Automatic document classification using text and images

Details Automatic document classification using text and images Automatic document classification using text and images

2006-05-02

2006-05-02

Hong, Stephen S. (Department: 2178)

Data processing: presentation processing of document, operator i

Presentation processing of document

Layout

C715S252000, C706S015000, C706S020000

Reexamination Certificate

active

07039856

ABSTRACT:
A method and apparatus for automatic document classification using text and images. The present invention provides a method and apparatus for automatic document classification based on text and image. A new document is analyzed based on textual content as well as visual appearance. The new document is automatically stored in one or more mirror directories in which the new document would most likely be stored by the user of the device if the new document were placed manually. Determination of the most likely directories is based on an analysis of multiple documents stored by the user in various directories. The mirror directories are components of a mirror directory structure, which is a copy of a pre-existing directory structure, such as the user's hard drive. By storing the new document automatically, the user is relieved of the duty of manually selecting a directory for the new document.

REFERENCES:
patent: 5218646 (1993-06-01), Sirat et al.
patent: 5335290 (1994-08-01), Cullen et al.
patent: 5414781 (1995-05-01), Spitz et al.
patent: 5418946 (1995-05-01), Mori
patent: 5418951 (1995-05-01), Damashek
patent: 5436983 (1995-07-01), Bernzott et al.
patent: 5463773 (1995-10-01), Sakakibara et al.
patent: 5568640 (1996-10-01), Nishiyama et al.
patent: 5574802 (1996-11-01), Ozaki
patent: 5642288 (1997-06-01), Leung et al.
patent: 5717940 (1998-02-01), Peairs
patent: 5767978 (1998-06-01), Revankar et al.
patent: 5784487 (1998-07-01), Cooperman
patent: 5794236 (1998-08-01), Mehrle
patent: 5805731 (1998-09-01), Yaeger et al.
patent: 5812995 (1998-09-01), Sasaki et al.
patent: 5819295 (1998-10-01), Nakagawa et al.
patent: 5828771 (1998-10-01), Bloomberg
patent: 5832470 (1998-11-01), Morita et al.
patent: 5841905 (1998-11-01), Lee
patent: 5845304 (1998-12-01), Iijima
patent: 5848418 (1998-12-01), de Souza et al.
patent: 5862259 (1999-01-01), Bokser et al.
patent: 5889886 (1999-03-01), Mahoney
patent: 5909510 (1999-06-01), Nakayama
patent: 5918236 (1999-06-01), Wical
patent: 5930788 (1999-07-01), Wical
patent: 5937084 (1999-08-01), Crabtree et al.
patent: 5983246 (1999-11-01), Takano
patent: 5987460 (1999-11-01), Niwa et al.
patent: 5991709 (1999-11-01), Schoen
patent: 5995651 (1999-11-01), Gelenbe et al.
patent: 5999664 (1999-12-01), Mahoney et al.
patent: 6018728 (2000-01-01), Spence et al.
patent: 6081616 (2000-06-01), Vaezi et al.
patent: 6094652 (2000-07-01), Faisal
patent: 6098066 (2000-08-01), Snow et al.
patent: 6104835 (2000-08-01), Han
patent: 6137911 (2000-10-01), Zhilyaev
patent: 6148289 (2000-11-01), Virdy
patent: 6154737 (2000-11-01), Inaba et al.
patent: 6185550 (2001-02-01), Snow et al.
patent: 6192351 (2001-02-01), Persaud
patent: 6243501 (2001-06-01), Jamali
patent: 6253169 (2001-06-01), Apte et al.
patent: 6356922 (2002-03-01), Schilit et al.
patent: 6363178 (2002-03-01), Chiba et al.
patent: 6460034 (2002-10-01), Wical
patent: 6480627 (2002-11-01), Mathias et al.
patent: 07049875 (1995-02-01), None
Poynder, Web Research Engines?, Information World Review, Dec. 1996, p. 47, 2 pgs.
Dagan, Automation of Information Access Tasks: Technological Trends and Opportunities, Jun. 1998, vol. 22 p. 75, 4pgs.
Imade et al., Segmentation and Classification for Mixed Text/Image Documents Using Neural Network, IEEE 1993, pp. 930-934.
Farkas, Neural Networks and Document Classification, IEEE 1993, Electrical and Computer Engineering, pp. 1-4.
Farkas, Towards Classifying Full-Text Using Recurrent Neural Networks, IEEE 1995, pp. 511-514/.
Lln et al., Extracting Classification Knowledge of Internet Documents with Mining Term Association: a Semantic Approach, ACM 1998, pp. 241-249.
Doyle, Is Automatic Classification a Reasonable Application of Statistical Analysis of Text?, Journal of the Association for Computing Machinery, vol. 12, No. 4, Oct. 1965, pp. 473-489.
Borko et al., Automatic Document Classification PartII. Additional Experiments, Journal of the Association for Computing Machinery, vol. 11, No. 2, Apr. 1964, pp. 138-151.
Iwane et al., A Functional Classification Approach to Layout Analysis of Document Images, IEEE Oct. 1993, pp. 778-78.
Shih et al., A Document Segmentation, Classification and Recognition System, IEEE 1992, pp. 258-267.
Chakrabarti et al., Scalable Feature Selection, Classification and Signature Generation for Generating Large Text Databases into Hierarchical Topic Taxanomies, VLDB Journal 1998, pp. 163-178.
Iwane et al., A Functional Classification Approach to Layout Analysis of Document Images, IEEE 1993, pp. 778-781.
Antonacopoulos et al., Segmentation and Classification of Document Images, 1995, IEEE, pp. 1-7.
Azokly et al., A Language for Document Generic Layout Description and Its Use for Segmentation into Regions, 1995, IEEE, pp. 1123-1126.
Jain et al., Page Segmentation Using Document Model, 1997, IEEE, pp. 34-38.
Shih et al., Adaptive Document Block Segmentation and Classification, Oct. 1996, Systems, Man and Cybernetics, vol. 26, pp. 797-802.
Tin Ho, et al., “Decision Combination in Multiple Classifer Systems”,IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, No. 1, Jan. 1994.

Affiliated with

Also associated with

Rating

Automatic document classification using text and images does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Automatic document classification using text and images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automatic document classification using text and images will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3602342