Which Kobani? A Case Study on the Role of Spatial Statistics and Semantics for Coreference Resolution Across Gazetteers
Thursday Sep 29 03:30 PM to 05:30 PM (2 hours)
Marriott Chateau Champlain (Main event) - Viger A
Spatial statistics Geospatial semantics Gazetteers Coreferecen resolution Ontology
Identifying the same places across different gazetteers is a key prerequisite for spatial data con- flation and interlinkage. Conventional approaches mostly rely on combining spatial distance with string matching and structural similarity measures, while ignoring relations among places and the semantics of place types. In this work, we propose to use spatial statistics to mine semantic signatures for place types and use these signatures for coreference resolution, i.e., to determine whether records form different gazetteers refer to the same place. We introduce 27 statistical features for computing these signatures and apply them to the type and entity levels to determine the corresponding places between two gazetteers, namely GeoNames and DBpedia. The city of Kobani, Syria is used as a running example to demonstrate the feasibility of our approach. The experimental results show that the proposed signatures have the potential to improve the performance of coreference resolution.