Paper Info
Title
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 in mean average precision (MAP) when compared to the traditional vector space model, even if Pseudo Relevance Feedback is employed.
Year
DOI
Venue
2010
10.1007/978-3-642-14770-8_11
IceTAL
Keywords
Field
DocType
geographic information retrieval,previous gir research,traditional ir engine,geographical query,novel representation,pertinent ranking,ranking problem,geographical ontology,geographical location,robust geographical resource,mean average precision,indexation,information retrieval,vector space model
Human–computer information retrieval,Relevance feedback,Query expansion,Ranking,Information retrieval,Geographic information retrieval,Ranking (information retrieval),Relevance (information retrieval),Vector space model,Mathematics
Conference
Volume
ISSN
ISBN
6233
0302-9743
3-642-14769-0
Citations 
PageRank 
References 
0
0.34
18
Authors
6
Name
Order
Citations
PageRank
Maya Carrillo1267.25
Esaú Villatoro-Tello2141.32
Aurelio López-López317530.86
Chris Eliasmith447567.16
Luis Villaseñor-Pineda540353.74
Manuel Montes-Y-Gómez663883.97