Concept Based Representations for Ranking in Geographic Information Retrieval

Abstract. Geographic Information Retrieval (GIR) is a specialized Information Retrieval (IR) branch that deals with information related to geographical locations. Traditional IR engines are perfectly able to retrieve the majority of the relevant documents for most geographical queries, but they have severe difficulties generating a pertinent ranking of the retrieved results, which leads to poor performance. A key reason for this ranking problem has been a lack of information. Therefore, previous GIR research has tried to fill this gap using robust geographical resources (i.e. a geographical ontology), while other research with the same aim has used relevant feedback techniques instead. This paper explores the use of Bag of Concepts (BoC; a representation where documents are considered as the union of the meanings of its terms) and Holographic Reduced Representation (HRR; a novel representation for textual structure) as re-ranking mechanisms for GIR. Our results reveal an improvement i...

• Type: Journal
• Year: 2010
• Where: TAL
• Authors: Maya Carrillo, Esaú Villatoro-Tello, Aurelio López-López, Chris Eliasmith, Luis Villaseñor Pineda, Manuel Montes-y-Gómez
• Keywords: Geographic Information Retrieval, Holographic Reduced Representation, Natural Language Processing, Robust Geographical Resources, TAL 2010