• Journal of KIISE:Software and Applications
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• v.28 no.5
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• pp.389-401
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• 2001

This paper proposes an abstraction mechanism of the low-level digital video features for the automatic retrievals of the explosion scenes from the digital video library. In the proposed abstraction mechanism, the regional dominant colors of the key frame and the motion energy of the shot are defined as the primary abstractions of the shot for the explosion scene retrievals. It is because an explosion shot usually consists of the frames with a yellow-tone pixel and the objects in the shot are moved rapidly. The regional dominant colors of shot are selected by dividing its key frame image into several regions and extracting their regional dominant colors, and the motion energy of the shot is defined as the edge image differences between key frame and its neighboring frame. The edge image of the key frame makes the retrieval of the explosion scene more precisely, because the flames usually veils all other objects in the shot so that the edge image of the key frame comes to be simple enough in the explosion shot. The proposed automatic retrieval algorithm declares an explosion scene if it has a shot with a yellow regional dominant color and its motion energy is several times higher than the average motion energy of the shots in that scene. The edge image of the key frame is also used to filter out the false detection. Upon the extensive exporimental results, we could argue that the recall and precision of the proposed abstraction and detecting algorithm are about 0.8, and also found that they are not sensitive to the thresholds. This abstraction mechanism could be used to summarize the long action videos, and extract a high level semantic information from digital video archive.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.116-121
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• 2017

cQA(Community-based Question Answering) 시스템은 온라인 커뮤니티를 통해 사용자들이 질문을 남기고 답변을 작성할 수 있도록 만들어진 시스템이다. 신규 질문이 인입되면, 기존에 축적된 cQA 저장소에서 해당 질문과 가장 유사한 질문을 검색하고, 그 질문에 대한 답변을 신규 질문에 대한 답변으로 대체할 수 있다. 하지만, 키워드 매칭을 사용하는 전통적인 검색 방식으로는 문장에 내재된 의미들을 이용할 수 없다는 한계가 있다. 이를 극복하기 위해서는 의미적으로 동일한 문장들로 학습이 되어야 하지만, 이러한 데이터를 대량으로 확보하기에는 어려움이 있다. 본 논문에서는 질문이 제목과 내용으로 분리되어 있는 대량의 cQA 셋에서, 질문 제목과 내용을 의미 벡터 공간으로 사상하고 두 벡터의 상대적 거리가 가깝게 되도록 학습함으로써 의사(pseudo) 유사 의미의 성질을 내재화 하였다. 또한, 질문 제목과 내용의 의미 벡터 표현(representation)을 위하여, semi-training word embedding과 CNN(Convolutional Neural Network)을 이용한 딥러닝 기법을 제안하였다. 유사 질문 검색 실험 결과, 제안 모델을 이용한 검색이 키워드 매칭 기반 검색보다 좋은 성능을 보였다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.285-291
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• 2001

This paper describes a natural language question answering system that can be used by students in getting as solution to their queries. Unlike AI question answering system that focus on the generation of new answers, the present system retrieves existing ones from question-answer files. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, it uses a semantic knowledge base (WordNet) to improve its ability to match question. Paper describes the design and the current implementation of the system as an intelligent tutoring system. Main drawback of the existing tutoring systems is that the computer poses a question to the students and guides them in reaching the solution to the problem. In the present approach, a student asks any question related to the topic and gets a suitable reply. Based on his query, he can either get a direct answer to his question or a set of questions (to a maximum of 3 or 4) which bear the greatest resemblance to the user input. We further analyze-application fields for such kind of a system and discuss the scope for future research in this area.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.199-204
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• 2006

최근 멀티미디어의 이용과 멀티미디어 접근을 위한 기술이 많이 증가하고 있다. 그렇지만 멀티미디어 검색엔진과 같은 실용시스템에서 멀티미디어에 대한 유용한 정보 추출과 정보의 응용은 여전히 문제로 있다. 특히, 멀티미디어 이용자는 검색의 효율성을 위하여 저장소를 직관적인 구조로 생성을 하고 있다. 그 예로 "KISS 추계학술 대회 이미지"와 같은 데이터 폴더를 만들거나, 각 멀티미디어 데이터에 Free Text 기반의 주석을 하여 관리를 하였다. 하지만 이러한 검색들에도 한계점을 가지고 있으며 또 다른 지능적인 의미 검색에 있어서도 인간이 바라는 검색의 정확도에 미치지 못하고 있다. 본 논문에서는 이러한 문제점을 해결하기 위한 새로운 접근법을 소개한다. 목적을 위하여 멀티미디어의 의미적인 작업을 위하여 컨텐츠 획득과 분류를 위한 새로운 사용자 도구를 소개하고자 한다. 도구를 이용하는 멀티미디어 사용자는 주어진 컨텐츠를 인간이 생각하고 컨텐츠가 내포하는 의미의 일정한 구조적 단위로 분해하고, 각 단위들에 MPEG-7 표준기반의 추가적인 기술 정보(Description information)를 부여하여 새로운 의미적 메타데이터를 생성할 수 있다. 이러한 의미적 메타데이터는 멀티미디어 검색을 위해 사용자들에게 효율성을 줄 것이라 본다.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.207-218
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• 2012

