• Language and Information
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• v.2 no.2
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• pp.155-183
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• 1998

The purpose of this paper is to explore the syntactic criteria for determining a secondary predicates as a predicate modifier or a conjunction, and to formalize the semantic aspects of the [-ke] structure as a predicate in Korean. Syntactically, the [-ke] structure is considered to be a secondary predicate when the shared arguments appear in both the [-ke] structure and the main verb structure. On the other hand, if they do not appear in both structures, the [-ke] structure is considered to be a connective element. Semantically the [-ke] structure has numerous aspects such as depictives, resultatives, objectivity, and emphasis. The depictives of the secondary predicate can be formalize as $p{\wedge}q$ where p represents a propositional expression of the secondary predicate and q is a propositional expression of the main verb. Resultatives have the logical form $q{\rightarrow}{\Box}p$, because the consequence has to always be true. However, objectivity has the logical form $q{\rightarrow}{\diamondsuit}p$, because the consequence can be either true or false. Emphasis is represented as $q{\rightarrow}p{\uparrow}$ because the secondary predicate represents the polarity of the event.

• The Mathematical Education
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• v.54 no.4
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• pp.317-334
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• 2015

In this article we study structure of the concept of creative products in mathematics using mathematical creative products. We develop MCPSS1 that improve reliability and validity of MCPSS(Creative Product Semantic Scale in Mathematics). And we search structure of the concept of creative products in mathematics using mathematical creative products focused on theoretical investigation. So we suggest structure model of the concept of creative products focused on theoretical investigation. We compare the result with preceding research using various mathematical creative products, find some difference between relations of sub-factors of structure of the concept of creative products. Our result will provide meaningful data to mathematics education researchers that want to know structure of the concept of creative products in mathematics.

• The Journal of Information Systems
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• v.30 no.2
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• pp.189-214
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• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.133-149
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• 2014

It is unavoidable to provide products that meet customers' needs and wants so that firms may survive under the competition in this globalized market. This paper focuses on how to provide levels for attributes that compse product so that firms may give the best products to customers. In particular, its main issue is how to determine common attributes and the others with their appropriate levels to maximize firms' profits, and how to construct a decision support system to ease decision makers' decisons about optimal common attribute selection using the Semantic Web and SWCL technologies. Parameter data in problems and the relationships in the data are expressed in an ontology data model and a set of constraints by using the Semantic Web and SWCL technologies. They generate a quantitative decision making model through the automatic process in the proposed system, which is fed into the solver using the Logic-based Benders Decomposition method to obtain an optimal solution. The system finally provides the generated solution to the decision makers. This presentation suggests the opportunity of the integration of the proposed system with the broader structured data network and other decision making tools because of the easy data shareness, the standardized data structure and the ease of machine processing in the Semantic Web technology.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.101-121
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• 2018

This study proposes the analysis method in sentence semantics that can be automatically identified and processed as appropriate items in the system according to the composition of the sentences contained in the data corresponding to the logical semantic structure metadata of the research papers. In order to achieve the purpose, the structure of sentences corresponding to 'Research Objectives' and 'Research Outcomes' among the semantic structure metadata was analyzed based on the number of words, the link word types, the role of many-appeared words in sentences, and the end types of a word. As a result of this study, the number of words in the sentences was 38 in 'Research Objectives' and 212 in 'Research Outcomes'. The link word types in 'Research Objectives' were occurred in the order such as Causality, Sequence, Equivalence, In-other-word/Summary relation, and the link word types in 'Research Outcomes' were appeared in the order such as Causality, Equivalence, Sequence, In-other-word/Summary relation. Analysis target words like '역할(Role)', '요인(Factor)' and '관계(Relation)' played a similar role in both purpose and result part, but the role of '연구(Study)' was little different. Finally, the verb endings in sentences were appeared many times such as '~고자', '~였다' in 'Research Objectives', and '~었다', '~있다', '~였다' in 'Research Outcomes'. This study is significant as a fundamental research that can be utilized to automatically identify and input the metadata element reflecting the common logical semantics of research papers in order to support researchers' scholarly sensemaking.

• Proceedings of the Korea Society of Design Studies Conference
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• 1996.04a
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• pp.59-60
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• 1996

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.222-229
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• 2016

Linked Data is a powerful technology for storing and publishing the structures of data. It is helpful for web applications because of its usefulness through semantic query data. However, using Linked Data is not easy for ordinary users who lack knowledge about the structure of data or the query syntax of Linked Data. For that problem, we propose a translator component that is used for translating RESTful/JSON request messages into SPARQL commands based on ontology - a metadata that describes the structure of data. Clients do not need to worry about the structure of stored data or SPARQL, a kind of query language used for querying linked data that not many people know, when they insert a new instance or query for all instances of any specific class with those complex structure data. In addition, the translator component has the search function that can find a set of data from multiple classes based on finding the shortest paths between the target classes - the original set that user provide, and target classes- the users want to get. This translator component will be applied for any dynamic ontological structure as well as automatically generate a SPARQL command based on users' request message.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.877-893
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• 2022

With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

• International Journal of Contents
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• v.15 no.1
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• pp.10-24
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• 2019

This study applied network agenda-setting theory to analyze the impact of the agenda-setting function of the media on certain issues by focusing on the agenda at the center of controversy, 'Creative Economy'. To this end, the study extracted the data referred to creative economy in the media and SNS from 1 January 2008 to 31 December 2014, and analyzed the data using the network analysis program UCINET and the Korean language analysis program Textom. The results of the present study show that, during the period under former President Lee (2008-2011), the media's creative economy agenda-setting function did not exert a significant impact on the agenda-setting within SNS. However, from 2012 when the government of former President Park Geun-hye had started, the agenda-setting function of the media starts to show increasingly strong influence on the agenda cognition in SNS. The central words and sub-words configuration forming the center of the semantic network moved in the direction of a high correlation, in addition to the gradually increasing correlation based on QAP correlation analysis. In 2014, the semantic networks of the media and SNS bore a close resemblance to each other, while the shape of networks and sub-words structure also had a high level of similarity.

• Journal of Korea Multimedia Society
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• v.10 no.1
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• pp.117-127
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• 2007

As the value of the multimedia data is getting high, the study on the semantic recognition and retrieval about the multimedia information is strongly demanded. In this paper, we build the motion ontology and adopt it for representing the meaning of the moving objects in video data. By referencing the WordNet structure, we extend its semantic meaning based on the reclassification of motion verbs, which are used to represent the semantic meaning of moving objects. The represented information is receded in OWL/RDF(S). Here, we could expect the 'Is-A' and 'Equivalent' reasoning of the data as we use the ontologies. And the semantic representation about the moving objects is possible through the video annotation using ontology. And we tested the accuracy of the system comparing with the key-word based system. As a result, we could get the approximately 10% improvement of the system performance.