• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.51-63
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• 2001

In this paper, we design and implement a XML document retrieval system to support structure-based retrieval using the BRS/Search system that is a commercial search engine, The implemented system in this paper represents the logical structure of XML documents as the directory structure of the Unix file system. In addition, we define the database schema of BRS/Search system to store documents, We also implement a ETID extractor, a structure information extractor, a storage manager and a query processor additionally to support content retrieval, structure retrieval, mixed retrieval and attribute retrieval in the BRS/Search system.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.209-226
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• 2007

XML documents format on the Web provides a mechanism to impose their content and logical structure information. Therefore, an XML processor provides access to their content and structure. The purpose of this study is to investigate the usefulness of structural hints in the leaf node language model-based XML document retrieval. In order to this purpose, this experiment tested the performances of the leaf node language model-based XML retrieval system to compare the queries for a topic containing only content-only constraints and both content constrains and structure constraints. A newly designed and implemented leaf node language model-based XML retrieval system was used. And we participated in the ad-hoc track of INEX 2005 and conducted an experiment using a large-scale XML test collection provided by INEX 2005.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.451-460
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• 2001

In this paper, we propose an indexing model for efficient structure retrieval of XML documents. The proposed indexing model consists of structured information that supports a wide range of queries such as content-based queries and structure-attribute queries at all levels of the document hierarchy and index organizations that are constructed based on the information. To support structured retrieval, a new representation method for structured information is presented. Using this structured information, we design content index, structure index, and attribute index for efficient retrieval. also, we explain processing procedures for mixed queries and evaluate the performance of proposed indexing model. It is shown that the proposed indexing model achieves better retrieval performance than the existing method.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.601-616
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• 2004

Information retrieval systems for structured documents provide multiple levels of retrieval capability by supporting structure-based queries. In order to process structure-based queries for structured documents, information for structural nesting relationship between elements and for element sequence must be maintained. This paper presents four index structures that can process various query types about structures such as structural relationships between elements or element occurrence order. The proposed algorithms are based on the concept of Global Document Instance Tree.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.678-691
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• 2000

A variety of multimedia applications require multimedia database management systems to manage multimedia data, such as text, image, and video, as well as t support content-based image or video retrieval. In this paper we design and implement a content-based image retrieval system, BADA-IV/I$^2$R(Image Information Retrieval), which is developed based on BADA-IV multimedia database management system. In this system image databases can be efficiently constructed and retrieved with the visual features, such as color, shape, and texture, of image. we extend SQL statements to define image query based on both annotations and visual features of image together. A high-dimensional index structure, called CIR-tree, is also employed in the system to provide an efficient access method to image databases. We show that BADA-IV/I$^2$R provides a flexible way to define query for image retrieval and retrieves image data fast and effectively: the effectiveness and performance of image retrieval are shown by BEP(Bull's Eye Performance) that is used to measure the retrieval effectiveness in MPEG-7 and comparing the performance of CIR-tree with those of X-tree and TV-tree, respectively.

• ETRI Journal
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• v.28 no.3
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• pp.337-346
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• 2006

In this paper, we propose a new language model, namely, a dependency structure language model, for information retrieval to compensate for the weaknesses of unigram and bigram language models. The dependency structure language model is based on the first-order dependency model and the dependency parse tree generated by a linguistic parser. So, long-distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model, where the dependency structure model gives a better performance than recently proposed language models and the Okapi BM25 method, and the dependency structure is more effective than unigram and bigram in language modeling for information retrieval.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2407-2424
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• 2022

Recently, Transformer has made great progress in video retrieval tasks due to its high representation capability. For the structure of a Transformer, the cascaded self-attention modules are capable of capturing long-distance feature dependencies. However, the local feature details are likely to have deteriorated. In addition, increasing the depth of the structure is likely to produce learning bias in the learned features. In this paper, an improved Transformer structure named TransDCS (Transformer with Dynamic Convolution and Shortcut) is proposed. A Multi-head Conv-Self-Attention module is introduced to model the local dependencies and improve the efficiency of local features extraction. Meanwhile, the augmented shortcuts module based on a dual identity matrix is applied to enhance the conduction of input features, and mitigate the learning bias. The proposed model is tested on MSRVTT, LSMDC and Activity-Net benchmarks, and it surpasses all previous solutions for the video-text retrieval task. For example, on the LSMDC benchmark, a gain of about 2.3% MdR and 6.1% MnR is obtained over recently proposed multimodal-based methods.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3469-3476
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• 1999

In spatial database based on spatial data structures, instead of one-dimensional indexing structure, new indexing structure which corresponds to multi-dimensional features of spatial objects is required. In order to meet those requirements, in this paper we proposed new indexing structure for efficient retrieval of spatial database by carrying through the feature analysis of conventional multi-dimensional indexing structures. To improve the sequential search method of supernodes in the conventional X-tree and to reduce the retrieval time in case of generating the huge supernode, we proposed a indexing structure integrating the kd-tree based on point index structure into the X-tree. We implemented the proposed indexing structure and analyzed its retrieval time according to the dimension and distribution of experimental data.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1357-1366
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• 2004

As the importance or XML is increasing to manage information and exchange data efficiently in the web, there are on going works about structural integration and retrieval. The XML. document with the defined structure can retrieve the structure through the DTD or XML schema, but the existing method can't apply to XML. documents which haven't the structure information. Therefore. in this paper we propose a new clus-tering technique at a basic research which make it possible to retrieve structure fast about the XML documents that haven't the structure information. We first estract the feature of frequent structure from each XML document. And we cluster based on the similar structure by con-sidering the frequent structure as representative structure of the XML document, which makes it possible to retrieve the XML document raster than dealing with the whole documents that have different structure. And also we perform the structure retrieval about XML documents based on the clusters which is the group of similar structure. Moreover, we show efficiency of proposed method to describe how to apply the structure retrieval as well as to display the example of application result.