ABSTRACT
An important trend in Web information processing is the support of multimedia retrieval. However, the most prevailing paradigm for multimedia retrieval, content-based retrieval (CBR), is a rather conservative one whose performance depends on a set of specifically defined low-level features and a carefully chosen sample object. In this paper, an aggressive search mechanism called Octopus is proposed which addresses the retrieval of multi-modality data using multifaceted knowledge. In particular, Octopus promotes a novel scenario in which the user supplies seed objects of arbitrary modality as the hint of his information need, and receives a set of multi-modality objects satisfying his need. The foundation of Octopus is a multifaceted knowledge base constructed on a layered graph model (LGM), which describes the relevance between media objects from various perspectives. Link analysis based retrieval algorithm is proposed based on the LGM. A unique relevance feedback technique is developed to update the knowledge base by learning from user behaviors, and to enhance the retrieval performance in a progressive manner. A prototype implementing the proposed approach has been developed to demonstrate its feasibility and capability through illustrative examples.
- Benitez, A. B., Smith, J. R. and Chang, S. F. "MediaNet: A Multimedia Information Network for Knowledge Representation". In Proc. of the SPIE 2000 Conference on Internet Multimedia Management Systems, vol.4210, 2000.Google Scholar
- Bharat, K. and Henzinger, M. R., "Improved Algorithm for Topic Distilling in Hyperlinked Environments". In Proc. of the 21st Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, pp. 104--111, 1998. Google Scholar
Digital Library
- Brin, S. and Page, L., "The Anatomy of a Large-Scale Hypertextual Web Search Engine." In Proc. of the 7th Int. World Wide Web Conf, pp. 107--117, 1998. Google Scholar
Digital Library
- Chang, S. F., Chen, W., Meng, H. J., Sundaram, H. and Zhong, D., "VideoQ: An Automated Content Based Video Search System Using Visual Cues". In Proc. of ACM Multimedia, pp. 313--324, 1997. Google Scholar
Digital Library
- Chen, W. and Chang, S. F. "VISMAP: An Interactive Image/Video Retrieval System Using Visualization and Concept Maps", In Proc. of Int. Conf. on Image Processing (ICIP), Greece, October 2001.Google Scholar
Cross Ref
- Dean, J. and Henzinger, M. R., "Finding Related Pages on the Web." In Proc. of the 8th Int. World Wide Web Conf. pp. 389--401, 1999. Google Scholar
Digital Library
- Flickner, M., Sawhney, H., Niblack, W. and Ashley, J., "Query by image and video content: The QBIC system." IEEE Computer, pp. 23--32, 1995. Google Scholar
Digital Library
- Gibson, D., Kleinberg, J. M., and Paghavan, P., "Inferring Web Communities from Link Topology." In Proc. of the 9th Conf. on Hypertext and Hypermedia, pp.225--234, 1998. Google Scholar
Digital Library
- Google Search Engine. http://www.google.com.Google Scholar
- Henzinger, M. R., Heydon, A., Mitzenmacher, M. and Najork, M., "Measuring Index Quality using Random Walks on the Web". In Proc. of the 8th Int. World Wide Web Conf. pp213--225, 1999. Google Scholar
Digital Library
- Hofmann, T. and Buhmann, J. M., "Pairwise Data Clustering by Deterministic Annealing", in IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(1): 1--14, 1997. Google Scholar
Digital Library
- Huang, T. S., Mehrotra, S., and Ramchandran, K., "Multimedia analysis and retrieval system (MARS) project," In Proc of 33rd Annual Clinic on Library Application of Data Processing-Digital Image Access and Retrieval, 1996.Google Scholar
- Kleinberg, J. M., "Authoritative Sources in a Hyperlinked Environment." In Proc. of ACM-SIAM Symposium on Discrete Algorithms, pp. 668--677, 1998. Google Scholar
Digital Library
- Kumar, R., Raghavan, P., Pajagopalan, S., and Tomkins, A., "Trawling the Web for Emerging Cyber-communities". In Proc. of the 8th Int. World Wide Web Conf. pp. 403--415, 1999. Google Scholar
Digital Library
- Lempel, R. and Soffer, A., "PicASHOW: Pictorial Authority Search by Hyperlinks on the Web." In Proc. 10th Int. World Wide Web Conf., pp. 438--448, 2001. Google Scholar
Digital Library
- Li, Q., Yang, J., and Zhuang, Y. T., "Web-based Multimedia Retrieval: Balancing out between Common Knowledge and Personalized Views". In Proc. of 2nd Int. Conf. on Web Information System and Engineering, pp. 100--109, 2001. Google Scholar
Digital Library
- Lu, Y., Hu, C. H., Zhu, X. Q., Zhang, H. J. and Yang, Q. "A Unified Framework for Semantics and Feature Based Relevance Feedback in Image Retrieval Systems". In Proc. of ACM Multimedia, pp. 31--38, 2000. Google Scholar
Digital Library
- Pirolli, P., Pitkow, J., and Rao, R., "Silk rom a Sow's Ear: Extracting Usable Structure from the Web." In Proc. ACM SIGCHI Conf. on Human Factors in Computing Systems, pp. 383--390, 1997. Google Scholar
Digital Library
- Rafiei, D. and Mendelzon, A. O., "What is this Page Known for? Computing Web Page Reputations." In Proc. of Int. World Wide Web Conf. pp. 823--835, 2000. Google Scholar
Digital Library
- Smith, J. R. and Chang, S. F., "VisualSEEk: a fully automated content-based image query system," in Proc. of ACM Multimedia 96, pp. 87--98, 1996. Google Scholar
Digital Library
- Smith, J. R. and Chang, S. F., "Visually Searching the Web for Content. IEEE Multimedia Magazine, 4(3): 12--20, 1997. Google Scholar
Digital Library
- Tansley, R., "The Multimedia Thesaurus: An Aid for Multimedia Information Retrieval and Navigation", Master Thesis, Computer Science, University of Southampton, UK, 1998.Google Scholar
- Yang, J., Zhuang, Y. T., Li, Q., "Search for Multi-Modality Data in Digital Libraries", in Proc. of 2nd IEEE Pacific-Rim Conference on Multimedia, pp. 482--489, China, 2001. Google Scholar
Digital Library
Index Terms
OCTOPUS: aggressive search of multi-modality data using multifaceted knowledge base
Recommendations
Improvement of vector space information retrieval model based on supervised learning
IRAL '00: Proceedings of the fifth international workshop on on Information retrieval with Asian languagesThis paper proposes and method to improve retrieval performance of the vector space model (VSM) by utilizing user-supplied information of those documents that are relevant to the query in question. In addition to the user's relevance feedback ...
I-Quest: an intelligent query structuring based on user browsing feedback for semantic retrieval of video data
In spite of significant improvements in video data retrieval, a system has not yet been developed that can adequately respond to a user's query. Typically, the user has to refine the query many times and view query results until eventually the expected ...
A novel dynamic multi-model relevance feedback procedure for content-based image retrieval
This paper deals with the problem of image retrieval in large databases with a big semantic gap by a relevance feedback procedure. We present a novel algorithm for modelling the users's preferences in the content-based image retrieval system.The ...





Comments