On the value of temporal information in information retrieval
ACM SIGIR Forum
Extracting and Exploring the Geo-Temporal Semantics of Textual Resources
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Proceedings of the 6th Workshop on Geographic Information Retrieval
Workshop on Geographical Information Retrieval
Extraction and exploration of spatio-temporal information in documents
Proceedings of the 6th Workshop on Geographic Information Retrieval
HeidelTime: High quality rule-based extraction and normalization of temporal expressions
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Studying how the past is remembered: towards computational history through large scale text mining
Proceedings of the 20th ACM international conference on Information and knowledge management
Identification of top relevant temporal expressions in documents
Proceedings of the 2nd Temporal Web Analytics Workshop
Tracking entities in web archives: the LAWA project
Proceedings of the 21st international conference companion on World Wide Web
BabelNetXplorer: a platform for multilingual lexical knowledge base access and exploration
Proceedings of the 21st international conference companion on World Wide Web
Event-centric search and exploration in document collections
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
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Spatial and temporal data have become ubiquitous in many application domains such as the Geosciences or life sciences. Sophisticated database management systems are employed to manage such structured data. However, an important source of spatio-temporal information that has not been fully utilized are unstructured text documents. In documents, combinations of temporal and spatial expressions form events, which can be mapped to a database structure and organized into trajectories that can be explored. In this context, the coupling of information retrieval techniques with spatio-temporal database concepts leads to new ways for managing and exploring document collections. In this demonstration, we present TimeTrails, a system for the extraction, querying, storage, and exploration of spatio-temporal information embedded in text documents. The user can query a document collection, and TimeTrails visualizes the spatio-temporal information extracted from relevant documents as document trajectories, resulting in a map-based view of documents. This view helps the user to explore the temporal and spatial content of documents in a meaningful way and to further restrict search results using spatial and temporal predicates.