• Genomics & Informatics
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• v.17 no.2
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• pp.13.1-13.3
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• 2019

The usage of controlled biomedical vocabularies is the cornerstone that enables seamless interoperability when using a common data model across multiple data sites. The Observational Health Data Science and Informatics (OHDSI) initiative combines over 100 controlled vocabularies into its own. However, the OHDSI vocabulary is limited in the sense that it combines multiple terminologies and does not provide a direct way to link them outside of their own self-contained scope. This issue makes the tasks of enriching feature sets by using external resources extremely difficult. In order to address these shortcomings, we have created a linked data version of the OHDSI vocabulary, connecting it with already established linked resources like bioportal, bio2rdf, etc. with the ultimate purpose of enabling the interoperability of resources previously foreign to the OHDSI universe.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.199-215
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• 2020

A seagrass that is marine vascular plants plays an important role in the marine ecosystem, so periodic monitoring ofseagrass habitatsis being performed. Recently, the use of dronesthat can easily acquire very high-resolution imagery is increasing to efficiently monitor seagrass habitats. And deep learning based on a convolutional neural network has shown excellent performance in semantic segmentation. So, studies applied to deep learning models have been actively conducted in remote sensing. However, the segmentation accuracy was different due to the hyperparameter, various deep learning models and imagery. And the normalization of the image and the tile and batch size are also not standardized. So,seagrass habitats were segmented from drone-borne imagery using a deep learning that shows excellent performance in this study. And it compared and analyzed the results focused on normalization and tile size. For comparison of the results according to the normalization, tile and batch size, a grayscale image and grayscale imagery converted to Z-score and Min-Max normalization methods were used. And the tile size isincreased at a specific interval while the batch size is allowed the memory size to be used as much as possible. As a result, IoU was 0.26 ~ 0.4 higher than that of Z-score normalized imagery than other imagery. Also, it wasfound that the difference to 0.09 depending on the tile and batch size. The results were different according to the normalization, tile and batch. Therefore, this experiment found that these factors should have a suitable decision process.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.39-51
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• 2005

A study of philosophy is a process that archive, reorganize and analyze the earlier works to discover new facts. Philosophy digital resources is necessary to research philosophy because they provide lots of electronic texts, philosophical information, forums, etc. In this paper, we introduce . our result of a research on philosophy digital resources existing in domestic or oversea web sites. We describe the problems which existing resources have and our solution to solve them. Also we provide a guideline to creating philosophy ontology based on topic maps which are data model of ontology. Our philosophy ontology defines hierarchy and associative relationships between philosophical knowledge and support retrieval and exploring of knowledge using semantic information.

• Korean Journal of Agricultural Science
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• v.27 no.1
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• pp.5-12
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• 2000

The main purpose of this study is to obtain spatial image information toward forest thinning process in Larix forest stands. Thirteen different alternatives were simulated to visualize on the basis of actual thinning work photos. The options were illustrated as photos produced by photoshop program. Each alternatives were evaluated by forest visitor group with total 244 respondents after reliability test. Spatial images of 13 thinning photos were measured by 12 semantic differential scale as broad -narrow, ordered-tangled, friendly-unfriendly, monotonous-divers, dry-refreshing, relieved -stifling, healthy-sickly, uniform-scattered, dead-alive, opened-closed, bent-straight, and beautiful-ugly. In comparison with thinning stands and natural stands, thinning works were visual improvement effects of spatial images. Seemingly, this trend is due to definite form beauty, straight and clear length form of coniferous forest, As can be expected, slash and downwood were negatively related to improvement effects of spatial images. The 60% ratio of stem/ tree height and 450-950 trees/ha was positive in attraction of spatial images. Results indicate how to conduct forest thinning system for spatial images on Larix forest stands.

• Spatial Information Research
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• v.19 no.4
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• pp.91-97
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• 2011

In this paper, we propose an architecture for geosemantic services. With the rapid progress of web services, wireless internet technologies and popularization of smart phone in recent years, a lot of applications based on geographic information are being developed. Moreover the search portals empowered by semantic web technologies are enabling general users to access on-line resources more easily. However, several studies in GIS domain have pointed out the practical limitation of existing service patterns, which are limited only to linking heterogenous spatial databases, insufficient for several important use cases. Hence we draw functional elements of geosemantic services from GIS and semantic web standards, and present the use cases and a new architecture for geosemantic services. This approach could set a foundation to implement geoemantic services.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.23-33
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• 2014

