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Table 6:Statistical summary for orthogonality Orthogonality

in EXPLORING FEASIBILITY OF SOFTWARE DEFECTS ORTHOGONAL CLASSIFICATION
by Davide Falessi, Giovanni Cantone
"... In PAGE 9: ...1.3 Orthogonality Based on Table6 , which data are again not yet disaggregated with respect to expertise, orthogonality is 97%, while variance is 2. This expresses that, in the average, programmers commonly percept ODC with respect, and tend to provide just one classification per defect, whatever is their expertise.... ..."

Table 2: Orthogonal Array

in NO WARRANTY
by John D. Mcgregor, John D. Mcgregor, Norton L. Compton, Lt Col 2001
"... In PAGE 32: ... An exhaustive test set for these three factors, each with three levels, would require 27 test cases. Table2 shows an orthogonal array that addresses pair-wise combinations and uses nine test cases to cover three factors with three levels. Table 2: Orthogonal Array ... ..."

Table 1. First blind test

in Algorithms, Experimentation
by Magdalini Eirinaki, Charalampos Lampos, Stratos Paulakis, Michalis Vazirgiannis
"... In PAGE 6: ... We presented the users with the paths and the three sets (unlabeled) in random order and asked them to rate them as indifferent (i), useful (u) or very useful (vu). The outcome is summed in Table1 (each cell lists the percentage of users that gave the particular rating for the corresponding path): Table 1. First blind test ... ..."

Table 3 Results of blind test.

in An Algorithm for Anaphora Resolution in Spanish Texts
by Manuel Palomar, Lidia Moreno, Jesús Peral, Rafael Muñoz, Antonio Ferrández, Patricio Martínez-Barco, Maximiliano Saiz-noeda 2001
Cited by 5

Table 2: Blind Corpus Experiments

in Large scale experiments for semantic labeling of noun phrases in raw text
by Louise Guthrie, Roberto Basili, Fabio Zanzotto, Kalina Bontcheva, Hamish Cunningham, David Guthrie, Jia Cui, Marco Cammisa, Jerry Cheng-chieh Liu, Cassia Farria Martin, Kristiyan Haralambiev, Martin Holub, Klaus Machery, Fredrick Jelinek 2004
Cited by 1

Table 2: Blind Corpus Experiments

in Large scale experiments for semantic labeling of noun phrases in raw text
by Louise Guthrie, Roberto Basili, Fabio Zanzotto, Kalina Bontcheva, Hamish Cunningham, David Guthrie, Jia Cui, Marco Cammisa, Jerry Cheng-chieh Liu, Cassia Farria Martin, Kristiyan Haralambiev, Martin Holub, Klaus Machery, Fredrick Jelinek 2004
Cited by 1

Table 3 Results of blind test

in An Algorithm for Pronominal Anaphora Resolution
by Shalom Lappin, Herbert J. Leass

Table 2. Second blind test

in Algorithms, Experimentation
by Magdalini Eirinaki, Charalampos Lampos, Stratos Paulakis, Michalis Vazirgiannis

Table 2 Terms for LYSA with blinding

in www.elsevier.com/locate/entcs Static Validation of a Voting Protocol
by Christoffer Rosenkilde, Nielsen Esben, Heltoft Andersen, Hanne Riis Nielson

Table 2. Blind relevance judgments

in Roussinov and Robles-Flores How QA Technology Helps Locate Malevolent Online Content ABSTRACT How Question Answering Technology Helps to Locate Malevolent Online Content
by Dmitri Roussinov, Jose A. Robles-flores
"... In PAGE 6: ... The alternative hypothesis H1a was that QA performed better. Table2 (posted at http://www.... ..."
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