In recent years, the skyline query paradigm has been established as a reliable method for database query personalization. While early efficiency problems have been solved by sophisticated algorithms and advanced indexing, new challenges in skyline retrieval effectiveness continuously arise. In particular, the rise of the Semantic Web and linked open data leads to personalization issues where skyline queries cannot be applied easily. We addressed the special challenges presented by linked open data in previous work; and now further extend this work, with a heuristic workflow to boost efficiency. This is necessary; because the new view on linked open data dominance has serious implications for the efficiency of the actual skyline computation, since transitivity of the dominance relationships is no longer granted. Therefore, our contributions in this paper can be summarized as: we present an intuitive skyline query paradigm to deal with linked open data; we provide an effective dominance definition, and establish its theoretical properties; we develop innovative skyline algorithms to deal with the resulting challenges; and we design efficient heuristics for the case of predicate equivalences that may often happen in linked open data. We extensively evaluate our new algorithms with respect to performance, and the enriched skyline semantics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.02a
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• pp.151-154
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• 2008

방송된 프로그램의 VOD 서비스는 웹 및 다양한 매체를 통해 중요한 정보 서비스가 되고 있다. 기존의 멀티미디어 검색은 파일명이나 메타데이터를 바탕으로 직접 검색하는 정적인 검색 방법이었다. 본 논문에서는 이런 정적인 검색 방법에서 벗어나 의미적으로 연관된 비디오를 동적으로 검색하여 풍부한 검색 결과를 보여주는 방법을 제안하고, 이를 수행하는 프로토타입 시스템을 설계, 구현함으로써 제안한 방법의 타당성을 보인다. 제안하는 방법은 온톨로지를 이용하여 특정 도메인상에서 사용자가 관심을 가지는 정보의 연관성을 표시하고, 이를 검색과정에 적용한다. 검색 결과는 의미적으로 연관된 정보를 보여줄 뿐 아니라, 연관 카테고리를 바탕으로 관련된 정보를 정리하여 보여줌으로써 사용자는 풍부한 검색 결과 가운데에서 원하는 정보를 쉽고 빠르게 접근할 수 있다. 예를 들면, '고혈압'이라는 검색어를 사용자가 입력하면, 고혈압에 관련된 방송 프로그램 뿐 아니라, '고혈압'에 좋은 음식이나 그 음식의 효능, 효과, 요리법 등 방송을 통해 볼 수 있는 관련 정보들을 한번에 검색할 수 있다.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.39-51
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• 2005

A study of philosophy is a process that archive, reorganize and analyze the earlier works to discover new facts. Philosophy digital resources is necessary to research philosophy because they provide lots of electronic texts, philosophical information, forums, etc. In this paper, we introduce . our result of a research on philosophy digital resources existing in domestic or oversea web sites. We describe the problems which existing resources have and our solution to solve them. Also we provide a guideline to creating philosophy ontology based on topic maps which are data model of ontology. Our philosophy ontology defines hierarchy and associative relationships between philosophical knowledge and support retrieval and exploring of knowledge using semantic information.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.90-93
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• 2008

In natural language, it is common that repetitive constituents in an expression are to be left out and it is necessary to figure out the constituents omitted at analyzing the meaning of the sentence. This paper is on recognition of boundaries of parallel noun phrases by figuring out constituents omitted. Recognition of parallel noun phrases can greatly reduce complexity at the phase of sentence parsing. Moreover, in natural language information retrieval, recognition of noun with modifiers can play an important role in making indexes. We propose an unsupervised probabilistic model that identifies parallel cores as well as boundaries of parallel noun phrases conjoined by a conjunctive particle. It is based on the idea of swapping constituents, utilizing symmetry (two or more identical constituents are repeated) and reversibility (the order of constituents is changeable) in parallel structure. Semantic features of the modifiers around parallel noun phrase, are also used the probabilistic swapping model. The model is language-independent and in this paper presented on parallel noun phrases in Korean language. Experiment shows that our probabilistic model outperforms symmetry-based model and supervised machine learning based approaches.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.50-56
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• 2011

This paper proposes 3D visualization method of compound knowledge which will be able to identify and search easily compound knowledge objects based the multidimensional relationship. For this, we structurized a compound knowledge with link and node which become the semantic network. and we suggested 3D visualization method using SOM. Also, to arrange compound knowledge from 3D space and to provide the chance of realistic and intuitional information retrieval to the user, we proposed compound knowledge 3D clustering methods using object similarity. Compound knowledge 3D visualization and clustering using SOM will be the optimum method to appear context of compound knowledge and connectivity in space-time.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.185-193
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• 2008

In spite of rapid development of IT-related meteorology and services, human users still ought to check the weather information manually as they did before because traditional weather information retrieval is based on pull-type and human interpretation. Furthermore, the automatic machine-driven weather information processing has been neglected for a long time although the intelligent weather information processing is expected to be very useful for personal daily life and ubiquitous computing. In this paper, we discussed a design of GRIB based ontology to enable smart weather information processing. GRIB is the general purposed and world-wildly used weather data format approved by the World Meteorological Organization. With the designed ontology and the inference system containing Jess engine, several intelligent weather applications have been implemented and tested to verify the virtue of machine-driven weather information processing.