• Title/Summary/Keyword: semantic

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Semantc Segmentation Using Simple Arduino Module (간단한 아두이노 모듈을 이용한 Semantic Segmentation)

  • Ha, Soo-Hee;Yoo, Jae-Chern
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.37-39
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    • 2021
  • 본 논문에서는 간단한 아두이노 모듈을 이용하여 MATLAB에서 실행되는 semantic segmentation을 조작해보았다. 기존에는 단순히 센서를 통해 감지하거나, 입력을 받아 출력하는 등의 수동적으로 아두이노 모듈을 활용하였다. 하지만 직접 아두이노와 semantic segmentation을 연결하여 semantic segmentation 결과를 조작하여, 아두이노를 인공지능과 결합하여 능동적으로 사용할 수 있게 하였다.

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Research on Comparing System with Syntactic-Semantic Tree in Subjective-type Grading (주관식 문제 채점에서의 구문의미트리 비교 시스템에 대한 연구)

  • Kang, WonSeog
    • The Journal of Korean Association of Computer Education
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    • v.20 no.5
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    • pp.79-88
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    • 2017
  • To upgrade the subjective question grading, we need the syntactic-semantic analysis to analyze syntatic-semantic relation between words in answering. However, since the syntactic-semantic tree has structural and semantic relation between words, we can not apply the method calculating the similarity between vectors. This paper suggests the comparing system with syntactic-semantic tree which has structural and semantic relation between words. In this thesis, we suggest similarity calculation principles for comparing the trees and verify the principles through experiments. This system will help the subjective question grading by comparing the trees and be utilized in distinguishing similar documents.

A Study on the Efficiency of BIM on the Multi-Semantic Form Modeling in Architectural Design Education (건축설계교육에서 다중의미를 가진 형태 모델링에 관한 BIM의 효율성에 관한 연구)

  • Hong, Seung-Wan;Cho, Min-Jung
    • Journal of KIBIM
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    • v.6 no.1
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    • pp.18-24
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    • 2016
  • While the advantages of BIM stem in the automatic and efficient assembling amongst the given, single semantic-embedded objects, it is still unknown the efficiency of BIM for developing the form that has more than one functions. To investigate the research question, in an authentic design course, the participants (N=38) assessed the efficiency of BIM when they designed a shop with the single semantic-embedded objects and multi-semantic objects. Independent T-tests reveal that in BIM, the use of the single semantic-embedded objects is statistically more efficient than that of multi-semantic objects (p<0.01). As the reason, in interviews, the participants reported that they had to split down the planned multi-meanings and assign only one meaning to one form in order to utilize the automatic assembling of BIM. Thus, they spent much effort and time for re-coordinating the match between the forms and multi-semantics. The findings of this study highlight the further directions of BIM in order to suit for the empirical practices of architects.

The Associational Meaning of Purple-series Color Names in the Clothing of Joseon Dynasty Period (조선시대 복식에 나타난 자색계 색명의 연상적 의미)

  • Kim Soon-Young
    • Journal of the Korean Society of Costume
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    • v.55 no.3 s.93
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    • pp.1-18
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    • 2005
  • In this study, the transition characteristics of purple series color names appearing in the clothing of the Joseon Dynasty were examined, and the associational meaning of each name were investigated through various methods. The results are as follows; First, Such characteristics as continuity, differentiation, substitution could be observed through the investigation of color names of purple-series appeared on the clothing in the Joseon Dynasty period. Secondly, the associational meaning could be subdivided into; social position symbolic meanings, usage meanings, economic meanings, and thought meanings. The social position symbolic meanings could be observed mainly in the single names which has been used since the ancient times, usage meanings could be observed in a wide variety according to the individual color names. The economic meanings could be observed by comparing the value of colored cloths and colored threads. The thought meanings were mainly related with the Confucianism. Thirdly, the associational semantic structure were established on the basis of associational meanings of purple-series color names. Individual color name on the social position symbolic semantic structure symbolizes [government official] and [servant]. Through usage semantic structure individual color names could be understood structurally according to the social position, sex distinction, wearing situation, items of clothing, and structure of clothing. Individual names on the economic semantic structure were segmented by the semantic components of the values in [high], [medium], [low] prices, kinds and quantity of dyes. The thought semantic structure could be subdivided [Confucianism] and [The Thought of Taeil] in its semantic structure.

A Study on Semantic Web for Multi-dimensional Data (다차원 데이터를 위한 시멘틱 웹 연구)

  • Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.3
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    • pp.121-127
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    • 2017
  • Recently, it has been actively Semantic Web studies for 2-dimensional data of the spatial data. 2-dimensional Semantic Web, are fused existing Geospatial Web and the Semantic Web, and integrate with the efficient cooperation of the vast non-spatial information on a variety of geospatial information and general Web, it is possible to provide it is a Web services technology of intelligent geographic information. However, in the research for multi-dimensional data processing, and in those who are missing overall, relevant standards also not been enacted. Therefore, in this paper, by applying a variety of base of the theory and technology related to this to take place the Ontology processing technology, multi-dimensional data processing is possible ontology, question, and suggested the contents of the reasoning. Also, we tried to apply what you have proposed respectively to the multi-dimensional query virtual scenario necessary.

