混合需求驱动的文内视觉资源移动视觉搜索框架
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摘要
文内视觉资源是学术文献中重要的可视知识单元,提供移动互联环境下文内视觉资源的搜索服务,将成为情报学领域学术知识服务的创新价值增长点。本文从文内视觉资源的"供给-需求-服务"三方视角出发,通过整合学术用户不同层次的需求,融合文内视觉资源的底层视觉特征、高层语义特征与上下文文本信息特征,探索文内视觉资源移动视觉搜索(VRAL-MVS)的实现框架。框架的资源描述与组织部分重点进行了VRAL-MVS系统的需求层次识别和VRAL本体构建,检索实现部分则侧重探讨了系统架构与检索流程,并开发了VRAL-MVS原型系统,以PLOS ONE数据集为例对框架效果进行了验证。总体上看,该框架能初步满足学术用户以图搜图、以图搜意与以图搜文的混合需求,本研究也是将移动视觉搜索技术引入学术情报服务,并深入到更细粒度的可视知识单元进行检索的探索型研究。
Visual resources in academic literature(VRAL) are important visual knowledge units. Providing a search service for VRAL in the mobile Internet environment would be an innovation value growth point of academic knowledge service in the field of information science. This paper explores a mobile visual search framework for VRAL(VRAL-MVS) from the perspective of "supply-demand-service." The framework integrates different levels of academic users' needs, and incorporates the underlying visual characteristics, the high-level semantic characteristics of VRAL, and the contextual text information features. The resource description and organization part of this framework focuses on the VRAL-MVS system requirements level identification and VRAL ontology construction. The retrieval part manages the system architecture and retrieval process, and develops a VRAL-MVS prototype system to verify the effects of the framework using the PLOS ONE datasets. In conclusion, this framework can meet the academic users' hybrid needs of searching for figure, for its meaning, and for article. This exploratory study introduces mobile visual search technology into academic information services and goes deeper into more fine-grained visual knowledge units for retrieval.
Visual resources in academic literature(VRAL) are important visual knowledge units. Providing a search service for VRAL in the mobile Internet environment would be an innovation value growth point of academic knowledge service in the field of information science. This paper explores a mobile visual search framework for VRAL(VRAL-MVS) from the perspective of "supply-demand-service." The framework integrates different levels of academic users' needs, and incorporates the underlying visual characteristics, the high-level semantic characteristics of VRAL, and the contextual text information features. The resource description and organization part of this framework focuses on the VRAL-MVS system requirements level identification and VRAL ontology construction. The retrieval part manages the system architecture and retrieval process, and develops a VRAL-MVS prototype system to verify the effects of the framework using the PLOS ONE datasets. In conclusion, this framework can meet the academic users' hybrid needs of searching for figure, for its meaning, and for article. This exploratory study introduces mobile visual search technology into academic information services and goes deeper into more fine-grained visual knowledge units for retrieval.
引文
[1]胡蓉,唐振贵,赵宇翔,等.文内视觉资源的分析框架与计量探索[J].情报学报,2017,36(2):141-151.
[2]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.
[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(4):19-25.
[4]马腾腾,赵宇翔,朱庆华.国外移动视觉搜索产品的比较分析研究[J].图书馆杂志,2016(9):81-88.
[5]爱奇艺App新增“以图搜剧”,首创AI剧照搜索引擎服务[EB/OL].[2017-07-06].http://news.ifeng.com/a/20170512/5108-3584_0.shtml.
[6]Zhang N,Mei T,Hua X S,et al.Tap Tell:Interactive visual search for mobile task recommendation[J].Journal of Visual Communication&Image Representation,2015,29:114-124.
[7]Chandrasekhar V,Takacs G,Chen D,et al.CHo G:Compressed histogram of gradients A low bit-rate feature descriptor[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,IEEE,2009:2504-2511.
[8]Tsai S S,Chen D,Takacs G,et al.Location coding for mobile image retrieval[C]//Proceedings of the International Conference on Mobile Multimedia Communications,London,UK,2009.
