Abstract
The explosive growth of World Wide Web has already made it the biggest image repository. Despite some image search engines provide con-venient access to web images, they frequently yield unwanted results. Locating needed and relevant images remains a challenging task. This paper proposes a novel ranking model named EagleRank for web image search engine. In EagleRank, multiple sources of evidence related to the images are considered, including image surrounding text passages, terms in special HTML tags, website types of the images, the hyper-textual structure of the web pages and even the user feedbacks. Meanwhile, the flexibility of EagleRank allows it to combine other potential factors as well. Based on inference network model, EagleRank also gives sufficient support to Boolean AND and OR operators. Our experimental results indicate that EagleRank has better performance than traditional approaches considering only the text from web pages.
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References
Coelho, T.A.S., Calado, P.P., Souza, L.V., Ribeiro-Neto, B., Muntz, R.: Image Retrieval Using Multiple Evidence Ranking. IEEE Trans. KDE 16(4), 408–417 (2004)
Metzler, D., Manmatha, R.: An Inference Network Approach to Image Retrieval. In: Enser, P.G.B., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds.) CIVR 2004. LNCS, vol. 3115, pp. 42–50. Springer, Heidelberg (2004)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. China Machine Press (2004)
Broglio, J., Callan, J.P., Croft, W.B., Nachbar, D.W.: Document Retrieval and Routing Using the INQUERY System. In: Harman, D.K. (ed.) Overview of the TREC-3, pp. 29–38 (1995)
Tsymbalenko, Y., Munson, E.V.: Using HTML Metadata to Find Relevant Image on the World Wide Web. In: Proc. Internet Computing 2001, LasVegas, June 2001, vol. II, pp. 842–848. CSREA press (2001)
Brin, S., Page, L.: The Anatomy of a Large-Scale Hypertextual Web Search Engine. In: Proc. 7th WWW Conference, pp. 107–117. Elsevier Science, Amsterdam (1998)
Lei, M., Wang, J.Y., Chen, B.J., Li, X.M.: Improved Relevance Ranking in WebGather. Journal of Computer Science and Technology 16(5), 410–417 (2001)
Kherfi, M.L., Ziou, D., Bernardi, A.: Image Retrieval from the World Wide Web: Issues, Techniques, and Systems. ACM Computing Surveys 36(1), 25–67 (2004)
Zhuang, Y.T., Pan, Y.H., Wu, F.: Web-based Multimedia Information Analysis and Retrieval. TsingHua University Press (2002)
Munson, E.V., Tsymbalenko, Y.: To search for Images on the Web, Look at the Text, Then Look at images. In: Proc. 1st Int’l workshop on web document analysis (September 2001)
Ghoshal, A., Ircing, P., Khudanpur, S.: Hidden Markov Models for Automatic Annotation and Content-Based Retrieval of Images and Video. In: Proc. 28th Int’l ACM SIGIR conf. on Research and development in IR, pp. 544–551 (2005)
Carneiro, G., Vasconcelos, N.: A Database Centric View of Semantic Image Annotation and Retrieval. In: Proc. 28th Int’l ACM SIGIR conf. on Research and development in IR, pp. 559–566 (2005)
Stevenson, K., Leung, C.: Comparative Evaluation of Web Image Search Engines For Multimedia Applications. In: IEEE Int’l Conf. on Multimedia and Expo (2005)
Frankel, C., Swain, M., Athitsos, V.: Webseer: An Image Search Engine for the World Wide Web. In: IEEE Conf. on CVPR (1997)
Rathi, V., Majumdar, A.K.: Content based image search over the World Wide Web. In: Indian Conf. on Computer Vision, Graphics and Image Processing (2002)
Entlich, R.: FAQ-Image search engine, http://www.rlg.org/preserv/diginews/diginews5-6.html#faq
QBIC Home Page, http://wwwqbic.almaden.ibm.com
Zhuang, Y.T., Li, Q., Lau, R.W.H.: Web-Based Image Retrieval: a Hybrid Approach. In: Proc. Computer Graphics Int’l 2001, pp. 62–69 (2001)
Zhang, C., Chai, J.Y., Jin, R.: User Term Feedback in Interactive Text-based Image Retrieval. In: Proc. SIGIR 2005, pp. 51–58 (2005)
Nivre, J.: Dependency Grammar and Dependency Parsing, MSI report 05133, Växjö University: School of Mathematics and System Engineering
Bikel, D.M., Schwartz, R., Weischedel, R.M.: An Algorithm that Learns What’s in a Name. Machine Learning 34, 211–231 (1999)
Choi, Y., Rasmussen, E.M.: Searching for Images: The Analysis of Users’ Queries for Image Retrieval in American History. Journal of the America Society for Information Science and Technology 54(6), 498–511 (2003)
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Liu, K., Chen, W., Chen, C., Bu, J., Wang, C., Huang, P. (2006). EagleRank: A Novel Ranking Model for Web Image Search Engine. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_86
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DOI: https://doi.org/10.1007/11922162_86
Publisher Name: Springer, Berlin, Heidelberg
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