• Journal of Korean Library and Information Science Society
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• v.21
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• pp.57-86
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• 1994

The purpose of the study is to understand the research trends in the hypertext information retrieval. Around 30 related papers were investigated, from which three distinctive streams of research trends are grasped: 1) a trend of incorporating the traditional retrieval models, especially the query-based searching model into the hypermedia system. 2) a trend of a n.0, pplying the hypermedia system as an interface to the OPAC system, 3) a trend of incorporating the artificial intelligence techniques into the hypermedia techniques. The research on the hypermedia is going on, and the research directions will be increasingly intend to incorporate the traditional retrieval models and artificial intelligence techniques into the hypermedia system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2612-2633
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• 2020

Due to the explosive growth of multimedia speech data, how to protect the privacy of speech data and how to efficiently retrieve speech data have become a hot spot for researchers in recent years. In this paper, we proposed an encrypted speech retrieval scheme based on long short-term memory (LSTM) neural network and deep hashing. This scheme not only achieves efficient retrieval of massive speech in cloud environment, but also effectively avoids the risk of sensitive information leakage. Firstly, a novel speech encryption algorithm based on 4D quadratic autonomous hyperchaotic system is proposed to realize the privacy and security of speech data in the cloud. Secondly, the integrated LSTM network model and deep hashing algorithm are used to extract high-level features of speech data. It is used to solve the high dimensional and temporality problems of speech data, and increase the retrieval efficiency and retrieval accuracy of the proposed scheme. Finally, the normalized Hamming distance algorithm is used to achieve matching. Compared with the existing algorithms, the proposed scheme has good discrimination and robustness and it has high recall, precision and retrieval efficiency under various content preserving operations. Meanwhile, the proposed speech encryption algorithm has high key space and can effectively resist exhaustive attacks.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.243-253
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• 2009

For the last 14 years, space-borne satellite SAR system such as RADARSAT-1, ERS-2, and ENVISAT ASAR have provided a continuous observation over the ocean. However, the data acquired from those systems were limited to C-band frequency until the advent of the first spacebome German X-band SAR system TerraSAR-X in 2007. Korea is also planning to launch the nation's first X-band SAR satellite (KOMPSAT-5) in 2010. It is timely and necessary to develop X-band models for estimating geophysical parameters from these X-band SAR systems. In this study, X-band wind retrieval model was investigated and developed based on numerical ocean scattering model (radar backscattering model and hydrodynamic interaction model). Although these models have not yet been tested and validated for broad ranges of wind conditions, the estimated wind speeds from TerraSAR-X data show generally good agreement with in-situ measurements.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1089-1099
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• 2013

The Bradley-Terry model is widely used for analysis of pairwise preference data. We explain that the popularity of Bradley-Terry model is gained due to not only easy computation but also some nice asymptotic properties when the model is misspecified. For information retrieval required to analyze big ranking data, we propose to use a pseudo likelihood based on the Bradley-Terry model even when the true model is different from the Bradley-Terry model. We justify using the Bradley-Terry model by proving that the estimated ranking based on the proposed pseudo likelihood is consistent when the true model belongs to the class of Thurstone models, which is much bigger than the Bradley-Terry model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.541-546
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• 2009

There are many videos about sports. There is a large need for content based video retrievals. In sports videos, the motions and camera works have much information about shots and plays. This paper proposes the baseball game process understanding using the similar motion retrieval on videos. We can retrieve the similar motion parts based on motions shown in videos using the space-time images describing the motions. Using a finite state model of plays, we can decide the precise point of pitches from the pattern of estimated typical motions. From only the motions, we can decide the precise point of pitches. This paper describes the method and the experimental results.

