• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.552-557
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• 2015

IT technology development and smart appliances due to the increased use of a lot of data on production and consumption has become in the internet. Because this is why importance of information retrieval technology although the growing becoming aware of the difficult techniques to access the required of lot a background knowledge on information retrieval technology. However, the Lucene due to emerge provide to background can implement on search engine by using the Lucene of lack background knowledge for search technology. In this paper, suggest to implement on search engine by using the developed a framework on Lucene-based. Suggest a frameworks are use in the search engines on have guarantee in server environment support on distributed processing and distributed storage, and high availability by using the Hadoop and Nutch, Solr, Zookeeper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.619-621
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• 2014

addition to the advances in information technology and the latest IT technology for their issue. To enable users who are using the Web to find need the information your search data they're sifting through about how many are struggling. In this paper, we propose a user-centered search system. Lucene search system to offer Hadoop's MapReduce with the Apache project Nutch, Solr, HDFS, utilizing design and implementation. This is the Web search users who wish to use depending on the intentions of the data that you want to collect and index information will be utilized in the search field.

• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.177-193
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• 2011

This study constructed an ontology targeting journal articles and evaluated its performance. Also, the performance of a triple structure ontology was compared with the knowledge base of an inverted index file designed for a simple keyword search engine. The coverage was three years of articles published in the Journal of the Korean Society for Information Management from 2007 to 2009. Protege was used to construct an ontology, whilst utilizing an inverted index file to compare performance. The concept ontology was manually established, and the bibliography ontology was automatically constructed to produce an OWL concept ontology and an OWL bibliography ontology, respectively. This study compared the performance of the knowledge base of the ontology, using the Jena search engine with the performance of an inverted index file using the Lucene search engine. As a result, The Lucene showed higher precision rate, but Jena showed higher recall rate.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.141-160
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• 2011

This study suggested knowledge base and search engine for the libraries that have the largescaled data. For this purpose, 3 components of knowledge bases(triple ontology, concept-based knowledge base, inverted file) were constructed and 3 search engines(search engine JENA for rule-based reasoning, Concept-based search engine, keyword-based Lucene retrieval engine) were implemented to measure their performance. As a result, concept-based retrieval engine showed the best performance, followed by ontology-based Jena retrieval engine, and then by a normal keyword search engine.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.603-605
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• 2014

Has been switched to the online shopping market in stores of the consumer is from increased utilization and smart devices, the internet popularization. That is why has been converting the user's consumption patterns and consumer culture. Open markets is provides of making a wide variety of events and lowest price policies, safe transactions etc, for attract the consumers of expand distribution channels of the web and via mobile. In this paper, a designs of provides a search system for minimum price product information to the user of Information collect and analyze on sale from open market.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.10
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• pp.1145-1156
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• 2015

There is a shortage of mobile application systems readily applicable to the field of crop cultivation in relation to diseases and insect pests directly connected to the quality of crops. Most of system have been devoted to diseases and insect pests that would offer full predictions and basic information about diseases and insect pests currently. But for lack of the instant diagnostic functions seriously and the field of crop cultivation, we design and implement a crop cultivation field-oriented smart diseases and insect pests information retrieval system based on mobile for u-Farm. The proposed system had such advantages as providing information about diseases and insect pests in the field of crop cultivation and allowing the users to check the information with their smart-phones real-time based on the Lucene, a search library useful for the specialized analysis of images, and JSON data structure. And it was designed based on object-oriented modeling to increase its expandability and reusability. It was capable of search based on such image characteristic information as colors as well as the meta-information of crops and meta-information-based texts. The system was full of great merits including the implementation of u-Farm, the real-time check, and management of crop yields and diseases and insect pests by both the farmers and cultivation field managers.

• Proceedings of The KACE
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• 2017.08a
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• pp.37-40
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• 2017

본 논문에서는 국가 연구 보고서의 공기 관계 정보와 제목, 요약 등에 가중치를 적용한 유사도 계산방법을 제안한다. 이를 위해 국가 연구개발 보고서에서 텍스트를 추출하여 한 문장 단위로 문서를 분할하고, 기본 불용어와 보고서에서 특징적으로 나타나는 불용어를 처리하고 형태소 분석을 한 뒤 공기관계를 추출하였다. 또한 문서의 유사도 계산시 정확성을 높이기 위해 제목과 요약 부분에 가중치를 부여하였다. 이를 통해 본 논문에서 제안하는 방법이 문서 검색 라이브러인 루씬(Lucene)을 이용한 방법보다 2.5%의 검색성능 향상을 그리고 Knn-휴리스틱 방법보다는 1.1%의 검색성능 향상을 보였다. 이러한 결과를 통해 문서의 요약과 제목 그리고 공기관계 정보가 연구보고서의 유사도를 계산 하는데 영향을 미친다는 것을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.311-316
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• 2010

본 논문에서는 NHN에서 제작한 오픈소스 분산처리 플랫폼 Coord 및 색인정보를 생성하는 Lucene을 이용하여 문서 검색 시스템의 설계를 제안한다. 주로 Coord 플랫폼을 사용하여 분산 검색 시스템의 구축 프로세스 및 구축 과정에서 고려할 점들에 대해 소개하고 있다. 구축 결과물에 대한 정량적 분석 및 특성을 다른 경쟁 플랫폼들과 비교 분석한다면 Coord의 사용을 활성화시킬 수 있는 자료로 사용될 수 있을 것이다. Coord 플랫폼을 개괄한 후에는 실제적인 시스템의 전체 구조를 제안한다. 이후에는 색인정보를 담고 있는 분산시스템을 설계할 때 생길 수 있는 여러 가지 문제점을 언급하고 그에 대한 Coord를 사용한 알고리즘을 해결책으로 제시한다. 이러한 설계를 바탕으로 실제 ACM논문 검색 시스템을 제작하여 운용한 예를 보인다. 또한, 본 논문이 제안한 시스템이 오픈소스 라이브러리 활용의 실례로써 Coord 및 여타 오픈소스 커뮤니티에 일조함을 기대할 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.548-551
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• 2016

기존 그리드 기반의 전통적인 RDBMS는 비구조적 데이터에 대한 색인이 지원되지 않았다. 이러한 제약 조건들로 인해 파일 문서 및 비 구조화된 데이터의 검색 엔진으로는 부적합하였다. 최근에 다양한 검색 오픈소스(Solr, Lucene)등으로 검색 엔진이 개발되어 활용되고 있지만, 검색한 결과와 기존 데이터의 연동이 쉽지 않고 구조 변경이 어려우며, 사용자의 다양한 요구 사항 수용이 쉽지 않은 단점을 가지고 있다. 따라서 본 연구에서는 빠른 검색을 위한 색인 (index) 최적화와 대용량 데이터 처리를 위한 파티션 기반 데이터의 분할 및 정복 (divide and conquer) 처리, 이중화된 검색어 색인 기능을 구현하였다. 또한 동의어 사전을 구축하여 연관 관계 분석이 가능하도록 DB를 구축하여 검색어와 동의어의 상호 관계성을 유지하였으며 오픈 소스보다 발전한 형태의 검색 엔진을 개발하는 것을 목표로 하였다. 본 연구를 위해 약 400만건 이상의 다양한 포맷 (Ms-office, Hwp, Pdf, Text)등의 파일 문서를 샘플로 실험을 진행하였다.