[9]Schroth G,Huitl R,Chen D,et al.Mobile visual location recognition[J].IEEE Signal Processing Magazine,2011,28(4):77-89.
[10]Ji R,Duan L Y,Chen J,et al.Location discriminative vocabulary coding for mobile landmark search[J].International Journal of Computer Vision,2012,96(3):290-314.
[11]Girod B,Chandrasekhar V,Chen D M,et al.Mobile visual search[J].IEEE Signal Processing Magazine,2011,28(4):61-76.
[12]陈长.面向数字图书馆的低比特移动视觉搜索研究与应用[D].北京:北京大学,2012.
[13]钟志鹏,王涌天,陈靖,等.一个基于移动视觉搜索技术的博物馆导览系统[J].计算机辅助设计与图形学学报,2012,24(4):555-562.
[14]Chen D M,Tsai S S,Girod B,et al.Building book inventories using smartphones[C]//Proceedings of the International Conference on Multimedea,Firenze,Italy,2010:651-654.
[15]齐云飞,赵宇翔,朱庆华.关联数据在数字图书馆移动视觉搜索系统中的应用研究[J].数据分析与知识发现,2017,1(1):81-90.
[16]Gudivada V N,Raghavan V V.Content-based image retrieval systems-guest editors’introduction[J].Computer,1995,8(8):18-22.
[17]蔡昌许.基于语义的图像标注与检索系统研究[D].武汉:武汉大学,2005.
[18]李胜辉.基于本体的图像语义的自动标注研究[D].长沙:湖南大学,2011.
[19]Neches R,Fikes R,Finin T,et al.Enabling Technology for Knowledge Sharing[J].Ai Magazine,1991,12(3):36-56.
[20]Fan J,Gao Y,Luo H.Hierarchical classification for automatic image annotation[C]//Proceedings of the International ACMSIGIR Conference on Research and Development in Information Retrieval,Amsterdam,the Netherlands,2007:111-118.
[21]邓涛,郭雷,杨卫莉.基于本体的图像语义标注与检索模型[J].计算机工程,2008,34(17):188-190.
[22]谭立球.基于本体的图像检索相关技术研究[D].长沙:中南大学,2009.
[23]彭杨.基于本体的动画素材图像语义标注研究[D].长沙:湖南师范大学,2009.
[24]张志武.基于本体和自动标注的网络邮票图像语义检索研究--以南京邮电大学数字邮票库为例[J].情报探索,2013(10):99-103.
[25]Brickley D,Miller L.FOAF vocabulary specification 0.99[OL].[2017-07-20].http://xmlns.com/foaf/spec/.
[26]Raimond Y,Abdallah S.The event ontology[OL].[2017-07-20].http://motools.sourceforge.net/event/event.html.
[27]Geo Names ontology[OL].[2017-07-20].http://www.geonames.org/ontology/documentation.html.
[28]Raimond Y,Abdallah S.The timeline ontology[OL].[2017-07-20].http://motools.sourceforge.net/timeline/timeline.html,2007.
[29]The ultimate MPEG-7 ontology[OL].[2017-07-20].http://mpeg7.org/mpeg-7-ontology/.
[30]SKOS simple knowledge organization system[OL].[2017-07-20].https://www.w3.org/2004/02/skos/.
[31]Shotton D.Ci TO,the citation typing ontology[J].Journal of Biomedical Semantics,2010,1(S1):S6.
[32]Giasson F,D’Arcus B.The bibliography ontology[OL].[2017-07-20].http://bibliontology.com.
[2]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.
[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(4):19-25.
[4]马腾腾,赵宇翔,朱庆华.国外移动视觉搜索产品的比较分析研究[J].图书馆杂志,2016(9):81-88.
[5]爱奇艺App新增“以图搜剧”,首创AI剧照搜索引擎服务[EB/OL].[2017-07-06].http://news.ifeng.com/a/20170512/5108-3584_0.shtml.
