• Journal of the Korean Society for Library and Information Science
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• v.25
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• pp.51-82
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• 1993

Effective indexing systems are required to enhance the performance of full-text retrieval systems. The result of the analysis of index terms selected by human indexers without a newspaper thesaurus indicates that controlled indexing language is necessary for effective and consistent indexing of newspaper articles. In this paper, basic principles are established for keyword selection from Korean newspapers and significant problems identified in the process of developing a newspaper thesaurus are discussed in depth.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.703-714
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• 2005

Researches in text categorization have been confined to whole-document-level classification, probably due to lacks of full-text test collections. However, full-length documents availably today in large quantities pose renewed interests in text classification. A document is usually written in an organized structure to present its main topic(s). This structure can be expressed as a sequence of sub-topic text blocks, or passages. In order to reflect the sub-topic structure of a document, we propose a new passage-level or passage-based text categorization model, which segments a test document into several Passages, assigns categories to each passage, and merges passage categories to document categories. Compared with traditional document-level categorization, two additional steps, passage splitting and category merging, are required in this model. By using four subsets of Routers text categorization test collection and a full-text test collection of which documents are varying from tens of kilobytes to hundreds, we evaluated the proposed model, especially the effectiveness of various passage types and the importance of passage location in category merging. Our results show simple windows are best for all test collections tested in these experiments. We also found that passages have different degrees of contribution to main topic(s), depending on their location in the test document.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.69-86
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• 1998

The purpose of velop the indexing algorithm of secondary legal information by the study of characteristics of legal information, to compare the indexing system using controlled vocabulary to the indexing system using natural language in the secondary legal information full-text databases, and to prove propriety and superiority of the indexing system using controlled vocabulary. The results are as follows; 1)The indexing system using controlled vocabulary in the secondary legal information full-text databases has more effectiveness than the indexing system using natural language, in the recall rate, the precision rate, the distribution of propriety, and the faculty of searching for the unique proper-records which the indexing system using natural language fans to find 2)The indexing system which adds more words to the controlled vocabulary in the secondary legal information full-text databases does not better effectiveness in the retail rate, the precision rate, comparing to the indexing system using controlled vocabulary. 3)The indexing system using word-added controlled vocabulary with an extra weight in the secondary legal information full-text databases does not better effectiveness in the recall rate, the precision rate, comparing to the indexing system using word-added controlled vocabulary without an extra weight. This study indicates that it is necessary to have characteristic information the information experts recognize - that is to say, experimental and inherent knowledge only human being can have built-in into the system rather than to approach the information system by the linguistic, statistic or structuralistic way, and it can be more essential and intelligent information system.

• Journal of Information Science Theory and Practice
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• v.10 no.4
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• pp.3-22
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• 2022

This paper provides an overview of the emergence of resource discovery systems and services, along with their advantages, best practices, and current landscapes. It outlines some of the key services and functionalities of a comprehensive discovery model suitable for academic libraries in developing countries. The proposed model (VuFind as a discovery tool) performs like other existing web-scale resource discovery systems, both commercial and open-source, and is capable of providing information resources from different sources in a single-window search interface. The objective of the paper is to provide seamless access to globally distributed subscribed as well as open access resources through its discovery interface, based on a unified index. This model uses Koha, DSpace, and Greenstone as back-ends and VuFind as a discovery layer in the front-end and has also integrated many enhanced search features like Bento-box search, Geodetic search, and full-text search (using Apache Tika). The goal of this paper is to provide the academic community with a one-stop shop for better utilising and integrating heterogeneous bibliographic data sources with VuFind (https://vufind.org/vufind).

• International Journal of Contents
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• v.3 no.3
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• pp.6-14
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• 2007

In this paper, we design and implement a XML Repository System(XRS) that exploits the advantages of DBMSs and IRSs. Our scheme uses BRS to support full text indexing and content-based queries efficiently, and ORACLE to store XML documents, multimedia data, DTD and structure information. We design databases to manage XML documents including audio, video, images as well as text. We employ the non-composition model when storing XML documents into ORACLE. We represent structured information as ETID(Element Type Id), SORD(Sibling ORDer) and SSORD(Same Sibling ORDer). ETID is a unique value assigned to each element of DTD. SORD and SSORD represent an order information between sibling nodes and an order information among the sibling nodes with the same element respectively. In order to show superiority of our XRS, we perform various experiments in terms of the document loading time, document extracting time and contents retrieval time. It is shown through experiments that our XRS outperforms the existing XML document management systems. We also show that it supports various types of queries through performance experiments.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.06a
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• pp.95-100
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• 2000

문자 인식기를 가지고 스캔된 원문 이미지를 인식한 결과로 형태소 분석과 어절 분석을 통해 대용량의 문서 정보를 데이터베이스에 구축하고 전문 검색(full text retrieval)이 가능하도록 한다. 그러나, 입력문자가 오인식된 경우나 띄어쓰기가 잘못된 데이터는 형태소 분석이나 어절 분석에 그대로 사용할 수가 없다. 한글 문자 인식의 경우 문자 단위의 인식률은 약 90.5% 정도나 문자 인식 오류와 띄어쓰기 오류 등을 고려한 어절 단위의 인식률은 현저하게 떨어진다. 이를 위해 한극어의 음절 특성을 고려해서 사전을 기반하지 않고 학습이 잘된 말뭉치(corpus)와 음절 단위의 bi-gram 정보를 이용한 자동 띄어쓰기를 하여 실험한 결과 학습 코퍼스의 크기와 띄어쓰기 오류 위치 정보에 따라 다르지만 약 86.2%의 띄어쓰기 정확도를 보였다. 이 결과를 가지고 형태소 분서고가 언어 평가 등을 이용한 문자 인식 후처리 과정을 거치면 문자 인식 시스템의 인식률 향상에 크게 영향을 미칠 것이다.

