• Title/Summary/Keyword: Semantic Mapping

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Issues and Challenges in the Extraction and Mapping of Linked Open Data Resources with Recommender Systems Datasets

  • Nawi, Rosmamalmi Mat;Noah, Shahrul Azman Mohd;Zakaria, Lailatul Qadri
    • Journal of Information Science Theory and Practice
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    • v.9 no.2
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    • pp.66-82
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    • 2021
  • Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

Comparative Study on the Perspectives of Educational Experts and the Public on the Educational Policy -Using the Semantic Network Analysis and Overlay Mapping- (교육정책에서의 교육전문가와 대중의 관점 비교 -의미연결망과 중첩맵 분석을 활용하여-)

  • Lee, Jin Suk
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.105-115
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    • 2022
  • This study compares the perspectives of experts and the public on the 2015 revised curriculum. To do this, research papers and newspaper articles were collected from October 2013 to May 2020. During this period, 1152 research papers and 692 newspaper articles were collected, and semantic network analysis was performed. As a result of the study, the educational expert group showed great interest in the core concept of the development of the revised curriculum focused on the abstract concept, while the public focused on the practical problems and consequences of the revision rather than the development of the revised curriculum itself. These results not only show the gap between the perspectives of the educational expert group and the public but also raise the need for effective communication to bridge the gap.

I/O mapping for ubiquitous home devices with semantic networks (시맨틱 네트워크를 이용한 유비쿼터스 가정환경 장치의 입출력 매핑)

  • Song, In-Jee;Hong, Jin-Hyuk;Cho, Sung-Bae
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.735-740
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    • 2006
  • 유비쿼터스 가정환경에서 서비스를 제공하기 위한 다양한 장치들은 각기 고유한 인터페이스를 가진다. 사용자는 이 장치들을 제어하기 위해서 각각 다른 인터페이스에 익숙해야 하며, 결국 장치 수만큼의 인터페이스를 다루어야 한다. 이와 같은 불편을 해소하기 위해서는 하나의 입력 장치로 여러 장치들을 조작하는 사용자 인터페이스가 필요하다. 특히 유비쿼터스 가정환경에서는 다양한 장치들의 상태 및 기능 등이 동적으로 변하고, 장치가 설정되는 환경도 일정하지 않기 때문에 사용자 중심의 유비쿼터스 환경을 제공하기 위해서는 다양한 인터페이스를 통합할 필요가 있다. 사용자가 비슷하게 인지하는 이종 장치들의 기능을 통합하여 사용자 인터페이스의 동일한 입력으로 매핑한다면 사용자의 부담을 줄일 수 있을 것이다. 본 논문에서는 유비쿼터스 가정환경의 다양한 장비들과 인터페이스 사이의 입출력 관계를 분석하여 시맨틱 네트워크로 모델링하는 방법을 제안한다. 각 장치의 상태와 기능을 시맨틱 네트워크로 정의하고, 노드나 엣지 사이의 유사도를 평가하여 장치와 사용자 인터페이스 사이를 자동으로 매핑한다. 제안하는 방법을 가정환경 입출력장치에 적용하고, 입출력 매핑을 시뮬레이션하는 환경을 구현하여 유용성을 검증한다.

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Salient Object Detection Based on Regional Contrast and Relative Spatial Compactness

  • Xu, Dan;Tang, Zhenmin;Xu, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.11
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    • pp.2737-2753
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    • 2013
  • In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

Semantic Network Analysis on the MIS Research Keywords: APJIS and MIS Quarterly 2005~2009

  • Lee, Sung-Joon;Choi, Jun-Ho;Kim, Hee-Woong
    • Asia pacific journal of information systems
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    • v.20 no.4
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    • pp.25-51
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    • 2010
  • This study compares and contrasts the intellectual development of the MIS field in Korea from 2005 to 2009 to that of international trends by using a keyword co-occurrence network analysis of the two flagship journals: APJIS and MIS Quarterly. From 316 research articles in these two journals, 132 unique and most frequently co-occurred keywords were put into analysis. The results of structural equivalence show a mild correlation between APJIS and MIS Quarterly. The e-commerce, trust, and technology adoption are the high frequency keywords in both journals. In Korea e-learning, purchasing, and recommendation systems turn out to be important keywords while outsourcing, research method, quantitative method, design research, information theory, and empirical research are in average international journals. This connotes that the Korean scholarship tends to focus more on practically oriented topics, but the clustering and relational mapping of research topics in each journal show a mild level of overlap with distinctive orientations due to intrinsic disparities depending on the concerned journals' geographical scopes, namely domestic or global.

Business Collaborative System Based on Social Network Using MOXMDR-DAI+

  • Lee, Jong-Sub;Moon, Seok-Jae
    • International Journal of Advanced Culture Technology
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    • v.8 no.3
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    • pp.223-230
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    • 2020
  • Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

A Study on the Natural Language Generation by Machine Translation (영한 기계번역의 자연어 생성 연구)

  • Hong Sung-Ryong
    • Journal of Digital Contents Society
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    • v.6 no.1
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    • pp.89-94
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    • 2005
  • In machine translation the goal of natural language generation is to produce an target sentence transmitting the meaning of source sentence by using an parsing tree of source sentence and target expressions. It provides generator with linguistic structures, word mapping, part-of-speech, lexical information. The purpose of this study is to research the Korean Characteristics which could be used for the establishment of an algorism in speech recognition and composite sound. This is a part of realization for the plan of automatic machine translation. The stage of MT is divided into the level of morphemic, semantic analysis and syntactic construction.

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OWL Authoring System for building Web Ontology (웹 온톨로지 구축을 위한 OWL 저작 시스템)

  • Lee Moohun;Cho Hyunkyu;Cho Hyeonsung;Cho Sunghoon;Jang Changbok;Choi Euiin
    • The Journal of Society for e-Business Studies
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    • v.10 no.3
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    • pp.21-36
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    • 2005
  • Current web search includes a lot of different results with information that user does not want, because it searches information using keyword mapping. Ontology can describe the correct meaning of web resource and relationships between web resources. And we can extract suitable information that user wants using Ontology Accordingly, we need the ontology to represent knowledge. W3C announced OWL(Web Ontology Language), meaning description technology for such web resource. However, the development of a special tool that can effectively compose and edit OWL is inactive. In this paper, we designed and developed an OWL authoring system that can effectively provide the generation and edit about OWL.

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AUTOMATIC GENERATION OF BUILDING FOOTPRINTS FROM AIRBORNE LIDAR DATA

  • Lee, Dong-Cheon;Jung, Hyung-Sup;Yom, Jae-Hong;Lim, Sae-Bom;Kim, Jung-Hyun
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.637-641
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    • 2007
  • Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

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A Study on the Visual System of Object - Oriented Based on Abstract Information (객체지향을 기반으로한 추상화 정보의 시각화 시스템에 대한 연구)

  • Kim, Haeng-Kon;Han, Eun-Ju;Chung, Youn-Ki
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.10
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    • pp.2434-2444
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    • 1997
  • As software industry progresses, the necessity of visual information have increased more than text-oriented information. So, automatic tools are required to satisfy a user's desire for visual design representation of various source information in the real-world. In this paper, we discuss the methodology and tools for parsing abstract information through semantic analysis and extracting visual information through visual mapping. Namely, as to abstract informations are represented as relational structure and then mapped into visual structure using regular rule, user can obtain visual information. We suggest VOLS(Visual Object Layout System) to transform a abstract information to visual information. It can improve user understandability and assist a maintenance for existing source code.

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