[6]Zhang N,Mei T,Hua X S,et al.Tap Tell:Interactive visual search for mobile task recommendation[J].Journal of Visual Communication&Image Representation,2015,29:114-124.
[7]Chandrasekhar V,Takacs G,Chen D,et al.CHo G:Compressed histogram of gradients A low bit-rate feature descriptor[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,IEEE,2009:2504-2511.
[8]Tsai S S,Chen D,Takacs G,et al.Location coding for mobile image retrieval[C]//Proceedings of the International Conference on Mobile Multimedia Communications,London,UK,2009.
[9]Schroth G,Huitl R,Chen D,et al.Mobile visual location recognition[J].IEEE Signal Processing Magazine,2011,28(4):77-89.
[10]Ji R,Duan L Y,Chen J,et al.Location discriminative vocabulary coding for mobile landmark search[J].International Journal of Computer Vision,2012,96(3):290-314.
[11]Girod B,Chandrasekhar V,Chen D M,et al.Mobile visual search[J].IEEE Signal Processing Magazine,2011,28(4):61-76.
[12]陈长.面向数字图书馆的低比特移动视觉搜索研究与应用[D].北京:北京大学,2012.
[13]钟志鹏,王涌天,陈靖,等.一个基于移动视觉搜索技术的博物馆导览系统[J].计算机辅助设计与图形学学报,2012,24(4):555-562.
[14]Chen D M,Tsai S S,Girod B,et al.Building book inventories using smartphones[C]//Proceedings of the International Conference on Multimedea,Firenze,Italy,2010:651-654.
[15]齐云飞,赵宇翔,朱庆华.关联数据在数字图书馆移动视觉搜索系统中的应用研究[J].数据分析与知识发现,2017,1(1):81-90.
[16]Gudivada V N,Raghavan V V.Content-based image retrieval systems-guest editors’introduction[J].Computer,1995,8(8):18-22.
[17]蔡昌许.基于语义的图像标注与检索系统研究[D].武汉:武汉大学,2005.
[18]李胜辉.基于本体的图像语义的自动标注研究[D].长沙:湖南大学,2011.
[19]Neches R,Fikes R,Finin T,et al.Enabling Technology for Knowledge Sharing[J].Ai Magazine,1991,12(3):36-56.
[20]Fan J,Gao Y,Luo H.Hierarchical classification for automatic image annotation[C]//Proceedings of the International ACMSIGIR Conference on Research and Development in Information Retrieval,Amsterdam,the Netherlands,2007:111-118.
[21]邓涛,郭雷,杨卫莉.基于本体的图像语义标注与检索模型[J].计算机工程,2008,34(17):188-190.
[22]谭立球.基于本体的图像检索相关技术研究[D].长沙:中南大学,2009.
[23]彭杨.基于本体的动画素材图像语义标注研究[D].长沙:湖南师范大学,2009.
[24]张志武.基于本体和自动标注的网络邮票图像语义检索研究--以南京邮电大学数字邮票库为例[J].情报探索,2013(10):99-103.
[25]Brickley D,Miller L.FOAF vocabulary specification 0.99[OL].[2017-07-20].http://xmlns.com/foaf/spec/.
[26]Raimond Y,Abdallah S.The event ontology[OL].[2017-07-20].http://motools.sourceforge.net/event/event.html.
[27]Geo Names ontology[OL].[2017-07-20].http://www.geonames.org/ontology/documentation.html.
[28]Raimond Y,Abdallah S.The timeline ontology[OL].[2017-07-20].http://motools.sourceforge.net/timeline/timeline.html,2007.
[29]The ultimate MPEG-7 ontology[OL].[2017-07-20].http://mpeg7.org/mpeg-7-ontology/.
[30]SKOS simple knowledge organization system[OL].[2017-07-20].https://www.w3.org/2004/02/skos/.
[31]Shotton D.Ci TO,the citation typing ontology[J].Journal of Biomedical Semantics,2010,1(S1):S6.
[32]Giasson F,D’Arcus B.The bibliography ontology[OL].[2017-07-20].http://bibliontology.com.