Hierarchical categorization method and system with automatic...

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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Details

C706S012000, C706S014000, C706S020000, C706S047000, C382S226000

Reexamination Certificate

active

07349917

ABSTRACT:
The present invention relates generally to the classification of items into categories, and more generally, to the automatic selection of different classifiers at different places within a hierarchy of categories. An exemplary hierarchical categorization method uses a hybrid of different classification technologies, with training-data based machine-learning classifiers preferably being used in those portions of the hierarchy above a dynamically defined boundary in which adequate training data is available, and with a-priori classification rules not requiring any such training-data being used below that boundary, thereby providing a novel hybrid categorization technology that is capable of leveraging the strengths of its components. In particular, it enables the use of human-authored rules in those finely divided portions towards the bottom of the hierarchy involving relatively close decisions for which it is not practical to create in advance sufficient training data to ensure accurate classification by known machine-learning algorithms, while still facilitating eventual change-over within the hierarchy to machine learning algorithms as sufficient training data becomes available to ensure acceptable performance in a particular sub-portion of the hierarchy.

REFERENCES:
patent: 6092059 (2000-07-01), Straforini et al.
patent: 6243695 (2001-06-01), Assaleh et al.
patent: 2003/0059106 (2003-03-01), Gutta
McCallum, Andrew et al., “Text Classification by Bootstrapping with Keywords, EM and Shrinkage,” ACL '99 Workshop for Unsupervised Learning in Natural Language Processing, 1999, 7 pages.
Dumais, Susan et al., “Hierarchical Classification of Web Content,” SIGIR 2000: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul. 2000, 8 pages.

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