• Title/Summary/Keyword: Retrieval Model

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Case-Based Reasoning Cost Estimation Model Using Two-Step Retrieval Method

  • Lee, Hyun-Soo;Seong, Ki-Hoon;Park, Moon-Seo;Ji, Sae-Hyun;Kim, Soo-Young
    • 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.

A Study on the Reformation of the Education Model of Information Retrieval (정보검색 교육의 개선방안 연구)

  • 고영만
    • Journal of the Korean Society for information Management
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    • v.15 no.3
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    • pp.113-132
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    • 1998
  • The purpose of this study is to suggest a new educational model of information retrieval suited to the practical needs. For this, technical, methodological, social, and economic changes of information retrieval environment are analysed and the required roles for the information retrieval services are evaluated. In addition, this study investigated the educational situation of the subject of information retrieval at 32 universities and 2 institutions. The findings suggest that the subject of information retrieval should be seperated into theoretical instruction and practical hours in order to meet the new requirements.

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Expected Waiting Times for Storage and Retrieval Requests in Automated Storage and Retrieval Systems (자동창고의 저장 및 불출요구의 대기시간에 관한 연구)

  • Cho, Myeonsig;Bozer, Yavuz A.
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.4
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    • pp.306-316
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    • 2004
  • We present a closed form approximate analytical model to estimate the expected waiting times for the storage and retrieval requests of an automated storage/retrieval (AS/R) system, assuming that the storage/retrieval (S/R) machine idles either at the rack or at the input/output point. The expected waiting times (and the associated mean queue lengths) can play an important role to decide whether the performance of a stable AS/R system is actually acceptable, to determine buffer size (or length) of the input conveyor, and to compute the number of the rack openings which is required to hold the loads which are requested by processing machines but waiting in the rack to be retrieved by the SIR machine. This model can be effectively used in the early design stage of an AS/R system.

Language Modeling Approaches to Information Retrieval

  • Banerjee, Protima;Han, Hyo-Il
    • Journal of Computing Science and Engineering
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    • v.3 no.3
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    • pp.143-164
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    • 2009
  • This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and future trends.

Hybrid Video Information System Supporting Content-based Retrieval and Similarity Retrieval (비디오의 의미검색과 유사성검색을 위한 통합비디오정보시스템)

  • Yun, Mi-Hui;Yun, Yong-Ik;Kim, Gyo-Jeong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.8
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    • pp.2031-2041
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    • 1999
  • In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

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A Study on Fuzzy Ranking Model based on User Preference (사용자 선호도 기반의 퍼지 랭킹모델에 관한 연구)

  • Kim Dae-Won
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.05a
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    • pp.94-95
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    • 2006
  • A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

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A Study on Fuzzy Ranking Model based on User Preference

  • Kim Dae-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.3
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    • pp.326-331
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    • 2006
  • A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. In this study we develop a new fuzzy ranking model based on the user preference. Through the experiments on the TREC-2 collection of Wall Street Journal documents, we show that the proposed method outperforms the conventional fuzzy ranking models.

A Solution Procedure for Designing Automated Storage/Retrieval Systems (자동창고 설계를 위한 최적화 모델 및 해법에 관한 연구)

  • 나윤균
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.18 no.34
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    • pp.9-14
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    • 1995
  • A cost minimization model for designing AS/RS (Automated Storage/Retrieval Systtems) has been developed under the S/R (Storage/Retrieval) machine throughput rate and total storage capacity requirements. The objective function includes S/R machine cost storage rack cost, and interface conveyor cost. Since the model is a nonlinear integer programming problem which is very hard to solve with large problem size, the model is simplified using previous research results to be solved exactly and a simultion procedure is combined to verify that throughput rate requirements are satisfied.

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Cluster-based Information Retrieval with Tolerance Rough Set Model

  • Ho, Tu-Bao;Kawasaki, Saori;Nguyen, Ngoc-Binh
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.1
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    • pp.26-32
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    • 2002
  • The objectives of this paper are twofold. First is to introduce a model for representing documents with semantics relatedness using rough sets but with tolerance relations instead of equivalence relations (TRSM). Second is to introduce two document hierarchical and nonhierarchical clustering algorithms based on this model and TRSM cluster-based information retrieval using these two algorithms. The experimental results show that TRSM offers an alterative approach to text clustering and information retrieval.

XML Structured Model of Tree-type for Efficient Retrieval (효율적인 검색을 위한 Tree 형태의 XML 문서 구조 모델)

  • Kim Young-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.4 s.32
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    • pp.27-32
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    • 2004
  • A XML Document has a structure which may be irregular The irregular document structure is difficult for users to know exactly. In this paper, we propose the XML document model and the structure retrieval method for efficient management and structure retrieval of XML documents. So we use fixed-sized LETID having the information of element, describe the structured information retrieval algorithm for parent and child element to represent the structured information of XML documents. Using this method, we represent the structured information of XML document efficiently. We can directly access to specific clement by simple operation, and process various queries. We expect the method to support various structured retrieval of specific element such as parent, child. and sibling elements.

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