The development of the information retrieval field is evolving to the research field searching accurately for the information from thing finding rapidly a large amount of information. Personalization and the semantic web technology is a key technology. The automatic indexing technology about the web document and throughput go beyond the research stage and show up as the practical service. However, there is a lack of research on the document information retrieval field about the attached document type of except the web document. In this paper, we illustrate about the method in which it analyzed the text content of the unstructured documents prepared in the text, word, hwp form and it how to construction OWL ontology. To build TBox of the document ontology and the resources which can be obtained from the document is selected, and we implement with the system in order to utilize as the instant of the constructed document ontology. It is effectually usable in the information retrieval and document management system using the semantic technology of the correspondence document as the ontology automatic construction of this kind of the unstructured documents.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.50-55
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• 2016

To attain an understanding of customers' opinions or demands regarding a companies' products or service, it is important to consider VOC (Voice of Customer) data; however, it is difficult to understand contexts from VOC because segmented and duplicate sentences and a variety of dialog contexts. In this article, POS (part of speech) and morphemes were selected as language resources due to their semantic importance regarding documents, and based on these, we defined an LSP (Lexico-Semantic-Pattern) to understand the structure and semantics of the sentences and extracted summary by key sentences; furthermore the LSP was introduced to connect the segmented sentences and remove any contextual repetition. We also defined the LSP by categories and classified the documents based on those categories that comprise the main sentences matched by LSP. In the experiment, we classified the VOC-data documents for the creation of a summarization before comparing the result with the previous methodologies.

• Journal of the Korean earth science society
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• v.33 no.1
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• pp.59-72
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• 2012

The purpose of this study is to explore the types of interlanguage that middle school students use in learning about the concept of diastrophism. Eighteen students from two classes in a middle school in Seoul participated in the study and each participant was interviewed four times. Data were analyzed in terms of semantic relations and thematic patterns. As a result, eight interlanguage types were identified and described, which are using everyday language as resources, combining scientific words with everyday words, conjugating scientific words imperfectly, and using semantic relations inappropriately. The implication of interlanguage for science learning and teaching is discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2122-2140
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• 2020

Proper and precise embedding of commercial ads within Webpages requires Ad-hoc analysis and understanding of their content. By the successful implementation of this step, both publishers and advertisers gain mutual benefits through increasing their revenues on the one hand, and improving user experience on the other. In this research work, we propose a novel multi-level context-based ads serving approach through which ads will be served at generic publisher websites based on their contextual relevance. In the proposed approach, knowledge encoded in domain-specific and generic semantic repositories is exploited in order to analyze and segment Webpages into sets of contextually-relevant segments. Semantically-enhanced indexes are also constructed to index ads based on their textual descriptions provided by advertisers. A modified cosine similarity matching algorithm is employed to embed each ad from the Ads repository into one or more contextually-relevant segments. In order to validate our proposal, we have implemented a prototype of an ad serving system with two datasets that consist of (11429 ads and 93 documents) and (11000 documents and 15 ads), respectively. To demonstrate the effectiveness of the proposed techniques, we experimentally tested the proposed method and compared the produced results against five baseline metrics that can be used in the context of ad serving systems. In addition, we compared the results produced by our system with other state-of-the-art models. Findings demonstrate that the accuracy of conventional ad matching techniques has improved by exploiting the proposed semantically-enhanced context-based ad serving model.

• Language and Information
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• v.14 no.1
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• pp.113-144
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• 2010

The primary goal of this paper is to find a feasible way to answer the question: Does the similarity in meaning between verbs relate to the similarity in their subcategorization? In order to answer this question in a rather concrete way on the basis of a large set of English verbs, this study made use of various language resources, tools, and statistical methodologies. We first compiled a list of 678 verbs that were selected from the most and second most frequent word lists from the Colins Cobuild English Dictionary, which also appeared in WordNet 3.0. We calculated similarity measures between all the pairs of the words based on the 'jcn' algorithm (Jiang and Conrath, 1997) implemented in the WordNet::Similarity module (Pedersen, Patwardhan, and Michelizzi, 2004). The clustering process followed, first building similarity matrices out of the similarity measure values, next drawing dendrograms on the basis of the matricies, then finally getting 177 meaningful clusters (covering 437 verbs) that passed a certain level set by z-score. The subcategorization frames and their frequency values were taken from the ICE-GB. In order to calculate the Selectional Preference Strength (SPS) of the relationship between a verb and its subcategorizations, we relied on the Kullback-Leibler Divergence model (Resnik, 1996). The SPS values of the verbs in the same cluster were compared with each other, which served to give the statistical values that indicate how much the SPS values overlap between the subcategorization frames of the verbs. Our final analysis shows that the degree of overlap, or the relationship between semantic similarity and the subcategorization frames of the verbs in English, is equally spread out from the 'very strongly related' to the 'very weakly related'. Some semantically similar verbs share a lot in terms of their subcategorization frames, and some others indicate an average degree of strength in the relationship, while the others, though still semantically similar, tend to share little in their subcategorization frames.