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Table 2 Experimentation results for recognizing spatial attribute of events based on statistical machine learning approach

From: Analysis of syntactic and semantic features for fine-grained event-spatial understanding in outbreak news reports

Features Machine learning techniques Event class
   Normal Reporting Information Hypothetical Over all
11 location-related features CRF 84.8
(85.8,83.8)
82.7
(81.9,83.5)
62.6
(63.0,62.2)
88.1
(92.5,84.1)
81.3
(81.9,80.7)
  SVM 84.6
(85.8,83.5)
83.7
(82.7,84.6)
54.8
(55.2,54.5)
81.0
(85.0,77.3)
80.0
(80.7,79.4)
  C4.5 78.8
(79.6,77.9)
85.7
(85.2,86.2)
44.3
(45.0,43.6)
64.4
(65.1,63.6)
74.9
(75.5,74.4)
11 location-related features + event class CRF 87.2
(88.3,86.1)
86.1
(85.6,86.6)
68.2
(68.4,67.9)
76.2
(80.0,72.7)
83.8
(84.5,83.1)
  SVM 86.6
(87.7,85.5)
83.7
(82.7,84.6)
65.8
(66.2,65.4)
78.6
(82.5,75.0)
82.6
(83.3,82.0)
  C4.5 82.8
(84.1,81.6)
88.4
(87.9,88.9)
55.3
(56.8,53.8)
78.2
(79.1,77.3)
80.1
(81.0,79.2)
11 location-related features + subject type CRF 85.7
(87.4,84.1)
85.8
(84.9,86.6)
75.5
(76.0,75.0)
80.95
(85.0,77.3)
84.1
(85.1,83.1)
  SVM 84.8
(86.4,83.2)
83.7
(82.7,84.6)
58.7
(59.1,58.3)
83.3
(87.5,79.5)
80.8
(81.6,79.9)
  C4.5 79.5
(80.8,78.3)
87.2
(86.3,88.0)
61.3
(61.1,61.5)
61.2
(61.9,60.5)
78.0
(78.5,77.4)
11 location-related features + subject type + event class CRF 86.7
(88.1,85.4)
87.1
(86.4,87.8)
80.4
(80.6,80.1)
76.2
(80.0,72.7)
85.5
(86.3,84.7)
  SVM 86.1
(87.8,84.4)
84.0
(83.1,84.4)
68.4
(68.8,67.9)
81.0
(85.0,77.3)
82.8
(83.7,82.0)
  C4.5 80.2
(80.9,79.5)
88.0
(87.5,88.5)
66.7
(68.7,64.7)
64.4
(65.1,63.6)
79.5
(80.1,78.8)
  1. The attribute annotation results shown in this table were based on micro-averaging. The scores are shown in the form of "F-score (precision, recall)"