• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.1-10
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• 2007

Many types of information provided through the web including news contents contain unnecessary clutters. These clutters make it difficult to build automated information processing systems such as the summarization, extraction and retrieval of documents. We propose a system that extracts and summarizes news contents from the web. The extraction system receives news contents in HTML as input and builds an element tree similar to DOM tree, and extracts texts while removing clutters with the hyperlink attribute in the HTML tag from the element tree. Texts extracted through the extraction system are transferred to the summarization system, which extracts key sentences from the texts. We implement the summarization system using co-occurrence relation graph. The summarized sentences of this paper are expected to be transmissible to PDA or cellular phone by message services such as SMS.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.406-415
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• 2005

Prosperity of Internet led to the web containing huge number of documents. Thus increasing importance is given to the web information retrieval technology that can provide users with documents that contain the right information they want. This paper proposes several techniques that are effective for the improvement of web information retrieval. Similarity between a document and the query is a major source of information exploited by conventional systems. However, we suggest a technique to make use of similarity between a sentence and the query. We introduce a technique to compute the approximate score of the sentence-query similarity even without a mature technology of natural language processing. It was shown that the amount of computation for this task is linear to the number of documents in the total collection, which implies that practical systems can make use of this technique. The next important technique proposed in this paper is to use stratification of documents in re-ranking the documents to output. It was shown that it can lead to significant improvement in performance. We furthermore showed that using hyper links, anchor texts, and titles can result in enhancement of performance. To justify the proposed techniques we developed a large scale web information retrieval system and used it for experiments.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.49-59
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• 2009

Contents-based image retrieval methods are in general more objective and effective than text-based image retrieval algorithms since they use color and texture in search and avoid annotating all images for search. SIM(Self-organizing Image browsing Map) is one of contents-based image retrieval algorithms that uses only browsable mapping results obtained by SOM(Self Organizing Map). However, SOM may have an error in selecting the right BMU in learning phase if there are similar nodes with distorted color information due to the intensity of light or objects' movements in the image. Such images may be mapped into other grouping nodes thus the search rate could be decreased by this effect. In this paper, we propose an improved SIM that uses HSV color model in extracting image features with color quantization. In order to avoid unexpected learning error mentioned above, our SOM consists of two layers. In learning phase, SOM layer 1 has the color feature vectors as input. After learning SOM Layer 1, the connection weights of this layer become the input of SOM Layer 2 and re-learning occurs. With this multi-layered SOM learning, we can avoid mapping errors among similar nodes of different color information. In search, we put the query image vector into SOM layer 2 and select nodes of SOM layer 1 that connects with chosen BMU of SOM layer 2. In experiment, we verified that the proposed SIM was better than the original SIM and avoid mapping error effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1404-1417
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• 1998

Currently, there exists two different methods for database retrieval in the internet. First is to use the search engine and the second is to use the plug-in or ActiveX technology, If a search engine, which makes use of indices built from keywords of simple text data in order to do a search, is used when accessing a database, first it is not possible to access more than one database at a time, second it is also not possible to support various conditional retrievals as in using query language, and third the set of data received might include many unwanted data, in other words, precision rate might be relatively low. Plug in or Active technology make use of Web browset to execute chents' query in order to do a database retrieval. Problems associated with this is that it is not possible to activate more than one DBMS simultaneously even if they are of the same data model. sefond it is not possible to execute a user query other than the ones thai arc previou sly defined by the client program In this paper, to resolve those aforementioned problems we design and implement database retrieval system using a virtual database, which makes it possible to provide direct query jntertacc through the conventional Web browser. We assume that the virtual database is designed and aggregated from more than one relational database using the same data model.

• Journal of Multimedia Information System
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• v.3 no.3
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• pp.53-61
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• 2016

This research proposes the index optimization as a classification task and application of the graph based KNN. We need the index optimization as an important task for maximizing the information retrieval performance. And we try to solve the problems in encoding words into numerical vectors, such as huge dimensionality and sparse distribution, by encoding them into graphs as the alternative representations to numerical vectors. In this research, the index optimization is viewed as a classification task, the similarity measure between graphs is defined, and the KNN is modified into the graph based version based on the similarity measure, and it is applied to the index optimization task. As the benefits from this research, by modifying the KNN so, we expect the improvement of classification performance, more graphical representations of words which is inherent in graphs, the ability to trace more easily results from classifying words. In this research, we will validate empirically the proposed version in optimizing index on the two text collections: NewsPage.com and 20NewsGroups.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.184-186
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• 2000

