Abstract
Showing video and article on the same page, as done by official web agencies such as CNN.com and Yahoo!, provides a practical way for convenient information digestion. However, as the absence of article, this layout is infeasible for mainstream web video repositories like YouTube. This paper investigates the problem of hyperlinking web videos to relevant articles available on the Web. Given a video, the task is accomplished by firstly identifying its contextual tags (e.g., who are doing what at where and when) and then employing a search based association to relevant articles. Specifically, we propose a multiple tag property exploration (mTagPE) approach to identify contextual tags, where tag relevance, tag clarity and tag correlation are defined and measured by leveraging visual duplicate analyses, online knowledge bases and tag co-occurrence. Then, the identification task is formulated as a random walk along a tag relation graph that smoothly integrates the three properties. The random walk aims at picking up relevant, clear and correlated tags as a set of contextual tags, which is further treated as a query to issue commercial search engines to obtain relevant articles. We have conducted experiments on a largescale web video dataset. Both objective performance evaluations and subjective user studies show the effectiveness of the proposed hyperlinking. It produces more accurate contextual tags and thus a larger number of relevant articles than other approaches.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Halvey, M.J., Keane, M.T.: Analysis of Online Video Search and Sharing. In: Proceeding of HT, pp. 217–226 (2007)
Li, X., Snoek, C.G.M., Worring, M.: Learning Social Tag Relevance by Neighbor Voting. IEEE Transactions on Multimedia 11(7), 1310–1322 (2009)
Chen, Z.N., Cao, J., Xia, T., Song, Y.C., Zhang, Y.D., Li, J.T.: Web Video Retagging. Multimedia Tools and Applications 55(1), 53–82 (2011)
Moxley, E., Mei, T., Manjunath, B.S.: Video Annotation through Search and Graph Reinforcement Mining. IEEE Transactions on Multimedia 12(3), 184–193 (2010)
Snoek, C.G.M., et al.: The MediaMill TRECVID 2008 Semantic Video Search Engine. In: Proceeding of TRECVID (2008)
Jiang, Y.G., Ngo, C.W., Yang, J.: Towards Optimal Bag-of-Features for Object Categorization and Semantic Video Retrieval. In: Proceeding of ACM CIVR, pp. 494–501 (2007)
Qi, G.J., Hua, X.S., Rui, Y.: Correlative Multilabel Video Annotation with Temporal Kernels. ACM Trans. Multimedia Comput. Commun. Appl. 5(1), 1–27 (2008)
Aradhye, H., Toderici, G., Yagnik, J.: Video2Text: Learning to Annotate Video Content. In: Proceeding of IEEE Data Mining Workshops, pp. 144–151 (2009)
Zhao, W.L., Wu, X., Ngo, C.W.: On the Annotation of Web Videos by Efficient Near-duplicate Search. IEEE Transactions on Multimedia 12(5), 448–461 (2010)
Siersdorfer, S., Pedro, J.S., Sanderson, M.: Content Redundancy in YouTube and its Application to Video Tagging. ACM Transactions on Information Systems, 301–331 (2011)
Liu, D., Hua, X.S., Yang, L., Wang, M., Zhang, H.J.: Tag Ranking. In: Proceeding of WWW, pp. 351–360 (2009)
Liu, D., Yan, S.C., Hua, X.S., Zhang, H.J.: Image Retagging using Collaborative Tag Propagation. IEEE Transactions on Multimedia 13(4), 702–712 (2011)
Liu, D., Hua, X.S., Zhang, H.J.: Content-based Tag Processing for Internet Social Images. Multimedia Tools and Applications 51(2), 723–738 (2011)
Sang, J., Xu, C.S., Liu, J.: User-aware image tag refinement via ternary semantic analysis. IEEE Transactions on Multimedia 14(3), 883–895 (2012)
Zhang, X.M., Huang, Z., Shen, H.T., Yang, Y., Li, Z.J.: Automatic tagging by exploring tag information capability and correlation. World Wide Web 15(3), 233–256 (2012)
Ballan, L., Bertini, M., Bimbo, A.D., Meoni, M., Serra, G.: Tag Suggestion and Localization in User-Generated Videos based on Social Knowledge. In: Proceeding of WSM, pp. 3–8 (2010)
Okuoka, T., Takahashi, T., Deguchi, D., Ide, I., Murase, H.: Labeling News Topic Threads with Wikipedia Entries. In: Proceeding of IEEE ISM, pp. 501–504 (2009)
Liu, X.L., Troncy, R., Huet, B.: Finding Media Illustrating Event. In: Proceeding of ICMR, pp. 1–8 (2011)
Eskevich, M., Jones, G.J.F., Aly, R.: Multimedia Information Seeking through Search and Hyperlinking. In: Proceeding of ACM ICMR, pp. 287–294 (2013)
Tan, S., Ngo, C.W., Tan, H.K., Pang, L.: Cross Media Hyperlinking for Search Topic Browsing. In: Proceeding of ACM Multimedia, pp. 1095–1098 (2011)
Hsu, W., Kennedy, L., Chang, S.F.: Video Search Reranking through Random Walk over document-level context graph. In: Proceeding of ACM Multimedia, pp. 971–980 (2007)
Yao, T., Ngo, C.W., Mei, T.: Circular Reranking for Visual Search. IEEE Transactions on Multimedia 12(5), 1644–1655 (2013)
Cao, J., Zhang, Y.D., Song, Y.C., Chen, Z.N., Zhang, X., Li, J.T.: MCG-WEBV: A Benchmark Dataset for Web Video Analysis. Technical Report, pp. 1-10 (2009)
Chen, Z.N., Cao, J., Song, Y.C., Guo, J.B., Zhang, Y.D., Li, J.T.: Context-Oriented Web Video Tag Recommendation. In: Proceeding of WWW, pp. 1079–1080 (2010)
Chen, Z.N., Cao, J., Song, Y.C., Zhang, Y.D., Li, J.T.: Web Video Categorization based on Wikipedia Categories and Content-Duplicate Open Resources. In: Proceeding of ACM Mutimedia, pp. 1107–1110 (2010)
Toutanova, K., Klein, D., Manning, C., Singer, Y.: Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. In: Proceeding of HLT-NAACL, pp. 252–259 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Chen, Z., Feng, B., Xie, H., Zheng, R., Xu, B. (2014). Video to Article Hyperlinking by Multiple Tag Property Exploration. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8325. Springer, Cham. https://doi.org/10.1007/978-3-319-04114-8_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-04114-8_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04113-1
Online ISBN: 978-3-319-04114-8
eBook Packages: Computer ScienceComputer Science (R0)