KNN-based Image Annotation by Collectively Mining Visual and Semantic Similarities

  • Ji, Qian;Zhang, Liyan;Li, Zechao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4476-4490
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    • 2017
  • The aim of image annotation is to determine labels that can accurately describe the semantic information of images. Many approaches have been proposed to automate the image annotation task while achieving good performance. However, in most cases, the semantic similarities of images are ignored. Towards this end, we propose a novel Visual-Semantic Nearest Neighbor (VS-KNN) method by collectively exploring visual and semantic similarities for image annotation. First, for each label, visual nearest neighbors of a given test image are constructed from training images associated with this label. Second, each neighboring subset is determined by mining the semantic similarity and the visual similarity. Finally, the relevance between the images and labels is determined based on maximum a posteriori estimation. Extensive experiments were conducted using three widely used image datasets. The experimental results show the effectiveness of the proposed method in comparison with state-of-the-arts methods.

A Semantic Search System based on Basic Ontology of Traditional Korean Medicine (한의 기초 온톨로지 기반 시맨틱 검색 시스템)

  • Kim, Sang-Kyun;Jang, Hyun-Chul;Kim, Jin-Hyun;Kim, Chul;Yea, Sang-Jun;Song, Mi-Young
    • Korean Journal of Oriental Medicine
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    • v.17 no.2
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    • pp.57-62
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    • 2011
  • We in this paper propose a semantic search system using the basic ontology in Korean medicine field. The basic ontology provides a formalization of medicinal materials, formulas, and diseases of Korean medicine. Recently, many studies for the semantic search system have been proposed. However, they do not support the semantic search and reasoning in the domain of Korean medicine because they do not have the Korean medicine ontology. Our system provides the semantic search features of semantic keyword recommendation, associated information browsing, and ontology reasoning based on the basic ontology. In addition, they also have the features of ontology search of a form of table and graph, synonym search, and external Open API supports. The general search engines usually provide search results for the simple keyword, while our system can also provide the associated information with respect to search results by using ontology so that can recommend more exact results to users.

Semantic Trajectory Based Behavior Generation for Groups Identification

  • Cao, Yang;Cai, Zhi;Xue, Fei;Li, Tong;Ding, Zhiming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5782-5799
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    • 2018
  • With the development of GPS and the popularity of mobile devices with positioning capability, collecting massive amounts of trajectory data is feasible and easy. The daily trajectories of moving objects convey a concise overview of their behaviors. Different social roles have different trajectory patterns. Therefore, we can identify users or groups based on similar trajectory patterns by mining implicit life patterns. However, most existing daily trajectories mining studies mainly focus on the spatial and temporal analysis of raw trajectory data but missing the essential semantic information or behaviors. In this paper, we propose a novel trajectory semantics calculation method to identify groups that have similar behaviors. In our model, we first propose a fast and efficient approach for stay regions extraction from daily trajectories, then generate semantic trajectories by enriching the stay regions with semantic labels. To measure the similarity between semantic trajectories, we design a semantic similarity measure model based on spatial and temporal similarity factor. Furthermore, a pruning strategy is proposed to lighten tedious calculations and comparisons. We have conducted extensive experiments on real trajectory dataset of Geolife project, and the experimental results show our proposed method is both effective and efficient.

A System Framework and Research Challenges for the Semantic Web Applications (시맨틱 웹 애플리케이션의 시스템 프레임워크 및 도전 과제에 관한 연구)

  • Yoo, Dong-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.255-266
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    • 2009
  • The Semantic Web has appeared to handle information on the web effectively, which has been increasing very rapidly since the web emerged. It refers to the machine, which understands the meaning of information on behalf of human and handles the information automatically that users want. The objective of this research is to help people to understand the Semantic Web as the next generation web by surveying the applications of Semantic Web technologies. To that end, this paper suggests a system framework which can be used for analyzing most of the Semantic Web applications. Using the suggested the framework, the recent Semantic Web applications are analyzed. And then research challenges are discussed to be overcome for the practical Semantic Web based on the analyzed results.

Two-Phase Shallow Semantic Parsing based on Partial Syntactic Parsing (부분 구문 분석 결과에 기반한 두 단계 부분 의미 분석 시스템)

  • Park, Kyung-Mi;Mun, Young-Song
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.85-92
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    • 2010
  • A shallow semantic parsing system analyzes the relationship that a syntactic constituent of the sentence has with a predicate. It identifies semantic arguments representing agent, patient, instrument, etc. of the predicate. In this study, we propose a two-phase shallow semantic parsing model which consists of the identification phase and the classification phase. We first find the boundary of semantic arguments from partial syntactic parsing results, and then assign appropriate semantic roles to the identified semantic arguments. By taking the sequential two-phase approach, we can alleviate the unbalanced class distribution problem, and select the features appropriate for each task. Experiments show the relative contribution of each phase on the test data.