Automatic layout criterion selection

Data processing: presentation processing of document – operator i – Presentation processing of document – Layout

Reexamination Certificate

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C715S253000

Reexamination Certificate

active

07836397

ABSTRACT:
A document publishing system includes a layout quality tagger (40) for tagging candidate layouts (36) of selected content (32) with overall layout quality criterion values using an overall layout quality criterion (16, 18) combining a set of component quality criteria as a weighted linear combination of kernels. Each kernel corresponds to an inner product comparing component quality criteria values of a training layout with corresponding component quality criteria an input layout. A trainer (14) trains the overall layout quality criterion using the training layouts (12). A layout selector (42) validates a layout for the selected content (32) based at least on the tagged overall layout quality criterion value of the layout. A publisher (50, 52, 54) publishes the validated layout (44) including the selected content (32).

REFERENCES:
patent: 5182793 (1993-01-01), Alexander et al.
patent: 5649068 (1997-07-01), Boser et al.
patent: 6327581 (2001-12-01), Platt
patent: 7062466 (2006-06-01), Wagner et al.
patent: 7451140 (2008-11-01), Purvis et al.
patent: 2004/0019851 (2004-01-01), Purvis et al.
patent: 2004/0205643 (2004-10-01), Harrington
patent: 2005/0028074 (2005-02-01), Harrington et al.
patent: 2005/0028075 (2005-02-01), Harrington et al.
patent: 2005/0028076 (2005-02-01), Harrington et al.
patent: 2005/0028096 (2005-02-01), Harrington et al.
patent: 2005/0028097 (2005-02-01), Harrington et al.
patent: 2005/0028098 (2005-02-01), Harrington et al.
patent: 2005/0028099 (2005-02-01), Harrington et al.
patent: 2005/0071755 (2005-03-01), Harrington et al.
patent: 2005/0154980 (2005-07-01), Purvis et al.
Cristianini et al., “The Learning Methodology,”An Introduction to Support Vector Machines and Other Kernel-based Learning Methods,pp. 1-51, Cambridge Univ. Press (2000).
Goutte et al., “Combining labelled and unlabelled data: a case study on . . . ,” Proc. of CoNLL-2002, 7 pp.
Cristianini et al., “On Kernel Target Alignment,” Journal of Machine Learning Research 1, pp. 1-31, (2002).
Muller et al., “An Introduction to Kernel-Based Learning Algorithms,” IEEE Transactions on Neural Networks, vol. 12 No. 2, pp. 181-2001, Mar. 2001.
Reich, AI in Engineering, 8(2):141-153, pp. 15-27, 1993.
Demiriz et al., “Linear Programming Boosting via Column Generation,” Machine Learning, 46, pp. 225-254, Kluwer Academic Publishers. Manufactured in The Netherlands, 2002.
Shashua et al., “Taxonomy of Large Margin Principle for Ordinal Regression Problems,” Technical Report, 2002—No. 39, Leibniz Center for Research, School of Computer Science and Eng., the Hebrew University of Jerusalem, (2002).
Vert et al., “A primer on kernel methods,” in Kernel Methods in Computational Biology, MIT Press, Cambridge, MA, US, pp. 1-42 (preprint), Aug. 2004.

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