• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.129-155
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• 2010

In recent years, the changes in information technology have been so dramatic and the rate of changes has increased so much that information science research rigorously evolves with the passage of time and proliferates in diverging research directions dynamically. The aims of this study are to provide a global overview of research trends in information science and to trace its changes in the main topics over time. The study examined the topics of research articles published in JASIST between 1985 and 2009 and identified its changes during five 5 year periods. The study found that the most productive area has consistently been 'Information Retrieval', followed by 'Informetrics', 'Information Use and Users', 'Network and Technology', and 'Publishing and Services'. Information retrieval is a predominant core area in Information Science covering computer-based handling of multimedia information, employment of new semantic methods from other disciplines, and mass information handling on virtual environments. Currently Informetric studies shift from finding existing phenomena to seeking valuable descriptive results and researchers of information use have concentrated especially on information-seeking aspects, so adding greater sophistication to the relatively simple approach taken in information retrieval.

• The Journal of Information Technology
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• v.4 no.2
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• pp.69-81
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• 2001

In this paper, we examine work in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representations, exploit context and overage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving visual information at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent systems in the fields of cognitive psychology, artificial intelligence, semiotics. We also discuss how some of the principal ideas from these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we discribe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework that facilitate and enable intelligent content-based retrieval.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.677-684
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• 2016

With the increase of multimedia information such as image, researches on extracting high-level semantic information from low-level visual information has been realized, and in order to automatically generate this kind of information. Various technologies have been developed. Generally, image retrieval is widely preceded by comparing colors and shapes among images. In some cases, images with similar color, shape and even meaning are hard to retrieve. In this article, in order to retrieve the object in an image, technical value of middle level is converted into meaning value of middle level. Furthermore, to enhance accuracy of segmentation, K-means algorithm is engaged to compute k values for various images. Thus, object retrieval can be achieved by segmented low-level feature and relationship of meaning is derived from ontology. The method mentioned in this paper is supposed to be an effective approach to retrieve images as required by users.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.43-52
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• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.

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

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.375-378
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• 2003

본 논문에서는 공간적 정보로 이미지검색을 하는 모양 특징정보 기반 이미지 검색 시스템에서 검색효율을 향상 시킬 수 있는 이진 영상 변환 및 유사도 검색에 대한 기법을 제안하였다. 모양특징정보의 좀더 정확한 값의 추출을 위해 이미지의 잡음이 윤곽선으로 인식되는 값이 최소화 될 수 있도록 하는 이진 영상 변환방법을 제안하였으며, 유사도 검색에서는 영역별 특징정보 간의 비교와 병행하여 영역을 다시 소그룹화한 다음 소그룹간의 평균 유사도 값의 비교방법을 적용하였다. 성능 평가를 통하여 제안된 이진 영상 변환 겐 유사도 검색 방법을 사용한 경우 기존의 방법보다 향상된 검색 효율성을 보임을 알 수 있었다.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.75-78
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• 2001

본 논문은 통계청에서 실시하는 인구주택 총조사로부터 획득된 각 개인의 직업 및 직종을 기술하고 있는 자연어를 입력받아 입력된 자연어가 의미하는 한국 표준 산업/구업 분류 코드의 후보들을 생성하는 산업/직업 코드 분류 도구를 제안한다. 코드 분류는 분류할 코드를 문서 범주로 간주하면 문서 분류와 동일한 문제로 생각할 수 있다. 하지만 본 산업/직업 코드 분류 문제는 입력되는 자연어의 길이가 한 두 문장 정도로 매우 짧아 문서 분류에 사용될 자질들이 개수가 주어 기존의 문서 분류 기법을 적용하기 어렵다. 이에 본 논문은 표준 코드를 기술하고 있는 내용을 미리 색인하고 입력된 자연어로부터 질의어를 생성하여 벡터공간모델로 질의어를 검색후 질의어와 일치율이 가장 높은 코드들을 분류될 후보 코드로 계시하는 정보검색 기법을 이용한 산업/직업 코드 분류 도구를 개발하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.99-102
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• 2000

이기종 간의 문서 교환 표준으로 제안되 SGML은 문서의 구조정보를 표현할 수 있는 장점으로 인해 CALS(Commerce At Light Speed), EC(Electronic Commerce), EDI(Electronic Data Interchange), 전자 도서관(Digital Library) 등 여러 분야에서 사용되고 있다. 이렇게 SGML이 여러 분야에서 사용됨에 따라 많은 SGML 문서 중에서 원하는 문서를 효율적으로 찾아줄 수 있는 검색 시스템의 필요성이 증가하고 있다. 이에 본 연구실에서는 기본적인 구조 검색을 지원하는 SGML 문서 관리시스템을 기개발하였다. 그러나 이 시스템은 구조 검색을 효과적으로 지원하기 못하기 때문에 본 연구에서는 구조 검색의 기능을 정의하고, 이를 지원하는 새로운 구조 질의어를 정의하였다. 또한 이러한 구조 검색을 효과적으로 지원하기 위한 구조 색인을 정의하였다. 그리고 구조 검색 방식으로 세가지 방식을 각각 구현 및 실험하여 그 중에서 성능이 뛰어난 절충식을 이용하여 검색 시스템을 구현하였다.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.250-259
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• 2019

Big data processing technology and artificial intelligence (AI) are increasingly attracting attention. Natural language processing is an important research area of artificial intelligence. In this paper, we use Korean news articles to extract topic distributions in documents and word distribution vectors in topics through LDA-based Topic Modeling. Then, we use Word2vec to vector words, and generate a weight matrix to derive the relevance SCORE considering the semantic relationship between the words. We propose a way to recommend documents in order of high score.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.1-13
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• 2000

While various types of information can be mixed in a continuous video stream without any cleat boundary, the meaning of a video scene can be interpreted by multiple levels of abstraction, and its description can be varied among different users. Therefore, for the content-based retrieval in video data it is important for a user to be able to describe a scene flexibly while the description given by different users should be maintained consistently This paper proposes an effective way to represent the different types of video information in conventional database models such as the relational and object-oriented models. Flexibly defined attributes and their values are organized as tree-structured dictionaries while the description of video data is stored in a fixed database schema. We also introduce several browsing methods to assist a user. The dictionary browser simplifies the annotation process as well as the querying process of a user while the result browser can help a user analyze the results of a query in terms of various combinations of Query conditions.