• Title/Summary/Keyword: retrieval effectiveness

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Evaluation of the Newspaper Library -With Emphasis on the Document Delivery Capability and Retrieval Effectivenss- (신문사 자료실에 대한 평가 -문헌전달능력과 검색효율을 중심으로-)

  • 노동조
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.7 no.1
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    • pp.319-351
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    • 1994
  • This rearch is a case study for the newspaper libraries in Seoul and the primary purpose of the this study are to investigate its document delivery capability. To achieve the above-mentioned purpose, representative rsers visited seven the newspaper library and checked their searching time. Document delivery capability was checked by units of hour, minute, second(searching time). Retrieval effectiveness was tested through the recall ratio and the precision ratio. The major findings of the study are summarized as follows: 1) Most of the newspaper libraries excellent to the document delivery capability; 6 newspaper libraries deliverived the data related subject. 2) The newspaper libraries were came out 50.1% the mean recall ratio and 84.8% the mean precision ratio about the all materials. 3) Concerned their own articles, the newspaper libraries showed 71.4% the recall ratio and 90.0% the precision ratio. That moaned their own articles were more effectived than others. 4) The Kookmin Ilbo library had the most excellent system, and the precision ratio of The Dong-A Ilbo library prior to the recall ratio. The Han Kyoreh Shinmun library had a excellent arragement in own articles, but The Segye Times library had problem in every parties.

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Similarity Assessment for Geometric Query on Mechanical Parts (기계부품의 형상검색은 위한 유사성 평가방법)

  • 김철영;김영호;강석호
    • Korean Journal of Computational Design and Engineering
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    • v.5 no.2
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    • pp.103-112
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    • 2000
  • CAD databases are the core element to the management of product information. A key to the successful use of the databases is a rational method of query to and retrieval from the databases. Although it is parts geometry that users eager to retrieve from the CAD databases, no system yet supports geometry-based query. This paper aims at developing a new method of assessing geometric similarity which can serve as the basis of geometric query for CAD database. The proposed method uses ASVP (Alternating Sums of Volumes with Partitioning) decomposition that is a volumetric representation of a part obtained from its boundary representation. A measure of geometric similarity between two solid models is defined on their ASVP tree representations. The measure can take into account overall shapes of parte, shapes of features and their locations. Several properties that a similarity measure needs to satisfy are discussed. The geometric query developed in this paper can be used in a wide range of applications using CAD databases, which include similarity-based design retrieval, variant process planning, and components selection from part library. An experiment has been carried out to demonstrate the effectiveness of the method, and the results are presented.

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A Study on the Pivoted Inverse Document Frequency Weighting Method (피벗 역문헌빈도 가중치 기법에 대한 연구)

  • Lee, Jae-Yun
    • Journal of the Korean Society for information Management
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    • v.20 no.4 s.50
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    • pp.233-248
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    • 2003
  • The Inverse Document Frequency (IDF) weighting method is based on the hypothesis that in the document collection the lower the frequency of a term is, the more important the term is as a subject word. This well-known hypothesis is, however, somewhat questionable because some low frequency terms turn out to be insufficient subject words. This study suggests the pivoted IDF weighting method for better retrieval effectiveness, on the assumption that medium frequency terms are more important than low frequency terms. We thoroughly evaluated this method on three test collections and it showed performance improvements especially at high ranks.

Document ranking methods using term dependencies from a thesaurus (시소러스의 연관성 정보를 이용한 문서의 순위 결정 방법)

  • 이준호
    • Journal of the Korean Society for information Management
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    • v.10 no.2
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    • pp.3-22
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    • 1993
  • In recent years various document ranking methods such as Relevance. R-Distance and K-Distance have been developed wh~ch can be used in thesaurus-based boolean retrieval systems. They give high quality document rankings in many cases by using term dependence lnformatlon from a thesaurus. However, they suffer from several problems resulting from inefficient and Ineffective evaluation of boolean operators AND. OR and NOT. In this paper we propose new thesaurus-based document ranking methods called KB-FSM and KB-EBM by exploitmg the enhanced fuzzy set model and the extended boolean model. The proposed methods overcome the problems of the previous methods and use term dependencies from a thesaurs effectively. We also show through performance comparison that KB-FSM and KBEBM provide higher retrieval effectiveness than Relevance. R-D~stance and K-Distance.

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Contents Analysis and Synthesis Scheme for Music Album Cover Art

  • Moon, Dae-Jin;Rho, Seung-Min;Hwang, Een-Jun
    • Journal of IKEEE
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    • v.14 no.4
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    • pp.305-311
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    • 2010
  • Most recent web search engines perform effective keyword-based multimedia contents retrieval by investigating keywords associated with multimedia contents on the Web and comparing them with query keywords. On the other hand, most music and compilation albums provide professional artwork as cover art that will be displayed when the music is played. If the cover art is not available, then the music player just displays some dummy or random images, but this has been a source of dissatisfaction. In this paper, in order to automatically create cover art that is matched with music contents, we propose a music album cover art creation scheme based on music contents analysis and result synthesis. We first (i) analyze music contents and their lyrics and extract representative keywords, (ii) expand the keywords using WordNet and generate various queries, (iii) retrieve related images from the Web using those queries, and finally (iv) synthesize them according to the user preference for album cover art. To show the effectiveness of our scheme, we developed a prototype system and reported some results.

Analysis and Localization of freeWAIS-sf (FreeWAIS-sf의 분석 및 한글화)

  • O, Jeong-Seok;Kim, Ji-Seung;Lee, Jun-Ho;Lee, Sang-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.5
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    • pp.611-618
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    • 1999
  • An efficient and effective access to needed information becomes an important factor in the modern information society. Many people have developed information retrieval (IR) systems that retrieve needed information from a large amount of data at a given time. However, most freely available IR systems have been developed for English text rather than for Korean text. In this research, we have analyzed the IR system freeWAIS-sf, and localized it with the Korean morphological analyzer, namely HAM. The localized freeWAIS-sf can handle both English text and Korean text simultaneously. We have also modified the weighting scheme of freeWAIS-sf. The experimental result shows that the modified weighting scheme outperforms the original one in terms of retrieval effectiveness.

Convolutional Neural Network Based Multi-feature Fusion for Non-rigid 3D Model Retrieval

  • Zeng, Hui;Liu, Yanrong;Li, Siqi;Che, JianYong;Wang, Xiuqing
    • Journal of Information Processing Systems
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    • v.14 no.1
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    • pp.176-190
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    • 2018
  • This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

Improving Retrieval Effectiveness with Multiple Query Combination (다중 질의 결합을 통한 검색 효과의 개선)

  • Lee Kyi-Ho;Lee Joon-Ho;Lee Kyu-Chul
    • Journal of the Korean Society for Library and Information Science
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    • v.31 no.3
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    • pp.135-146
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    • 1997
  • Different users or the same user using controlled versus free-text vocabularies could generate different queries for the same information need. It has been known in the information retrieval literature that different query representations may retrieve different sets of documents. In this paper, we first generate multiple query vectors from a given information problem by using different relevance feedback methods. Then, we combine the multiple query vectors into a single query vector. We also show through experiments that significant improvements can be achieved by the combination of the multiple query vectors.

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Ship's Collision Avoidance Support System Using Fuzzy-CBR

  • Park, Gyei-Kark;Benedictos John Leslie RM.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.635-641
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    • 2006
  • Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and infer the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

Building of Collision Avoidance Algorithm based on CBR

  • Park Gyei-Kark;Benedictos John Leslie RM
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.39-44
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    • 2006
  • Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning(CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and index the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

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