extract this information from films have not been investigated. Therefore, we need a model that automatically analyzes the relationship aspects in the movie. In this paper, we propose a method to analyze the relationship between characters in the movie by utilizing deep learning techniques to measure the emotion of each character pair. The proposed method first extracts main characters from the movie script and finds the dialogue between the main characters. Then, to analyze the relationship between the main characters, it performs a sentiment analysis, weights them according to the positions of the metabolites in the entire time intervals and gathers their scores. Experimental results with real data sets demonstrate that the proposed scheme is able to effectively measure the emotional relationship between the main characters.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.81-87
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• 2018

In this paper, in order to maximize the input process efficiency of the building energy simulation field, the authors developed the automatic extraction module of spatial information based BIM geometry information. Existing research or software extracts geometry information based on object information, but it can not be used in the field of energy simulation because it is inconsistent with the geometry information of the object constituting the thermal zone of the actual building model. Especially, IFC-based geometry information extraction module is needed to link with other architectural fields from the viewpoint of reuse of building information. The study method is as follows. (1) Grasp the category and attribute information to be extracted for energy simulation and Analyze the IFC structure based on spatial information (2) Design the algorithm for extracting and reprocessing information for energy simulation from IFC file (use programming language Phython) (3) Develop the module that generates a geometry information database based on spatial information using reprocessed information (4) Verify the accuracy of the development module. In this paper, the reprocessed information can be directly used for energy simulation and it can be widely used regardless of the kind of energy simulation software because it is provided in database format. Therefore, it is expected that the energy simulation process efficiency in actual practice can be maximized.