NDLI: Automated categorization in the international patent classification

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Automated categorization in the international patent classification

Content Provider	ACM Digital Library
Author	Törcsvári, A. Fall, C. J. Karetka, G. Benzineb, K.
Abstract	A new reference collection of patent documents for training and testing automated categorization systems is established and described in detail. This collection is tailored for automating the attribution of international patent classification codes to patent applications and is made publicly available for future research work. We report the results of applying a variety of machine learning algorithms to the automated categorization of English-language patent documents. This procedure involves a complex hierarchical taxonomy, within which we classify documents into 114 classes and 451 subclasses. Several measures of categorization success are described and evaluated. We investigate how best to resolve the training problems related to the attribution of multiple classification codes to each patent document.
Starting Page	10
Ending Page	25
Page Count	16
File Format	PDF
ISSN	01635840
DOI	10.1145/945546.945547
Journal	ACM SIGIR Forum (SIGF)
Volume Number	37
Issue Number	1
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1978-08-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Ipc taxonomy Support vector machines Patent Automated categorization
Content Type	Text
Resource Type	Article
Subject	Management Information Systems Hardware and Architecture

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