Automatic Extraction of Spatio-Temporal Information from Arabic Text Documents

Unstructured Arabic text documents are an important source of geographical and temporal information. The possibility of automatically tracking spatio-temporal information, capturing changes relating to events from text documents, is a new challenge in the fields of geographic information retrieval (GIR), temporal information retrieval (TIR) and natural language processing (NLP). There was a lot of work on the extraction of information in other languages that use Latin alphabet, such as English, French, or Spanish, by against the Arabic language is still not well supported in GIR and TIR and it needs to conduct more researches. In this paper, we present an approach that support automated exploration and extraction of spatio-temporal information from Arabic text documents in order to capture and model such information before it can be utilized in search and exploration tasks. The system has been successfully tested on 50 documents that include a mixture of types of Spatial/temporal information. The result achieved 91.01% of recall and of 80% precision. This illustrates that our approach is effective and its performance is satisfactory.