• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.56-63
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• 2024

Despite the rapid strides in content-based image retrieval, a notable disparity persists between the visual features of images and the semantic features discerned by humans. Hence, image retrieval based on the association of semantic similarities recognized by humans with visual similarities is a difficult task for most image-retrieval systems. Our study endeavors to bridge this gap by refining image semantics, aligning them more closely with human perception. Deep learning techniques are used to semantically classify images and retrieve those that are semantically similar to personalized images. Moreover, we introduce a keyword-based image retrieval, enabling automatic labeling of images in mobile environments. The proposed approach can improve the performance of a mobile device with limited resources and bandwidth by performing retrieval based on the visual features and keywords of the image on the mobile device.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1498-1504
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• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Journal of the Korean Mathematical Society
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• v.36 no.3
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• pp.609-619
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• 1999

We give a mathematically rigorous description of the recently popular latent semantic indexing (LSI) method in text information retrieval theory. Also, a related problem of finding a document ranking function in linear relevance feedback is discussed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.14 no.1
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• pp.219-230
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• 2003

The purpose of this study is to improve of retrieval effectiveness to clustered and filtered document through query expansion. The result of this research prove that extended queries and documents, information in encyclopedia, clustering and filtering techniques are effective to promote retrieval effectiveness.

• Journal of the Korean Society for information Management
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• v.22 no.2 s.56
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• pp.41-56
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• 2005

For the purpose of extending the Web that is able to understand and process information by machine, Semantic Web shared knowledge in the ontology form. For exquisite query processing, this paper proposes a method to use semantic relations in the ontology as relevance feedback information to query expansion. We made experiment on pharmacy domain. And in order to verify the effectiveness of the semantic relation in the ontology, we compared a keyword based document retrieval system that gives weights by using the frequency information compared with an ontology based document retrieval system that uses relevant information existed in the ontology to a relevant feedback. From the evaluation of the retrieval performance. we knew that search engine used the concepts and relations in ontology for improving precision effectively. Also it used them for the basis of the inference for improvement the retrieval performance.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.345-366
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• 2011

The law affects our daily lives, and hence, constitutes a crucial information resource. However, electronic access to legal information using keyword-based retrieval systems appears to provide users with limited satisfaction. There are many factors behind this inadequacy. First, the discrepancies between formal legal terms and their counterparts in common language are quite large. Second, the situation is further confounded by frequent abbreviations in legal terms. Third, even though there is a constant deluge of legal information, users' needs have evolved to demand more Q and A type searches. All of these factors make the existing retrieval systems inefficient and ineffective. This article suggests an ontology-based system as a means to deal with such difficulties. To that end, a legal retrieval system(experimental system), built on the basis of a newly-constructed law ontology, was tested against a keyword-based legal retrieval system(existing one), yielding data on their relative effectiveness in retrieval and user satisfaction.

• 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.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.3
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• pp.21-31
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• 2020

The study examined information retrieval tools as predictors for information resources utilization, four research questions, and four hypotheses were made to guide the study. A descriptive survey was adopted for the study. Random sampling technique was used to select sample of 393 from a population of 557 academic staff registered in the University of Port Harcourt library. The questionnaire was adopted as a data collection instrument titled Information retrieval as predictors for information resources utilization (IRPIRUQ). Data were analyzed using both simple and multiple regression while analysis of variance (ANOVA) associate with regression was used for testing the hypotheses at 0.05 alpha level. The study revealed that information resources are under utilized as the OPAC and Online Databases are not easily accessed. Further findings showed that the academic staff made use of internet search engines more often than the OPAC and online databases. It was recommended among others that a new library software be installed in place of KOHA for wider connectivity and adequate distribution of software that will aid usage of the online databases and OPAC.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.1-16
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• 2005

When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. Accordingly, this study suggests the re-ranking retrieval model which reflects the content based similarity between user's inquiry terms and index words by grasping the document knowledge structure. In order to accomplish this, the former constructs a thesaurus and similarity relation matrix to provide the subject analysis mechanism and the latter propose the algorithm which establishes a search model such as query expansion in order to analyze the user's demands. Therefore, the algorithm that this study suggests as retrieval utilizing the information structure of a retrieval system can be content-based retrieval mechanism to establish a 2-step search model for the preservation of recall and improvement of accuracy which was a weak point of the previous fuzzy retrieval model.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3762-3774
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• 2000

The advances of computer hardware and information processing technologies raise the needs of multimedia information retrieval systems. Up to date. multimedia information systems have been developed for text information and image information. Nowadays. the multimedia information systems for video and audio information. especially for musical information have been grown up more and more. In recent music information retrieval systems. not only the information retrieval based on meta-information such like composer and title but also the content-based information retrieval is supported. The content-based information retrieval in music information retrieval systems utilize the similarity value between the user query and the music information stored in music database. In tbis paper. hence. we developed a similarity computation algorithm in which the pitches and lengths of each corresponding pair of notes are used as the fundamental factors for similarity computation between musical information. We also make an experiment of the proposed algorithm to validate its appropriateness. From the experimental results. the proposed similarity computation algorithm is shown to be able to correctly check whether two music files are analogous to each other or not based on melodies.