이 연구에서는 텍스트 문서를 웹에서 HTML 문서 형태로 효율적으로 검색할 수 있는 변환 시스템을 개발하였다. 웹상에 사용자가 원하는 부분만을 HTML 문서 형태로 제공하도록 문서의 논리적인 구조를 파악하며 그 구조에 대한 정보와 각 논리 단위에 해당하는 부분의 범위 정보를 저장할 수 있도록 관계형 데이터베이스 스키마를 개발하였다. 개발한 시스템은 문서의 목차 테이블을 자동으로 구축하고 목차 테이블의 각 항목에 하이퍼링크를 설정한다. 문서를 웹에서 검색하기 위한 첫 화면은 목차 테이블이며, 그 중 한 항목이 클릭되면 그 항목의 내용이 제공되고, 만약 그 하위에 속하는 항목들이 있다면 그들에 대한 링크를 역시 제공한다. 이러한 방법으로 한 문서의 전체를 그 논리 구조에 따라 사용자가 원하는 대로 검색할 수 있다. 이 시스템은 멀티미디어 타입의 문서를 하이퍼미디어 문서 형식으로 변환할 수 있도록 확장하여 보완 개발될 수 있고, 장래에 전자 출판과 전자 도서관에 응용될 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.274-276
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• 1998

많은 분야에서 정보를 효과적으로 전달하기 위한 수단으로 멀티미디어가 많이 사용되고 있다. 이에 멀티미디어 문서를 효율적으로 저장, 검색, 표현하기 위한 기법에 대한 연구가 필요하다. 멀티미디어 문서 내에 사용되는 audio, video, image, text와 같은 여러 미디어들은 문서 내에서 시.공간적 관계뿐 아니라 내용상의 연관성을 갖게 된다. 본 논문에서는 멀티미디어 문서에 사용되는 미디어들의 특징 및 연관성을 추출해 내고, 각 미디어들을 효율적으로 관리하기 위하여 미디어 특성에 맞는 세크멘테이션 기법을 이용하고 이들에 대한 내용상의 연관성을 고려하여 저장(store), 검색(retrieve), 표현(present)하기위한 시스템을 설계 하였다.

• Annual Conference on Human and Language Technology
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• 2006.10e
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• pp.98-106
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• 2006

문서분류기의 개발에 있어 교사학습기법을 이용할 경우 많은 양의 사람에 의한 범주 부착 말뭉치가 필요하다. 그러나 이의 구축은 많은 시간과 노력을 필요로 한다. 최근 이러한 범주 부착 말뭉치 대신 원시말뭉치와 범주마다 약간의 씨앗 정보를 이용하여 학습을 수행하여 문서분류기를 개발하는 방법론이 제시되었다. 본 논문에서는 이 방법론 하에서 다른 연구에서의 결과보다 좋은 성능을 나타내는 비교사 학습 기법을 소개한다. 본 논문에서 제시하는 기법의 특징은 씨앗 단어에서 출발하여 평균상호정보를 이용하여 다른 대표단어 및 그들의 가중치를 학습한 다음, 정보검색에서 많이 사용하는 기술을 이용하여 그 가중치를 갱신하는 것이다. 그리고 이 과정을 반복 수행하여 최종적으로 높은 성능의 시스템을 개발할 수 있음을 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.333-336
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• 2003

컴퓨터와 네트워크의 처리속도 증가와, 인터넷의 발달로 인하여 이미지, 사운드, 동영상 등 각종 멀티미디어 정보가 인터넷상에 다수 등록되고 있으며, 이에 대한 검색 요구도 증가하고 있다. 그에 따라 다양한 멀티미디어 정보 검색을 위한 방법이 연구되고 있지만, 그에 대하 활용도는 미미하며, 데이터 베이스에 등록된 단순 멀티미디어 정보 검색에 머물고 있는 실정이다. 이에 본 연구는 인터넷상의 멀티미디어 정보 중 이미지 정보를 능동적으로 수집, 정보를 추출하여 검색에 이용한다 이를 위하여, 이미지에 대한 text 정보와 이미지의 속성 및 Link 정보를 이용, 의미 있는 이미지와 의미 없는 이미지를 분류하여 검색의 효율을 높이고, 속성 및 Link 정보를 가중치로 사용함으로써 검색 시 이미지의 중요도를 평가할 수 있도록 한다.