• Journal of the Korea Society of Computer and Information
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• v.3 no.1
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• pp.35-46
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• 1998

In the Information Retrieval System. the relevance of retrieved items is determined by the judgement of the user and thus the evaluation of the system efficiency counts on the cognizance of users to some extent. The relevance feedback mechanism provides a device allowing iterative searches during which the query can be modified and refined based on user input from the relevant documents. The feedback system are generally reported to outperform non-feedback systems. The procedures and algorithms to implement the feedback mechanism are surveyed in this paper.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.375-377
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• 2010

본 연구는 병원에서 제공하는 정보 및 세미나를 필요로 하는 환자들의 우선순위 검색과 검색 결과 내의 인원별, 지역별 등의 연관검색이 가능하도록 하는 병원 고객관리시스템 설계를 목적으로 한다.

• Land and Housing Review
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• v.1 no.1
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• pp.1-7
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• 2010

Case-based reasoning (CBR) method can make estimators understand the estimation process more clearly. Thus, CBR is widely used as a methodology for cost estimation. In CBR, the quality of case retrieval affects the relevance of retrieved cases and hence the overall quality of the reminding capability of CBR system. Thus, it is essential to retrieve relevant past cases for establishing a robust CBR system. Case retrieval needs the following tasks to obtain appropriate case(s); indexing, search, and matching (Aamodt and Plaza 1994). However, the previous CBR researches mostly deal with matching process that has limits such as accuracy and efficiency of case retrieval. In order to address this issue, this research presents a CBR cost model for building projects that has two-step retrieval process: decision tree and nearest neighbor methods. Specifically, the proposed cost model has indexing, search and matching modules. Features in the model are divided into shape-based and scale-based attributes. Based on these, decision tree is established for facilitating the search task and nearest neighbor method was utilized for matching task. In regard to applying nearest neighbor method, attribute weights are assigned using GA optimization and similarity is calculated using the principle of distance measuring. Thereafter, the proposed CBR cost model is developed using 174 cases and validated using 12 test cases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.15-19
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• 2012

A Domain Dictionary generation algorithm based on pseudo feedback model is presented in this paper. This algorithm can increase the precision of domain dictionary generation algorithm. The generation of Domain Dictionary is regarded as a domain term retrieval process: Assume that top N strings in the original retrieval result set are relevant to C, append these strings into the dictionary, retrieval again. Iterate the process until a predefined number of domain terms have been generated. Experiments upon corpus show that the precision of pseudo feedback model based algorithm is much higher than existing algorithms.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.20-27
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• 2006

In this paper we constructed semantic net that can efficiently conform retrieval and reuse of object-oriented source code. In order that initial relevance of semantic net was constructed using thesaurus to represent concept of object-oriented inheritance between each node. Also we made up for the weak points in spreading activation method that use to activate node and line of semantic net and to impulse activation value. Therefore we proposed the method to enhance retrieval time and to keep the quality of spreading activation.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10b
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• pp.523-525
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• 1998

소프트웨어 개발의 생산성과 신뢰성을 향상시키기 위해 소프트웨어 재사용이 필요하며, 소프트웨어 재사용에서는 원하는 부품을 정확하고 신속하게 검색하는 것이 매우 중요하다. 본 논문에서는 재사용 라이브러리에서 재사용 부품 추출을 위하여 정보추출 기법의 질의어 최적화 과정에 시뮬레이티드 어닐링을 적용하였다. 최적화 과정은 적합성 피이드백(relevance feedback)과 벡터 공간 모델을 적용하여 선형추출(linear retrieval)을 할 때 질의어 용어 가중치를 최적화 하는 것으로써, 실험을 통하여 최적화한 질의어의 추출효과도(retrieval effectiveness)척도가 최적화 하지 않은 경우의 척도보다 결과가 매우 좋다는 것을 보인다. 그리고 언덕 오르기(Hill-climbing)알고리즘을 사용한 방법과 비교, 분석한다.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

• Journal of the Korean Society for information Management
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• v.25 no.2
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• pp.49-68
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• 2008

In many information retrieval experiments, the data fusion techniques have been used to achieve higher effectiveness in comparison to the single evidence-based retrieval. However, there had not been many image retrieval studies using the data fusion techniques especially in combining retrieval results based on multiple retrieval methods. In this paper, we describe how the image retrieval effectiveness can be improved by combining two sets of the retrieval results using the Sobel operator-based edge detection and the Self Organizing Map(SOM) algorithms. We used the clip art images from a commercial collection to develop a test data set. The main advantage of using this type of the data set was the clear cut relevance judgment, which did not require any human intervention.

• Journal of the Korean Society for information Management
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• v.17 no.1
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• pp.103-127
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• 2000

This study compared finding economic and energy information on the WWW to finding the same information on DIALOG, a traditional search service. Professional searchers answered 20 questions for end users using either of DIALOG and one Internet database (general search engine or Web database). The relevance of the results in both sets of answers was ranked by searchers and end-users, respectively. The study found that searching for information on the Web took at least twice as long as it did when using DIALOG. Relevance rating was a little higher for materials found on DIALOG. However, the relevance rating difference between two systems was not so higher than we expected. From the research results, we conclude that Internet database including Web database and general search engines is providing valuable information of economic and energy subject areas.

• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.417-455
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• 2003

Ontologies are formal theories that are suitable for implementing the semantic web. which is a new technology that attempts to achieve effective retrieval, integration, and reuse of web resources. Ontologies provide a way of sharing and reusing knowledge among people and heterogeneous applications systems. The role of ontologies is that of making explicit specified conceptualizations. In this context, domain and generic ontologies can be shared, reused, and integrated in the analysis and design stage of information and knowledge systems. This study aims to design an ontology for international organizations. and build an Internet web retrieval system based on the proposed ontology. and finally conduct an experiment to compare the system performance of the proposed system with that of internet search engines focusing relevance and searching time. This study found that average relevance of ontology-based searching and Internet search engines are 4.53 and 2.51, and average searching time of ontology-based searching and Internet search engines are 1.96 minutes and 4.74 minutes.