• Journal of the Korean Society for information Management
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• v.10 no.1
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• pp.53-63
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• 1993

The conventional fuzzy set model has been criticized as a retrieval model because the MIN and MAX operators have the properties adverse to effective calculation of document values. Since the first introduction of fuzzy set theory a variety of fuzzy operators have been developed, which can replace the MIN and MAX operators. We analyze their behavioral aspects of generating document values, and propose the enhanced fuzzy set model based on a class of fuzzy operators called positively compensatory operators. We also show through performance experiments that the proposed fuzzy set model provides higher retrieval effectiveness.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.577-590
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• 2003

The shape-based retrieval is defined as the operation that searches for the (sub) sequences whose shapes are similar to that of a query sequence regardless of their actual element values. In this paper, we propose a similarity model suitable for shape-based retrieval and present an indexing method for supporting the similarity model. The proposed similarity model enables to retrieve similar shapes accurately by providing the combination of various shape-preserving transformations such as normalization, moving average, and time warping. Our indexing method stores every distinct subsequence concisely into the disk-based suffix tree for efficient and adaptive query processing. We allow the user to dynamically choose a similarity model suitable for a given application. More specifically, we allow the user to determine the parameter p of the distance function $L_p$ when submitting a query. The result of extensive experiments revealed that our approach not only successfully finds the subsequences whose shapes are similar to a query shape but also significantly outperforms the sequence search.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.38-46
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• 2017

In this study, a query language was developed to supplement the information retrieval and model regeneration in the case of Industry Foundation Classes (IFC)-based civil infrastructure information models. First, the IFC objects to represent the structural components, entities to manage the related properties, and relationships to connect with the mentioned elements were analyzed in a point of information flow. The results confirmed that the end-users could have problems with access and comprehend the properties and its relationships in the IFC file. Second, the IfcPropertySet-focused query method and applicable stand-alone module were proposed referring to the previous Building Information Model Query Language (BimQL). The availabilities of the proposed method were examined using the rail and sleeper information models through information retrieval and model regeneration. The most important advantage of the proposed approach is the IFC-based information retrievals that can guarantee the interoperability between software packages.

• Korean Journal of Biological Psychiatry
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• v.14 no.1
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• pp.61-67
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• 2007

Objectives : The purpose of this study was to test stage model in Traumatic Brain Injury(TBI) patients. According to the stage model, attention deficits which is basic stage in information processing lead to memory disturbance and subsequently affect higher-order cognitive function such as memory, decision-making, abstract thinking, and judgement related to executive function. Therefore, it was hypothesized that attention affect recall(retrieval efficacy) related to executive function mostly relative to other cognitive function, in TBI patients with low executive function. Methods : Participants were referred to a TBI clinic and then was rated on K-WAIS and Executive Intelligence Test(EXIT). Participants were divided into two groups according to Executive IQ(EIQ) score, which of high function group(N=67) was more than 80(above low average) and of low function group(N=52) was under 80 (under borderline). To test the stage model, using hierarchical regression analysis, recall(retrieval efficacy) was regressed on 3 subscales(attention, verbal, visuospatial scale) after controlling for IQ according to each group. Furthermore, the mediation effect of attention between retrieval efficacy and verbal, visuospatial score was analyzed. Results : In the low function group, only attention area predicted significantly recall(retrieval efficacy), indicating that lower attention were related to lower EIQ after controlling for IQ. In the high function group, no area predicted significantly retrieval efficacy. In the low function group, verbal and visuospatial scale did not predicted significantly retrieval efficacy, indicating that there was no evidences supporting the mediation model. Conclusion : Only attention affect retrieval efficacy in TBI patients with low executive function. But, the mediation effect of attention between retrieval efficacy and verbal and visuospatial scale was not tested in the low function group. These results implied that stage model was tested partially. In treating cognitive deficit in TBI patients, it is necessary to develop cognitive rehabilitation program based on stage model. Furthermore, it is necessary to necessary to test mediation model in the future study.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.103-120
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• 2007

Node is the semantic unit and a part of structured document. Information retrieval from structured documents offers an opportunity to go subdivided below the document level in search of relevant information, making any element in an structured document a retrievable unit. The node-based document retrieval constitutes several similarity calculating methods and the extended node retrieval method using structure information. Retrieval performance is hardly influenced by the methods for determining document similarity The extended node method outperformed the others as a whole.