Please use this identifier to cite or link to this item:
|Title:||Pattern-oriented associative rule-based patent classification|
|Keywords:||Associated rule-based approach|
|Citation:||He, C., Loh, H.T. (2010-03-15). Pattern-oriented associative rule-based patent classification. Expert Systems with Applications 37 (3) : 2395-2404. ScholarBank@NUS Repository. https://doi.org/10.1016/j.eswa.2009.07.069|
|Abstract:||This paper proposes an innovative pattern-oriented associative rule-based approach to construct automatic TRIZ-based patent classification system. Derived from associative rule-based text categorization, the new approach does not only discover the semantic relationship among features in a document by their co-occurrence, but also captures the syntactic information by manually generalized patterns. We choose 7 classes which address 20 of the 40 TRIZ Principles and perform experiments upon the binary set for each class. Compared with three currently popular classification algorithms (SVM, C4.5 and NB), the new approach shows some improvement. More importantly, this new approach has its own advantages, which were discussed in this paper as well. Crown Copyright © 2009.|
|Source Title:||Expert Systems with Applications|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jul 21, 2018
WEB OF SCIENCETM
checked on Jun 12, 2018
checked on May 18, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.