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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (1): 81-90    DOI: 10.11925/infotech.2096-3467.2017.01.10
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Linked Data for Mobile Visual Search System of Digital Library
Qi Yunfei1,3(), Zhao Yuxiang2, Zhu Qinghua1
1School of Information Management, Nanjing University, Nanjing 210093, China
2School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094, China
3Dean’s Office, Henan University of Finance and Economics, Zhengzhou 451464, China
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[Objective]This paper proposes a new method for the mobile visual search, which retrieves the visual and semantic information from the digital library simultaneously. [Methods] First, we used the BIBFRAME, linked data and image processing techniques to extract the semantic and characteristics information from the visual resources. Second, we combined the visual and semantic search with the help of linked data. [Results] The proposed method improved the performance of visual and semantic information retrieval. [Limitations] The system efficiency, the algorithm for feature identification, and the SPARQL retrieval procedure needed to be optimized. [Conclusions] The proposed method could successfully search visual and semantic information, which might create more innovative services for the digital library.

Key wordsLinked Data      Digital Library      Mobile Visual Search      Semantic Search      BIBFRAME     
Received: 12 September 2016      Published: 22 February 2017
ZTFLH:  G350  

Cite this article:

Qi Yunfei,Zhao Yuxiang,Zhu Qinghua. Linked Data for Mobile Visual Search System of Digital Library. Data Analysis and Knowledge Discovery, 2017, 1(1): 81-90.

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层次 名称
Work 相关的类: Agent(Person、Organization、Meeting、Jurisdiction、Family)、Collect、Event、GenreForm、Identifier、
相关的对象属性: genreForm、notation、place、subject、summary、tableOfContents、title、type、hasInstance、hasPart、reference、
相关的数值属性: awards、date、identifieBy、place
Instance 相关的类: Identifier、Carrier、Contribution、GenreForm、Identifier、IntendedAudience、TableOfContents
相关的对象属性: carrier、genreForm、intendedAudience、notation、place、subject、summary、tableOfContents、title、
相关的数值属性: awards、date、editionStatement、identifieBy、place、imageType、textCoding、textLanguage、trackCoding、
Item 相关的类: Barcode、Identifier、ShelfMark
相关的对象属性: barcode、contirbution、electronicLocator、genreForm、heldBy、place、shelfMark、subject、title、itemOf
相关的数值属性: custodiaHistory、date
类型 检索式
前缀 PREFIX vr:<
语义信息 SELECT ?o WHERE { vr:image00001 ?p ?instace.
?instace vr:title ?o.}
相同事件 SELECT ?o WHERE { vr:image00001 vr:same
EventAs ?event. ?event vr:title ?o.}
相同主题 SELECT ?o WHERE { vr:image00001
vr:sameSubjectAs ?subject. ?subject vr:title ?o.}
相同作者 SELECT ?o WHERE { vr:image00001
vr:sameAgentAs ?agent.}
相同集合 SELECT ?o WHERE { vr:image00001
vr:sameCollectAs ?Collective.
?collective vr:collectiveTitle ?o.}
[1] 中国互联网络信息中心. 第38次中国互联网络发展状况统计报告[R/OL]. [2016-09-10]. .
[1] (China Internet Network Information Center. Statistical Report of the 38th Chinese Internet Development [R/OL]. [2016-09-10].
[2] Girod B, Chandrasekhar V, Chen D M, et al.Mobile Visual Search[J]. IEEE Signal Processing Magazine, 2011, 28(4): 61-76.
doi: 10.1109/MSP.2011.940881
[3] 赵宇翔, 朱庆华. 大数据环境下移动视觉搜索的游戏化机制设计[J]. 情报资料工作, 2016, 37(4): 19-25.
[3] (Zhao Yuxiang, Zhu Qinghua.On Mobile Visual Search Game Mechanism Design in the Big Data Environment[J]. Information and Documentation Services, 2016, 37(4): 19-25.)
[4] 张兴旺, 李晨晖. 数字图书馆移动视觉搜索机制建设的若干关键问题[J]. 图书情报工作, 2015, 59(15): 42-48.
doi: 10.13266/j.issn.0252-3116.2015.15.006
[4] (Zhang Xingwang, Li Chenhui.Critical Issues on the Construction of Digital Library Mobile Visual Search Mechanism[J]. Library and Information Service, 2015, 59(15): 42-48.)
doi: 10.13266/j.issn.0252-3116.2015.15.006
[5] Du Y G, Li Z Y, Qu W Y, et al.MVSS: Mobile Visual Search Based on Saliency[C]// Proceedings of IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference On Embedded and Ubiquitous Computing. IEEE, 2013: 922-928.
[6] Alzu’bi A, Amira A, Ramzan N.Semantic Content-based Image Retrieval: A Comprehensive Study[J]. Journal of Visual Communication & Image Representation, 2015, 32: 20-54.
[7] Ke Y, Sukthankar R.PCA-SIFT: A More Distinctive Representation for Local Image Descriptors[C] //Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2004: 506-513.