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.95-100
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• 2000

문자 인식기를 가지고 스캔된 원문 이미지를 인식한 결과로 형태소 분석과 어절 분석을 통해 대용량의 문서 정보를 데이터베이스에 구축하고 전문 검색(full text retrieval)이 가능하도록 한다. 그러나, 입력문자가 오인식된 경우나 띄어쓰기가 잘못된 데이터는 형태소 분석이나 어절 분석에 그대로 사용할 수가 없다. 한글 문자 인식의 경우 문자 단위의 인식률은 약 90.5% 정도나 문자 인식 오류와 띄어쓰기 오류 등을 고려한 어절 단위의 인식률은 현저하게 떨어진다. 이를 위해 한국어의 음절 특성을 고려해서 사전을 기반하지 않고 학습이 잘된 말뭉치(corpus)와 음절 단위의 bigram 정보를 이용한 자동 띄어쓰기를 하여 실험한 결과 학습 코퍼스의 크기와 띄어쓰기 오류 위치 정보에 따라 다르지만 약 86.2%의 띄어쓰기 정확도를 보였다. 이 결과를 가지고 형태소 분석과 언어 평가 등을 이용한 문자 인식 후처리 과정을 거치면 문자 인식 시스템의 인식률 향상에 크게 영향을 미칠 것이다.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1204-1218
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• 1999

문서영상 검색을 위한 디지털도서관의 대부분은 논문제목과/또는 논문요약으로부터 만들어진 색인에 근거한 제한적인 검색기능을 제공하고 있다. 본 논문에서는 영문 문서영상전체에 대한 검색을 위한 단어 영상 형태 특징기반의 단어검색시스템을 제안한다. 본 논문에서는 검색의 효율성과 정확도를 높이기 위해 1) 기존의 단어검색시스템에서 사용된 특징들을 조합하여 사용하며, 2) 특징의 개수 및 위치뿐만 아니라 특징들의 순서를 포함하여 매칭하는 방법을 사용하며, 3) 특징비교에 의해 검색결과를 얻은 후에 여과목적으로 문자인식을 부분적으로 적용하는 2단계의 검색방법을 사용한다. 제안된 시스템의 동작은 다음과 같다. 문서 영상이 주어지면, 문서 영상 구조가 분석되고 단어 영역들의 조합으로 분할된다. 단어 영상의 특징들이 추출되어 저장된다. 사용자의 텍스트 질의가 주어지면 이에 대응되는 단어 영상이 만들어지며 이로부터 영상특징이 추출된다. 이 참조 특징과 저장된 특징들과 비교하여 유사한 단어를 검색하게 된다. 제안된 시스템은 IBM-PC를 이용한 웹 환경에서 구축되었으며, 영문 문서영상을 이용하여 실험이 수행되었다. 실험결과는 본 논문에서 제안하는 방법들의 유효성을 보여주고 있다. Abstract Most existing digital libraries for document image retrieval provide a limited retrieval service due to their indexing from document titles and/or the content of document abstracts. This paper proposes a word spotting system for full English document image retrieval based on word image shape features. In order to improve not only the efficiency but also the precision of a retrieval system, we develop the system by 1) using a combination of the holistic features which have been used in the existing word spotting systems, 2) performing image matching by comparing the order of features in a word in addition to the number of features and their positions, and 3) adopting 2 stage retrieval strategies by obtaining retrieval results by image feature matching and applying OCR(Optical Charater Recognition) partly to the results for filtering purpose. The proposed system operates as follows: given a document image, its structure is analyzed and is segmented into a set of word regions. Then, word shape features are extracted and stored. Given a user's query with text, features are extracted after its corresponding word image is generated. This reference model is compared with the stored features to find out similar words. The proposed system is implemented with IBM-PC in a web environment and its experiments are performed with English document images. Experimental results show the effectiveness of the proposed methods.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.5-26
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• 2004

A literature analysis for the planning and realization of the multimedia meta database and digital library's integrated information system was carried out to establish the various oceanographic resources in the Oceanographic Information Center, the first in Korea. The study targeted from printed matter, network resources, full-text and to VOD. The focus of the analysis lies in the providing practical integrated information retrieval service for oceanographic resources based on the framework of effective MODS metadata with network resources description. The analyses included oceanographic resources, multimedia information processing, MODS metadata descriptive elements, metadata classification, system organization, and retrieval for planning and implementation of the multimedia meta database system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.430-433
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• 2007

There have been several researches to manipulate XML Queries efficiently since XML has been accepted in many areas. Among the many of the researches majority of them adopt relational databases as underlying systems because relational model which is used the most widely for managing large data efficiently. In this paper we develop XQuery to SQL Translation Algorithms called XSTAR that can efficiently handle XPath, XQuery FLWORs with nested iteration expressions, element constructors and keywords retrieval on relational database as well as constructing XML fragments from the transformed SQL results. The entire algorithms mentioned in XSTAR have been implemented as the XQuery processor engine in XML management system, XPERT, and we can test and confirm it's prototype from "http ://dblab.kmu.ac.kr/project.jsp".