• Journal of Information Technology Services
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• v.7 no.4
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• pp.199-208
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• 2008

Tagging represents one of the Web 2.0 technology, and has an appropriate mechanism for the classification of dynamically changing Web informations. This technique is capable of searching the Web informations using the user specified tags, but still it has a limitation of providing only the limited informations to the tags. Therefore, in order to search the related informations easily, we need to extend this technique further to search not only the desired informations through the designated tags and also the related informations. In this paper, we first have designed and developed an algorithm that can get a desired tag cluster, which is capable of collecting the searched tags along with the related tags. We first performed a test to compare the difference between the user collected tag data through RSS and the reduced data. The second test focused on the accuracy of extracted related tags that depends on the similarity functions, such as the Pearson Correlation and Euclidean. Finally, we showed the final results visually using the graph algorithm.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.2
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• pp.291-311
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• 2015

This paper demonstrates the comparative analysis of the similarity and difference between Medical Subject Headings (MeSH) and social tags. Both types of metadata have the same purpose - that is, succinctly abstracting content of a given document - but are created from heterogeneous viewpoints. The former MeSH terms show the aspects of publication related professionals, whereas the latter social tags are from the perspectives of general readers. When both types of metadata are assigned to the same publications, do they consist of different nomenclatures reflecting the heterogeneous viewpoints or are they similar, since both metadata types describe the same publications? Social tags are also compared with family terms of MeSH terms in the given MeSH hierarchy, so as to understand the specificity of social tags, related to MeSH terms. Lastly, given the fact that readers assign social tags in casual ways without any restricted vocabulary, we tested how many social tags contain consumer health terms, which are familiar to laypeople. Through these comparisons, we ultimately aim to examine how much the highly controlled publication index reflects general readers' cognitive understandings and stress the necessity of general readers' involvement in the publication indexing process.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.399-416
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• 2009

In this study, clustering methods with related tags were discussed for improving search and exploration in the tag space. The experiments were performed on 10 Delicious tags and the strongly-related tags extracted by each 300 documents, and hierarchical and non-hierarchical clustering methods were carried out based on the tag co-occurrences. To evaluate the experimental results, cluster relevance was measured. Results showed that Ward's method with cosine coefficient, which shows good performance to term clustering, was best performed with consistent clustering tendency. Furthermore, it was analyzed that cluster membership among related tags is based on users' tagging purposes or interest and can disambiguate word sense. Therefore, tag clusters would be helpful for improving search and exploration in the tag space.

• MALSORI
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• v.68
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• pp.115-126
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• 2008

In this paper, we propose a vocabulary coverage improvement method for embedded continuous speech recognition (CSR) using knowledgebase. A vocabulary in CSR is normally derived from a word frequency list. Therefore, the vocabulary coverage is dependent on a corpus. In the previous research, we presented an improved way of vocabulary generation using part-of-speech (POS) tagged corpus. We analyzed all words paired with 101 among 152 POS tags and decided on a set of words which have to be included in vocabularies of any size. However, for the other 51 POS tags (e.g. nouns, verbs), the vocabulary inclusion of words paired with such POS tags are still based on word frequency counted on a corpus. In this paper, we propose a corpus independent word inclusion method for noun-, verb-, and named entity(NE)-related POS tags using knowledgebase. For noun-related POS tags, we generate synonym groups and analyze their relative importance using Google search. Then, we categorize verbs by lemma and analyze relative importance of each lemma from a pre-analyzed statistic for verbs. We determine the inclusion order of NEs through Google search. The proposed method shows better coverage for the test short message service (SMS) text corpus.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• Journal of Internet Computing and Services
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• v.11 no.3
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• pp.15-24
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• 2010

In this paper, we propose an image classification which combines semantic relations of tags with contents of images to improve the satisfaction of image retrieval on application domains as huge image sharing sites. To make good use of image retrieval or classification algorithms on huge image sharing sites as Flickr, they are applicable to real tagged Web images. To classify the Web images by 'bag of visual word' based image content, our algorithm includes training the category model by utilizing the preliminary retrieved images with semantically related tags as training data and classifying the test images based on PLSA. In the experimental results on the Flickr Web images, the proposed method produced the better precision and recall rates than those from the existing method using tag information.

• Journal of Magnetics
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• v.20 no.3
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• pp.295-301
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• 2015

We evaluated certain issues related to magnetic resonance imaging (MRI) coupled with the use of active 2.5 GHz radio frequency identification (RFID) tags for patient identification using low field (0.3 T) MRI and computed tomography (CT) scans. We also investigated the performance of the RFID reader located outside the MRI room by considering several factors. A total of ten active RFID tags were exposed to several MRI sequences and X-rays of CT scan. We found that only card type active RFID tags are suitable for patient identification purpose in MRI environment and both wristbands as well as card tags were suitable for the same in CT environment. Severe artifacts were found in the captured MRI and CT images when the area of the imaging was in proximity to the tags. No external factors affected the performance of active RFID reader stationed outside the MRI scan room.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1305-1314
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• 2013

The existing tag based system deducts a retrieval result with low accuracy through the usage of a single tag matching by using tags tagged in contents. And the system doesn't provide effectively contents related information which the tags have, as the users place tags on contents without considering the priority and associative relation between tags. For a solve of above problems, this paper suggests a tag ranking system which extracts semantic similarity between tags and re-ranks the tags tagged in contents. In order to evaluate the performance of suggested system, this paper experiments and compares the ranking result of this paper's tag ranking system with the result of baseline method using tags tagged in images and frequency method adapting tag co-appearance frequency.

• Journal of the Korean Society for information Management
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• v.27 no.1
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• pp.41-60
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• 2010

This study aims to analyze the properties of the tags used in the fiction genre, the structural aspect of the patterns and the contents of the tags by utilizing LibraryThing, where the tags are assigned in work units of FRBR. A comparative analysis was conducted in terms of the level of association between the descriptive terms in bibliography and LCSH terms. The study also examined the sources of the tags not included in the bibliographic descriptions or LCSHs, what aspects of work they represented, and the terms used as tags in relation to the work. By restricting the study to a single genre, a number of tags that reflected the characteristics of fiction (three elements of the fiction which are theme, plot, style and three elements of the fiction composition which are character, event, setting) were extracted. This study finds out the role of the tag making up the taxonomy and proposes a new direction for the tagging system by demonstrating the possibility of using tags as facets in information organization and retrieval.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.321-325
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• 2009

The detection process of defective tags in most of Korean domestic RFID manufacturing companies is handled or treated by on-hand processing after the job of chip bonding, so it has been requesting to reduce the time and cost for manufacturing of RFID tags. Therefore, in this paper, we design and implement the system to perform the functionality of detection of defective tags after the process of chip bonding, and so provide the basis of a related software to establish the foundation of a automation system for the detection of defected RFID tags which is requested in the related Korean domestic industrial field. The developed system in this paper shows the enhancement of 700% in processing speed and 100% in detection rate of defective tags, comparing to the method of on-hand processing.