• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.715-716
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• 2009

인터넷의 발전은 대량의 정보를 양산하였고, 이러한 대량의 정보 집합 내에서는 비슷한 정보가 재활용 되거나 반복되는 정보중복문제를 가지고 있다. 중복되는 정보들로부터 사용자에게 원하는 정보를 신속히 검색할 수 있도록 하는 정보 요약에 대한 필요성은 점차 증가하고 있다. 본 논문은 비음수 행렬 인수분해(NMF, non-negative matrix factorization)에 의한 문서의 의미특징을 이용하여 주제기반의 다중문서를 요약하는 새로운 방법을 제안한다. 본 논문에서는 다중문서가 포함하고 있는 문서들 간의 고유구조를 문서요약에 이용하여서 요약의 질을 높일 수 있고, 주제와 문장 간의 유사성과 다양성 고려하여서 쉽게 과잉정보를 제거하여 문장을 요약할 수 있는 장점을 갖는다.

• Korean Journal of Cognitive Science
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• v.12 no.1_2
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• pp.35-42
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• 2001

In this paper. a document is represented as a weighted graph called a text relationship map. In the graph. a node represents a vector of nouns in a sentence, an edge completely connects other nodes. and a weight on the edge is a value of the similarity between two nodes. The similarity is based on the word overlap between the corresponding nodes. The importance of a node. called an aggregate similarity in this paper. is defined as the sum of weights on the links connecting it to other nodes on the map. In this paper. we present a Korean text summarization system using the aggregate similarity. To evaluate our system, we used two test collection, one collection (PAPER-InCon) consists of 100 papers in the field of computer science: the other collection (NEWS) is composed of 105 articles in the newspapers and had built by KOROlC. Under the compression rate of 20%. we achieved the recall of 46.6% (PAPER-InCon) and 30.5% (NEWS) and the precision of 76.9% (PAPER-InCon) and 42.3% (NEWS).

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.702-714
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• 2001

As Internet technology evolves, there is growing need of Internet queries involving multiple information sources. Efficient processing of such queries necessitates the integrated summary data that compactly represents the data distribution of the entire database scattered over many information sources. This paper presents an efficient method of managing the integrated summary data based on the wavelet transform and addresses Internet query processing using the integrated summary data. The simplest method for creating the integrated summary data would be to summarize the integrated data sidtribution obtained by merging the data distributions in multiple information sources. However, this method suffers from the high cost of transmitting storing and merging a large amount of data distribution. To overcome the drawbacks, we propose a new wavelet transform based method that creates the integrated summary data by merging multiple summary data and effective method for optimizing Internet queries using it A wavelet transformed summary data is converted to satisfy conditions for merging. Moreover i the merging process is very simpe owing to the properties of the wavelet transform. we formally derive the upper bound of the error of the wavelet transformed intergrated summary data. Compared with the histogram-based integrated summary data the wavelet transformedintegrated summary data provesto be 1.6~5.5 time more accurate when used for selectivity estimation in experiments. In processing Internet top-N queries involving 56 information sources using the integrated summary data reduces the processing cost to 1/44 of the cost of not using it.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.35-42
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• 2008

The proposed scheme in this paper can search multi-links efficiently using the depth priority method based on hop count instead of searching the all links. To do this, we proposed a modified line segment scheme using two line segment method. The scheme represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multiple-links aggregation. And we apply it to current spanning tree topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crankback rate. Simulation result analysis showed the proposed spanning tree topology aggregation scheme presents the better performance than existing scheme.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.1-9
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• 2007

Topology information can be constructed hierarchically in the networks and the process of aggregating topology information is known as TA(Topology Aggregation). It is very important for scalability in networks. In paticular, routing and TA algorithm are very much elements on networks performance in private networks to networks interface. Therefore, in this paper, we designed and implemented routing simulator for TA in private networks to networks interface. And we evaluated and analyzed the existent TA algorithm using the implemented simulator. The implemented simulator can be used valuably to developing TA algorithm.

• Journal of KIISE:Software and Applications
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• v.26 no.3
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• pp.335-342
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• 1999

논리 프로그램의 타입 및 모드 분석은 실행 시간에 변수가 갖는 텀의 집합에 대한근사값을 구하는데 보통 요약 해석을 기반으로 하여 설계되고 개발되어 왔다. 이 논문에서는 타입 및 모드 분석을 위해서 설계된 다양한 요약 도메인을 고려하여 그들간의 계층 관계를 Galois insertion을 기준으로 밝힌다. 이 논문에서는 요약 도메인으로써 타입 그래프, 깊이-k 타입 , 깊이-k 모드, 순환모드, 그리고 모드를 고려할 것이다. 특히 깊이-k 모드는 타입 및 모드 분석을 통합하기 위한 도메인으로써 깊이-k 타입을 확장하여 제안하였다.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.114-125
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• 2002

Although there have been a lot of researches on a video abstraction algorithm, the video abstraction tool is necessary to correctly pick up some important shots in a video because the important shots might vary on the person's subjectivity. This paper proposes a video abstraction and search system for making a video abstraction automatically or manually. Proposed system has two main components, server and client. The server generates the Metadata and makes a video abstraction file. The description for video abstraction file is based on MPEG-7. Since proposed system has a function to manually correct the results of each step, the author could produce a good video abstraction easily and efficiently. The proposed system could be used to build a digital video library.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.82-93
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• 2000

Recently, the capability of efficient access to the desired video content is of growing importance because more digital video data are available at an increasing rate. A video summary abstracting the gist from the entirety enables the efficient browsing as well as the fast skimming of the video contents. In this paper, we discuss a novel dynamic summarization method based on the detection of highlights which represent semantically significant content and the description scheme (DS) proposed to MPEG-7 aiming to provide summary description. The summary DS proposed to MPEG-7 allows for efficient navigation and browsing to the contents of interest through the functionalities of multi-level highlights, hierarchical browsing and user-customized summarization. In this paper, we also show the validation and the usefulness of the methodology for dynamic summarization and the summary DS in real applications with soccer video sequences.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.62-69
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• 2009

The purpose of document summarization is to provide easy and quick understanding of documents by extracting summarized information from the documents produced by various application programs. In this paper, we propose a document summarization method that creates and analyzes a connection graph representing the similarity of keyword lists of sentences in a document taking into account the mean length(the number of keywords) of sentences of the document. We implemented a system that automatically generate a summary from a document using the proposed method. To evaluate the performance of the method, we used a set of 20 documents associated with their correct summaries and measured the precision, the recall and the F-measure. The experiment results show that the proposed method is more efficient compared with the existing methods.

• Journal of KIISE
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• v.44 no.2
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• pp.179-185
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• 2017

Document summarization aims to generate a summary that is consistent and contains the highly related sentences in a document. In this study, we implemented for document summarization that extracts highly related sentences from a whole document by considering both similarities and entailment relations between sentences. Accordingly, we proposed a new algorithm, TextRank-NLI, which combines a Recurrent Neural Network based Natural Language Inference model and a Graph-based ranking algorithm used in single document extraction-based summarization task. In order to evaluate the performance of the new algorithm, we conducted experiments using the same datasets as used in TextRank algorithm. The results indicated that TextRank-NLI showed 2.3% improvement in performance, as compared to TextRank.