[8] Bay H, Tuytelaars T, Gool L V.SURF: Speeded Up Robust Features[J]. Computer Vision & Image Understanding, 2006, 110(3): 404-417.
doi: 10.1007/11744023_32
[9] Tsai S S, Chen H, Chen D, et al.Word-HOGs: Word Histogram of Oriented Gradients for Mobile Visual Search[C] //Proceedings of IEEE International Conference on Image Processing. IEEE, 2014: 3968-3972.
[10] Zhang G, Zeng Z, Zhang S, et al.Transmitting Informative Components of Fisher Codes for Mobile Visual Search[C]//Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2015: 1136-1140.
[11] Zhang Q, Li Z, Du Y, et al.A Novel Progressive Transmission in Mobile Visual Search[C]//Proceedings of IEEE 12th International Conference on Dependable, Autonomic and Secure Computing. IEEE, 2014: 259-264.
[12] Zhao B, Zhao H W, Liu P P, et al.A New Mobile Visual Search System Based on the Human Visual System[J]. Applied Mechanics & Materials, 2013,461: 792-800.
[13] Yang X, Liu L, Qian X, et al.Mobile Visual Search via Hievarchical Sparse Coding[C]//Proceedings of IEEE International Conference on Multimedia and Expo. IEEE, 2014: 1-6.
[14] Qi H, Stojmenovic M, Li K, et al.A Low Transmission Overhead Framework of Mobile Visual Search Based on Vocabulary Decomposition[J]. IEEE Transactions on Multimedia, 2014, 16(7): 1963-1972.
doi: 10.1109/TMM.2014.2345026
[15] Zhang D, Yap K H, Subbhuraam S.Mobile Product Recognition with Efficient Bag-of-Phrase Visual Search[C]// Proceedings of International Symposium on Communications, Control and Signal Processing. IEEE, 2014: 65-68.
[16] Chen D M, Girod B.Memory-Efficient Image Databases for Mobile Visual Search[J]. IEEE Multimedia, 2014, 21(1): 14-23.
[17] 张亭亭, 赵宇翔, 朱庆华. 数字图书馆移动视觉搜索的众包模式初探[J]. 情报资料工作, 2016, 37(4): 11-18.
[17] (Zhang Tingting, Zhao Yuxiang, Zhu Qinghua.A Probe into Crowdsourcing Model of Digital Library Mobile Visual Search[J]. Information and Documentation Services, 2016, 37(4): 11-18.)
[18] 刘木林, 朱庆华, 赵宇翔. 基于关联数据的数字图书馆移动视觉搜索框架研究[J]. 情报资料工作, 2016, 37(4) : 6-10.
[18] (Liu Mulin, Zhu Qinghua, Zhao Yuxiang.Research on Linked Data-based Digital Library Mobile Visual Search Framework[J]. Information and Documentation Services, 2016, 37(4): 6-10.)
[19] 刘炜. 关联数据:概念、技术及应用展望[J]. 大学图书馆学报, 2011, 29(2): 5-12.
doi: 10.3969/j.issn.1002-1027.2011.02.001
[19] (Liu Wei.Overview on Linked Data: Concept, Technology and Implementation[J]. Journal of Academic Libraries, 2011, 29(2): 5-12.)
doi: 10.3969/j.issn.1002-1027.2011.02.001
[20] Library of Congress. Library of Congress Subject Headings [EB/OL]. [2016-09-10]. .
[21] Library of Congress. BIBFRAME Model & Vocabulary [EB/OL]. [2016-09-10]. .
[22] 刘炜, 夏翠娟, 张春景. 大数据与关联数据: 正在到来的数据技术革命[J]. 现代图书情报技术, 2013(4): 2-9.
[22] (Liu Wei, Xia Cuijuan, Zhang Chunjing.Big Data and Linked Data: The Emerging Data Technology for the Future of Librarianship[J]. New Technology of Library and Information Service, 2013(4): 2-9.)
[23] 曹月珍, 马建玲. 关联数据在图书馆的最新发展[J]. 图书馆学研究, 2014(14): 6-12.
[23] (Cao Yuezhen, Ma Jianling.The Latest Development of Linked Data in the Library[J]. Researches in Library Science, 2014(14): 6-12.)
[24] 欧石燕. 面向关联数据的语义数字图书馆资源描述与组织框架设计与实现[J]. 中国图书馆学报, 2012, 38(6): 58-71.
[24] (Ou Shiyan.Design and Implementation of a Linked Data- oriented Framework for Resource Description and Organization in Semantic Digital Libraries[J]. Journal of Library Science in China, 2012, 38(6): 58-71.)
