Multi-lingual Geographical Information Retrieval

This paper reports on the results of our experiments in the Monolingual English, German and Portuguese tasks and the Bilingual German topics on English collections, English topics on German collections and English topics on Portuguese collections tasks. Seven runs were submitted as ocial runs, four for the monolingual task and three for the bilingual task. We used the Terrier (TERabyte RetrIEveR) Information Retrieval Platform version 2.1 to index and query the collections. Experiments were performed for both tasks using the Inverse Document Frequency model with Laplace after-eect and normalization 2. Topics were processed automatically and the only elds considered were the title and the description. We included the title eld only for an experiment with the Portuguese collection. The stopword list provided by Terrier was used to index all the collections. Results for both the monolingual and bilingual tasks were low in terms of precision and recall mainly due to the following reasons: 1) no manual processing was done; 2) no query expansion based on automated relevance feedback was added; 3) no experiments including the narrative eld were run; 4) no terms were translated for the bilingual task; 5) no German and Portuguese stopword lists were used instead of the default stopword list; and 6) no pre-processing or removal of diacritic marks was performed. We are running new experiments to address some of the issues aforementioned and determine the impact they have on retrieval performance