Adding dominant media elements to search results

Details Adding dominant media elements to search results Adding dominant media elements to search results

2011-08-09

2011-08-09

Lewis, Cheryl (Department: 2155)

Data processing: database and file management or data structures

Database and file access

Post processing of search results

C707S805000, C715S234000

Reexamination Certificate

active

07996395

ABSTRACT:
A method and system for determining dominance of the media elements of display pages is provided. The dominance system provides a scoring mechanism for scoring the dominance of media elements of display pages based on features of each media element of the display page. To generate the scores for the media elements of the display page, the dominance system first identifies the media elements and then identifies the features of the media elements. The dominance system then scores the identified media elements using the provided scoring mechanism and the identified features.

REFERENCES:
patent: 6271840 (2001-08-01), Finseth et al.
patent: 6643641 (2003-11-01), Snyder
patent: 6816847 (2004-11-01), Toyama
patent: 7433895 (2008-10-01), Li et al.
patent: 2001/0056418 (2001-12-01), Youn
patent: 2003/0195883 (2003-10-01), Mojsilovic et al.
patent: 2003/0229628 (2003-12-01), Banerjee et al.
patent: 2003/0231806 (2003-12-01), Troyanker
patent: 2004/0101156 (2004-05-01), Kacker
patent: 2004/0243541 (2004-12-01), Zhang et al.
patent: 2005/0120311 (2005-06-01), Thrall
patent: 2005/0223027 (2005-10-01), Lawrence et al.
patent: 1 089 198 (2001-04-01), None
patent: 2402470 (2004-08-01), None
patent: WO-02/39207 (2002-05-01), None
patent: WO-03/102819 (2003-12-01), None
patent: WO-2004/046982 (2004-06-01), None
Xiao, Rong et al., “Boosting Chain Learning for Object Detection,” Proceedings of the Ninth IEEE International Conference on Computer Vision (ICCV 2003) , 2003 (7 pages).
Wang, Zhou et al., “Image Quality Assessment: From Error Visibility to Structural Similarity,” IEEE Transactions on Image Processing, vol. 13, No. 4, Apr. 2004 (13 pages).
Tong, Hanghang et al., “Learning No-Reference Quality Metric by Examples,” Department of Automation, Tsinghua University, Beijing, China (8 pages).
Ratsch, Gunnar et al., Soft Margins for AdaBoost, NeuroCOLT2 Technical Report Series, NC-TR-1998-021, Sep. 1998 (28 pages).
Lu, Guojun et al., “An Integrated WWW Image Retrieval System,” Copyright 1999, Guojun Lu and Ben Williams (9 pages).
Freund, Yoav et al., “An Efficient Boosting Algorithm for Combining Preferences,” Journal of Machine Learning Research 4, 2003 (37 pages).
Almeida Tatiana et al., “Image Retrieval Using Multiple Evidence Ranking,” IEEE Transactions on Knowledge and Data Engineering, vol. 16, No. 4, Apr. 2004 (10 pages).
Cai, Deng et al., “Hierarchical Clustering of WWW Image Search REsults Using Visual, Textual and Link Information,” MM, Oct. 10-16, 2004, New York, New York, Copyright 2004 (8 pages).
Brin, Sergey, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” Computer Science Department, Stanford University, Stanford, California (26 pages) http://www7.scu.edu.au/programme/fullpapers/1921/com1921.html.
Google Zeitgeist, Search Patterns, Trends and Surprises According to Google (3 pages) http://www.google.com/press/zeitgeist.html.
Vapnik, Vladimir N., “Chapter 4 Controlling the Generalization Ability of Learning Processes,” The Nature of Statistical Learning Theory, Springer-Verlag New York, Inc., 1995, pp. 89-118.
Xue, Gui-Rong et al., “Optimizing Web Search Using Web Click-Through Data,” CIKM, ACM, 2004, pp. 118-126.
Fan, Jianping et al., “Multi-Level Annotation of Natural Scenes Using Dominant Image Components and Semantic Concepts,” ACM Multimedia, 2004.
Sclaroff, Stan et al., “ImageRover: A Content-Based Image Browser for the World Wide Web,” BU CS TR97-005, IEEE Workshop on Content-based Access of Image and Video Libraries, Jun. 1997, pp. 1-8.
Hartmann, Alexander et al., “Automatic Classification of Images on the Web,” Storage and Retrieval for Media Databases, 2001, 10 pages.
Arentz, Will Archer et al., “Classifying Offensive Sites Based on Image Content,” Computer Vision and Image Understanding, Elsevier Inc., 2003.
Liu, Hao et al., “Effective Browsing of Web Image Search Results,” MIR, ACM, 2004.
Joachims, T. , “Optimizing Search Engines Using Clickthrough Data ,” In Proceeding of the ACM Conference on Knowledge Discovery and Data Mining, 2002 (10 pages).
Wynblatt, M. et al., Web Page Caricatures:Multimedia Summaries for WWW Documents, 1998, Proceedings, IEEE, Jun. 28-Jul. 1, 1998.
Jay et al., “How People Use Presentation To Search For a Link:Expanding The Understanding Of Accessibility On The Web,” Universal Access in the Information Society, 2007.
Poulson, David et al., “Making the Internet Accessible for People with Cognitive and Communication Impairments,” Universal Access in the Information Society, Springer Berlin/Heidelberg, vol. 3, Mar. 2004.

Affiliated with

Also associated with

Rating

Adding dominant media elements to search results does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Adding dominant media elements to search results, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Adding dominant media elements to search results will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2674235