Solving conflicts in information merging by a flexible interpretation of atomic propositions
Artificial Intelligence
Temporally anchored relation extraction
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Modeling geographic, temporal, and proximity contexts for improving geotemporal search
Journal of the American Society for Information Science and Technology
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When searching for information about historical events, queries are naturally formulated using temporal constraints. However, the structured temporal information needed to support such constraints is usually not available to information retrieval systems. Furthermore, the temporal boundaries of most historical events are inherently ill-defined, calling for suitable extensions of classical temporal reasoning frameworks. In this paper, we propose a framework based on a fuzzification of Allen’s Interval Algebra to cope with these issues. By using simple heuristic techniques to extract temporal information from web documents, we initially focus more on recall than on precision, relying on the subsequent application of a fuzzy temporal reasoner to improve the reliability of the extracted information, and to deal with conflicts that arise because of the vagueness of events. Experimental results indicate that a consistent and reliable knowledge base of fuzzy temporal relations can thus be obtained, which effectively allows us to target temporally constrained retrieval tasks.