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» Training a Selection Function for Extraction
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SIGIR
2011
ACM
12 years 10 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
IJCAI
1997
13 years 9 months ago
Extracting Propositions from Trained Neural Networks
This paper presents an algorithm for extract­ ing propositions from trained neural networks. The algorithm is a decompositional approach which can be applied to any neural networ...
Hiroshi Tsukimoto
ACSC
2003
IEEE
14 years 27 days ago
A Comparative Study for Domain Ontology Guided Feature Extraction
We introduced a novel method employing a hierarchical domain ontology structure to extract features representing documents in our previous publication (Wang 2002). All raw words i...
Bill B. Wang, Robert I. McKay, Hussein A. Abbass, ...
ASC
2004
13 years 7 months ago
Extracting rules from trained neural network using GA for managing E-business
Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to ...
Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami
ICPR
2006
IEEE
14 years 8 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...