Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
2008-03-25
2008-03-25
Breene, John (Department: 2162)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000, C707S793000
Reexamination Certificate
active
10969326
ABSTRACT:
A multimedia object retrieval and annotation system integrates an annotation process with object retrieval and relevance feedback processes. The annotation process annotates multimedia objects, such as digital images, with semantically relevant keywords. The annotation process is performed in background, hidden from the user, as the user conducts normal searches. The annotation process is “semi-automatic” in that it utilizes both keyword-based information retrieval and content-based image retrieval techniques to automatically search for multimedia objects, and then encourages users to provide feedback on the retrieved objects. The user identifies objects as either relevant or irrelevant to the query keywords and based on this feedback, the system automatically annotates the objects with semantically relevant keywords and/or updates associations between the keywords and objects. As the retrieval-feedback-annotation cycle is repeated, the annotation coverage and accuracy of future searches continues to improve.
REFERENCES:
patent: 5020019 (1991-05-01), Ogawa
patent: 5572728 (1996-11-01), Tada et al.
patent: 5579471 (1996-11-01), Barber et al.
patent: 5594809 (1997-01-01), Kopec et al.
patent: 5721938 (1998-02-01), Stuckey
patent: 5855015 (1998-12-01), Shoham
patent: 5870754 (1999-02-01), Dimitrova et al.
patent: 5899999 (1999-05-01), De Bonet
patent: 5983237 (1999-11-01), Jain et al.
patent: 5995978 (1999-11-01), Cullen et al.
patent: 6041335 (2000-03-01), Merritt et al.
patent: 6076088 (2000-06-01), Paik et al.
patent: 6092080 (2000-07-01), Gustman
patent: 6105055 (2000-08-01), Pizano et al.
patent: 6285995 (2001-09-01), Abdel-Mottaleb et al.
patent: 6301586 (2001-10-01), Yang et al.
patent: 6314420 (2001-11-01), Lang et al.
patent: 6324545 (2001-11-01), Morag
patent: 6369811 (2002-04-01), Graham et al.
patent: 6408293 (2002-06-01), Aggarwal et al.
patent: 6442538 (2002-08-01), Nojima
patent: 6504571 (2003-01-01), Narayanaswami et al.
patent: 6557042 (2003-04-01), He et al.
patent: 6574632 (2003-06-01), Fox et al.
patent: 6643643 (2003-11-01), Lee et al.
patent: 6728406 (2004-04-01), Murao
patent: 6728706 (2004-04-01), Aggarwal et al.
patent: 6751613 (2004-06-01), Lee et al.
patent: 6901411 (2005-05-01), Li et al.
patent: 6915292 (2005-07-01), Lee et al.
patent: 7043474 (2006-05-01), Mojsilovic et al.
patent: 7111002 (2006-09-01), Zhang et al.
patent: 2002/0069218 (2002-06-01), Sull et al.
patent: 2007/0033170 (2007-02-01), Sull et al.
patent: 2007/0033292 (2007-02-01), Sull et al.
patent: 2007/0033515 (2007-02-01), Sull et al.
patent: 2007/0033521 (2007-02-01), Sull et al.
patent: 2007/0033533 (2007-02-01), Sull
patent: 2007/0038612 (2007-02-01), Sull et al.
patent: 2007/0044010 (2007-02-01), Sull et al.
patent: 11039325 (1999-02-01), None
patent: 2000112959 (2000-04-01), None
patent: WO0045342 (2000-08-01), None
Lu et al. A Unified framwork for semantic and feature based relevance feedback image retrieval system, International Multimedia conference, Proceedings of eighth ACM international conference on Multimedia, pp. 31-37, 2000.
Zhuang et al. Web-based image retrieval: a hygrid approach, Computer Graphics International 2001, pp. 62-69, Jul. 3-6, 2001.
Jing et al. Keyword propagation for image retrieval, Circuit and System, 2004, vol. 2, p. II-53-56, May 23-26, 2004.
Kim et al. QCluster: relevance feedback using adaptive clustering for content-based image retrieval, International conference on Management of Data, Proceeding of the 2003 ACM SIGMOD international conference on Management data, pp. 599-610, 2003.
Shyu et al. A unified framework for image database clustering and content-based retrieval, ACM international Workshop on Multimedia Databases, Proceeding of the 2nd ACM international workshop on Multimeida databases, pp. 19-27, 2004.
Ozetekin et al. Expert agreement and content based reranking in a meta search environment using Mearf, International World Wide Web Conference, Proceedings of the 11th international conference on World Wide Web, pp. 333-3344, 2002.
Atsushi, et al; “A Flexible Content-Based Image Retrieval System with Combined Scene Description Keyword”; 1996 IEEE Proceedings of Multimedia '96; pp. 201-208.
Uehara, et al., MIRACLES : Multimedia Information RetrievAL, Classification, and Exploration System—Application to Web Document Retrieval, Technical Report of the Institute of Electronics, Information and Communication Engineers, Japan, May 2, 2000, vol. 100, No. 31, pp. 17-24.
Amano et al., “A Flexible Content-Based Image Retrieval System with Combined Scene Description Keyword,” Jun. 17-23, 1996, IEEE Multimedia Computing and System, pp. 201-208.
Lai et al., “PBIR-MM: multimodal Image retrieval and annotation,” 2002 ISBN: 1-58113-620-X, pp. 421-422.
Shevade et al., “Vidya: An experiential annotation system,” 2003 ISBN: 1-508113, pp. 91-98.
Liu Wen-Yin
Zhang Hong-Jiang
Breene John
Microsoft Corporation
To Baoquoc N.
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