GIR Experimentation

Geographic Information Retrieval (GIR) community has generally accepted the thesis that both thematic and geographic aspect of documents are useful for GIR. This paper describes a preliminary experiment exploring this thesis by seperately index-ing/searching geographical relevant-terms (place names, geo-spatial relations, geographic concepts and geographic adjacetives) extracted from reference document collection. Two indexes were created one for extracted geographic relevant-terms (i.e. document footprint) and one for reference document collections. Geo-Score and Thematic-Score against document collection footprint and reference document collection respectively were combined through a linear interpolation to obtained the final score for document relevance ranking. We used several freely available geographic resources – Wikipedia, World-Gazetteer, GEOnet Name Server (GNS), and WordNet. Apache Lucene was used as an indexing and search platform while Alias-I LingPipe was used to detect geographic named entities (GNEs), and other geo-relevant concepts and terms in documents. We submitted runs for monolingual English task, and our system achieved mean average precision (MAP) of 0.1690 to 0.2194. No significant improvement was observed through geographic query expansion.