[25] 欧石燕, 胡珊, 张帅. 本体与关联数据驱动的图书馆信息资源语义整合方法及其测评[J]. 图书情报工作, 2014, 58(2): 5-13.
doi: 10.13266/j.issn.0252-3116.2014.02.001
[25] (Ou Shiyan, Hu Shan, Zhang Shuai.An Ontology & Linked Data Driven Semantic Integration Method of Library Information Resources and Its Evaluation[J]. Library and Information Service, 2014, 58(2): 5-13.)
doi: 10.13266/j.issn.0252-3116.2014.02.001
[26] 欧石燕, 唐振贵. 面向图书馆关联数据的自动问答技术研究[J]. 中国图书馆学报, 2015, 41(6): 44-60.
doi: 10.13530/j.cnki.jlis.150030
[26] (Ou Shiyan, Tang Zhengui.A Question Answering Method over Library Linked Data[J]. Journal of Library Science in China, 2015, 41(6): 44-60.)
doi: 10.13530/j.cnki.jlis.150030
[27] 周宇, 欧石燕. 面向关联数据的高校机构知识库构建方法研究[J]. 图书情报工作, 2016, 60(1): 105-113.
doi: 10.13266/j.issn.0252-3116.2016.01.015
[27] (Zhou Yu, Ou Shiyan.Reasearch on Linked Data-oriented Construction Method of Academic Institutional Repositories[J]. Library and Information Service, 2016, 60(1): 105-113.)
doi: 10.13266/j.issn.0252-3116.2016.01.015
[28] 夏翠娟, 刘炜, 赵亮, 等. 关联数据发布技术及其实现-以Drupal为例[J]. 中国图书馆学报, 2012, 38(1): 49-57.
[28] (Xia Cuijuan, Liu Wei, Zhao Liang, et al.The Current Technologies and Tools for Linked Data: A Case of Drupal[J]. Journal of Library Science in China, 2012, 38(1): 49-57.)
[29] 夏翠娟, 刘炜. 关联数据的消费技术及实现[J]. 大学图书馆学报, 2013, 31(3): 29-37.
[29] (Xia Cuijuan, Liu Wei.Technologies and Implementation of Consuming Linked Data[J]. Journal of Academic Libraries, 2013, 31(3): 29-37.)
[30] 夏翠娟, 金家琴. 从关系数据库到关联数据: W3C标准应用探析[J]. 图书馆杂志, 2015, 34(5): 85-94.
[30] (Xia Cuijuan, Jin Jiaqin.On the Application of W3C’s RDB2RDFS Standards[J]. Library Journal, 2015, 34(5): 85-94.)
[31] 夏翠娟, 刘炜, 陈涛, 等. 家谱关联数据服务平台的开发实践[J]. 中国图书馆学报, 2016, 42(3): 27-38.
[31] (Xia Cuijuan, Liu Wei, Chen Tao, et al.A Genealogy Data Service Platform Implemented with Linked Data Technology[J]. Journal of Library Science in China, 2016, 42(3): 27-38.)
[32] 陈涛, 夏翠娟, 刘炜, 等. 关联数据的可视化技术研究与实现[J]. 图书情报工作, 2015, 59(17): 113-119.
doi: 10.13266/j.issn.0252-3116.2015.17.017
[32] (Chen Tao, Xia Cuijuan, Liu Wei, et al.Research and Implementation of Visualization Technology for Linked Data[J]. Library and Information Service, 2015, 59(17): 113-119.)
doi: 10.13266/j.issn.0252-3116.2015.17.017
[33] 赵夷平, 毕强. 关联数据在学术资源网相似文献发现中的应用研究[J]. 现代图书情报技术, 2016(3): 41-49.
[33] (Zhao Yiping, Bi Qiang.Using Linked Data to Retrieve Similar Documents from the Academic Resource Websites[J]. New Technology of Library and Information Service, 2016(3): 41-49.)
[34] 刘炜, 夏翠娟. 书目数据新格式BIBFRAME及其应用[J]. 大学图书馆学报, 2014, 32(1): 5-13.
doi: 10.3969/j.issn.1002-1027.2014.01.002
[34] (Liu Wei, Xia Cuijuan.Introduction to BIBFRAME as a Successor to MARC[J]. Journal of Academic Libraries, 2014, 32(1): 5-13.)
doi: 10.3969/j.issn.1002-1027.2014.01.002
[35] 夏翠娟, 刘炜, 张磊, 等. 基于书目框架(BIBFRAME)的家谱本体设计[J]. 图书馆论坛, 2014(11): 5-19.
[35] (Xia Cuijuan, Liu Wei, Zhang Lei, et al.A Genealogical Ontology in the Form of BIBFRAME Model[J]. Library Tribune, 2014(11): 5-19.)
[36] 胡小菁. BIBFRAME核心类演变分析[J]. 中国图书馆学报, 2016, 42(3): 20-26.
doi: 10.13530/j.cnki.jlis.160013
[36] (Hu Xiaojing.Evolution of BIBFRAME Core Classes[J]. Journal of Library Science in China, 2016, 42(3): 20-26.)
doi: 10.13530/j.cnki.jlis.160013
[37] University of London Centre for Digital Music in Queen Mary. The Event Ontology [EB/OL]. [2016-09-10]. .
[38] Friend of a Friend (FOAF) Project [EB/OL]. [2016-09-10]. .
[39] Semantic Web Deployment Working Group of W3C. SKOS Simple Knowledge Organization System [EB/OL]. [2016-09- 10]. .
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