Xiaofei He
Wei-Ying Ma
Abstract
Due to the rapid growth of the number of digital images on the Web, there is an increasing demand for an effective and efficient method for organizing and retrieving the available images. This article describes iFind, a system for clustering and searching WWW images. By using a vision-based page segmentation algorithm, a Web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. The textual information is used for image indexing. By extracting the page-to-block, block-to-image, block-to-page relationships through link structure and page layout analysis, we construct an image graph. Our method is less sensitive to noisy links than previous methods like PageRank, HITS, and PicASHOW, and hence the image graph can better reflect the semantic relationship between images. Using the notion of Markov Chain, we can compute the limiting probability distributions of the images, ImageRanks, which characterize the importance of the images. The ImageRanks are combined with the relevance scores to produce the final ranking for image search. With the graph models, we can also use techniques from spectral graph theory for image clustering and embedding, or 2-D visualization. Some experimental results on 11.6 million images downloaded from the Web are provided in the article.
- Belkin, M. and Niyogi, P. 2001. Laplacian eigenmaps and spectral techniques for embedding and clustering. In Advances in Neural Information Processing Systems 14. Vancouver, Canada.Google Scholar
- Brew, C. and Wade, S. 2002. Spectral clustering for German verbs. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Philadelphia, PA. Google ScholarDigital Library
- Brin, S. and Page, L. 1998. The anatomy of a large-scale hypertextual (Web) search engine. In Proceedings of the 7th ACM Conference on the World Wide Web. Brisbane, Australia. Google ScholarDigital Library
- Cai, D., He, X., Ma, W.-Y., Wen, J.-R., and Zhang, H.-J. 2004a. Organizing WWW images based on the analysis of page layout and Web link structure. In IEEE International Conference on Multimedia and Expo. Xi'an, China.Google Scholar
- Cai, D., He, X., Wen, J.-R., and Ma, W.-Y. 2004b. Block-level link analysis. In Proceedings of the ACM SIGIR Conference on Information Retrieval. Sheffield, UK. Google ScholarDigital Library
- Cai, D., Yu, S., Wen, J.-R., and Ma, W.-Y. 2003a. Extracting content structure for Web pages based on visual representation. In Proceedings of the 5th Asia Pacific Web Conference. Xi'an, China. Google ScholarDigital Library
- Cai, D., Yu, S., Wen, J.-R., and Ma, W.-Y. 2003b. Vips: A vision-based page segmentation algorithm. Microsoft Tech. Rep., MSR-TR-2003-79.Google Scholar
- Cai, D., Yu, S., Wen, J.-R., and Ma, W.-Y. 2004c. Block-based Web search. In Proceedings of the ACM SIGIR Conference on Information Retrieval. Sheffield, UK. Google ScholarDigital Library
- Chung, F. R. K. 1997. Spectral Graph Theory. Regional Conference Series in Mathematics, vol. 92.Google Scholar
- Frankel, C., Swain, M., and Athitsos, V. 1996. Webseer: An image search engine for the World Wide Web. Tech. Rep., TR-96-14, Department of Computer Science, University of Chicago. Google ScholarDigital Library
- Google. http://www.google.com/press/zeitgeist.html. Google zeitgeist---search patterns, trends, and surprises according to google.Google Scholar
- Guattery, S. and Miller, G. L. 2000. Graph embeddings and Laplacian eigenvalues. SIAM J. Matrix Anal. Appl. 21, 3, 703--723. Google ScholarDigital Library
- He, X., Yan, S., Hu, Y., Niyogi, P., and Zhang, H.-J. 2005. Face recognition using Laplacian-faces. IEEE Trans. Pattern Anal. Mach. Intell. 27, 3, 328--340. Google ScholarDigital Library
- Kleinberg, J. 1999. Authoritative sources in a hyperlinked environment. J. ACM 46, 5, 604--622. Google ScholarDigital Library
- Lempel, R. and Soffer, A. 2001. Picashow: Pictorial authority search by hyperlinks on the Web. In Proceedings of the 10th ACM Conference on World Wide Web. Hong Kong, China, 438--448. Google ScholarDigital Library
- Ma, W.-Y. and Manjunath, B. S. 1996. Texture features and learning similarity. In IEEE Conference on Computer Vision and Pattern Recognition. San Francisco, CA, 425--430. Google ScholarDigital Library
- Ma, W.-Y. and Manjunath, B. S. 1999. Netra: A toolbox for navigating large image databases. Multimedia Syst. 7, 3, 184--189. Google ScholarDigital Library
- Mohar, B. 1997. Some applications of Laplace eigenvalues of graphs. In Graph Symmetry: Algebraic Methods and Applications, G. Hahn and G. Sabidussi, Eds.Google Scholar
- Ng, A. Y., Jordan, M., and Weiss, Y. 2001. On spectral clustering: Analysis and an algorithm. In Advances in Neural Information Processing Systems 14. Vancouver, Canada.Google Scholar
- Robertson, S. E. and Walker, S. 1999. Okapi/keenbow at trec-8. In Eighth Text Retrieval Conference (TREC-8). 151--162.Google Scholar
- Rui, Y., Huang, T. S., Ortega, M., and Mehrotra, S. 1998. Relevance feedback: A power tool for interactive content-based image retrieval. IEEE Trans. Circ. Syst. Video Tech. 8, 5, 644--655. Google ScholarDigital Library
- Sclaroff, S., Taycher, L., and Cascia, M. L. 1994. Imagerover: A content-based image browser for the World Wide Web. In IEEE Workshop on Content-Based Access of Image and Video Libraries. San Juan, Puerto Rico. Google ScholarDigital Library
- Shi, J. and Malik, J. 2000. Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22, 8, 888--905. Google ScholarDigital Library
- Smith, J. and Chang, S.-F. 1996. Visualseek: A fully automated content-based image query system. In Proceedings of the ACM Conference on Multimedia. New York. Google ScholarDigital Library
- Smith, J. and Chang, S.-F. 1997. Webseek, a content-based image and video search and catalog tool for the Web. IEEE Multimedia.Google Scholar
- Song, R., Liu, H., Wen, J.-R., and Ma, W.-Y. 2004. Learning block importance models for Web pages. In Proceedings of the 13th ACM Conference on World Wide Web. Google ScholarDigital Library
- Wen, J.-R., Song, R., Cai, D., Zhu, K., Yu, S., Ye, S., and Ma, W.-Y. 2003. Microsoft Research asia at the Web track of TREC 2003. In Twelfth Text Retrieval Conference (TREC-12).Google Scholar
Index Terms
- Clustering and searching WWW images using link and page layout analysis
Recommendations
Hierarchical clustering of WWW image search results using visual, textual and link information
MULTIMEDIA '04: Proceedings of the 12th annual ACM international conference on MultimediaWe consider the problem of clustering Web image search results. Generally, the image search results returned by an image search engine contain multiple topics. Organizing the results into different semantic clusters facilitates users' browsing. In this ...
Why People Search for Images using Web Search Engines
WSDM '18: Proceedings of the Eleventh ACM International Conference on Web Search and Data MiningWhat are the intents or goals behind human interactions with image search engines? Knowing why people search for images is of major concern to Web image search engines because user satisfaction may vary as intent varies. Previous analyses of image ...
Combining anchor text categorization and graph analysis for paid link detection
WWW '09: Proceedings of the 18th international conference on World wide webIn order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid links is important for a web search engine to produce highly relevant ...
Comments