A Deep Multi-View Learning Framework for City Event Extraction from Twitter Data Streams
Table 5: Evaluation results of the CRF-dictionary vs. CNN-enhanced tagging on London1 city and San Francisco datasets
['Location tagging performance', 'CRF-dictionary Tagging Recall', 'CRF-dictionary Tagging Precision', 'CRF-dictionary Tagging F-measure', 'CNN-enhanced LOCATION Tagging Recall', 'CNN-enhanced LOCATION Tagging Precision', 'CNN-enhanced LOCATION Tagging F-measure']
To better evaluate our claims we have also tested our proposed word tagging approaches on a more realistic dataset collected from London referenced as London1. Though basic pre-processing steps such as tokenizing and stop word removals have been included in the pipeline. The dataset is divided into two sub-corpora for training and testing the fused NER model.