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Volumn 07-12-June-2015, Issue , 2015, Pages 3081-3089

Joint photo stream and blog post summarization and exploration

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; INTERNET; INTERPOLATION; KNOWLEDGE MANAGEMENT; PATTERN RECOGNITION; SEMANTICS; SOCIAL NETWORKING (ONLINE);

EID: 84959191227     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298927     Document Type: Conference Paper
Times cited : (29)

References (30)
  • 1
    • 0037213089 scopus 로고    scopus 로고
    • An information-theoretic perspective of tf-idf measures
    • A. Aizawa. An Information-Theoretic Perspective of TF-IDF Measures. Info. Proc. Manag., 39(1):45-65, 2003
    • (2003) Info. Proc. Manag. , vol.39 , Issue.1 , pp. 45-65
    • Aizawa, A.1
  • 2
    • 84887345951 scopus 로고    scopus 로고
    • A thousand frames in just a few words: Lingual description of videos through latent topics and sparse object stitching
    • P. Das, C. Xu, R. F. Doell, and J. J. Corso. A Thousand Frames in Just a Few Words: Lingual Description of Videos through Latent Topics and Sparse Object Stitching. In CVPR, 2013
    • (2013) CVPR
    • Das, P.1    Xu, C.2    Doell, R.F.3    Corso, J.J.4
  • 4
    • 84887365305 scopus 로고    scopus 로고
    • A sentence is worth a thousand pixels
    • S. Fidler, A. Sharma, and R. Urtasun. A Sentence is Worth a Thousand Pixels. In CVPR, 2013
    • (2013) CVPR
    • Fidler, S.1    Sharma, A.2    Urtasun, R.3
  • 7
    • 72449143639 scopus 로고    scopus 로고
    • Mining city landmarks from blogs by graph modeling
    • R. Ji, X. Xie, H. Yao, andW.-Y. Ma. Mining City Landmarks from Blogs by Graph Modeling. In ACMMM, 2009
    • (2009) ACMMM
    • Ji, R.1    Xie, X.2    Yao, H.3    Ma, W.-Y.4
  • 8
    • 33749563073 scopus 로고    scopus 로고
    • Training linear svms in linear time
    • T. Joachims. Training Linear SVMs in Linear Time. In KDD, 2006
    • (2006) KDD
    • Joachims, T.1
  • 9
    • 69549111057 scopus 로고    scopus 로고
    • Cutting-plane training of structural svms
    • T. Joachims, T. Finley, and C.-N. J. Yu. Cutting-Plane Training of Structural SVMs. Mach Learn, 77:27-59, 2009
    • (2009) Mach Learn , vol.77 , pp. 27-59
    • Joachims, T.1    Finley, T.2    Yu, C.-N.J.3
  • 10
    • 84911405209 scopus 로고    scopus 로고
    • Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction
    • G. Kim and E. P. Xing. Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction. In CVPR, 2014
    • (2014) CVPR
    • Kim, G.1    Xing, E.P.2
  • 11
    • 84911385330 scopus 로고    scopus 로고
    • Reconstructing storyline graphs for image recommendation from web community photos
    • G. Kim and E. P. Xing. Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos. In CVPR, 2014
    • (2014) CVPR
    • Kim, G.1    Xing, E.P.2
  • 14
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • J. Lafferty, A. McCallum, and F. C. Pereira. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML, 2001
    • (2001) ICML
    • Lafferty, J.1    McCallum, A.2    Pereira, F.C.3
  • 15
    • 84865623418 scopus 로고    scopus 로고
    • Enhancing diversity, coverage and balance for summarization through structure learning
    • L. Li, K. Zhou, G.-R. Xue, H. Zha, and Y. Yu. Enhancing Diversity, Coverage and Balance for Summarization through Structure Learning. In WWW, 2009
    • (2009) WWW
    • Li, L.1    Zhou, K.2    Xue, G.-R.3    Zha, H.4    Yu, Y.5
  • 17
    • 85162522202 scopus 로고    scopus 로고
    • Im2Text: Describing images using 1 million captioned photographs
    • V. Ordonez, G. Kulkarni, and T. L. Berg. Im2Text: Describing Images Using 1 Million Captioned Photographs. In NIPS, 2011
    • (2011) NIPS
    • Ordonez, V.1    Kulkarni, G.2    Berg, T.L.3
  • 18
    • 34547633089 scopus 로고    scopus 로고
    • Mining blog stories using community-based and temporal clustering
    • A. Qamra, B. Tseng, and E. Y. Chang. Mining Blog Stories Using Community-based and Temporal Clustering. In CIKM, 2006
    • (2006) CIKM
    • Qamra, A.1    Tseng, B.2    Chang, E.Y.3
  • 20
    • 84868695730 scopus 로고    scopus 로고
    • Automatic keyword extraction from individual documents
    • John Wiley and Sons, Ltd
    • S. Rose, D. Engel, N. Cramer, and W. Cowley. Automatic Keyword Extraction from Individual Documents. In Text Mining: Applications and Theory, pages 1-20. John Wiley and Sons, Ltd, 2010
    • (2010) Text Mining: Applications and Theory , pp. 1-20
    • Rose, S.1    Engel, D.2    Cramer, N.3    Cowley, W.4
  • 22
    • 85099019865 scopus 로고    scopus 로고
    • Introduction to the conll-2003 shared task: Language-independent named entity recognition
    • E. F. T. K. Sang and F. D. Meulder. Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition. CONLL, 2003
    • (2003) CONLL
    • Sang, E.F.T.K.1    Meulder, F.D.2
  • 23
    • 48849117633 scopus 로고    scopus 로고
    • Pegasos: Primal estimated sub-gradient solver for SVM
    • S. Shalev-Shwartz, Y. Singer, and N. Srebro. Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In ICML, 2007
    • (2007) ICML
    • Shalev-Shwartz, S.1    Singer, Y.2    Srebro, N.3
  • 24
    • 71149119963 scopus 로고    scopus 로고
    • Stochastic methods for l1 regularized loss minimization
    • S. Shalev-Shwartz and A. Tewari. Stochastic Methods for L1 Regularized Loss Minimization. In ICML, 2009
    • (2009) ICML
    • Shalev-Shwartz, S.1    Tewari, A.2
  • 25
    • 50949090870 scopus 로고    scopus 로고
    • Scene summarization for online image collections
    • I. Simon, N. Snavely, and S. M. Seitz. Scene Summarization for Online Image Collections. In ICCV, 2007
    • (2007) ICCV
    • Simon, I.1    Snavely, N.2    Seitz, S.M.3
  • 26
    • 77954006739 scopus 로고    scopus 로고
    • Photo tourism: Exploring photo collections in 3D
    • N. Snavely, S. M. Seitz, and R. Szeliski. Photo Tourism: Exploring Photo Collections in 3D. In SIGGRAPH, 2006
    • (2006) SIGGRAPH
    • Snavely, N.1    Seitz, S.M.2    Szeliski, R.3
  • 27
    • 78649395383 scopus 로고    scopus 로고
    • Piecewise pseudolikelihood for efficient training of conditional random fields
    • C. Sutton and A. McCallum. Piecewise Pseudolikelihood for Efficient Training of Conditional Random Fields. ICML, 2007
    • (2007) ICML
    • Sutton, C.1    McCallum, A.2
  • 28
    • 71149086466 scopus 로고    scopus 로고
    • Learning structural svms with latent variables
    • C.-N. J. Yu and T. Joachims. Learning Structural SVMs with Latent Variables. In ICML, 2009
    • (2009) ICML
    • Yu, C.-N.J.1    Joachims, T.2
  • 29
    • 56449130129 scopus 로고    scopus 로고
    • Predicting diverse subsets using structural svms
    • Y. Yue and T. Joachims. Predicting Diverse Subsets Using Structural SVMs. In ICML, 2008
    • (2008) ICML
    • Yue, Y.1    Joachims, T.2
  • 30
    • 84898772194 scopus 로고    scopus 로고
    • Learning the visual interpretation of sentences
    • C. L. Zitnick, D. Parikh, and L. Vanderwende. Learning the Visual Interpretation of Sentences. In ICCV, 2013.
    • (2013) ICCV
    • Zitnick, C.L.1    Parikh, D.2    Vanderwende, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.