Recommending needles in a haystack: the SURGE approach

Hermoso, Ramon (Universidad de Zaragoza) ; Ilarri, Sergio (Universidad de Zaragoza) ; Trillo-Lado, Raquel (Universidad de Zaragoza) ; Marzo, Cristina

Resumen: Collective Spatial Keyword Querying (CoSKQ) was proposed over a decade ago as a model to retrieve sets of objects in spatial databases given a specific query. The rationale behind is that the retrieved solution sets must cover query keywords as well as minimise the geographic distances between the query and the solution elements. However, in most real scenarios, the exact matching of query keywords and object descriptions is rare or not possible. In this paper, we extend the notion of CoSKQ for recommendation problems and present SURGE (Spatial User Recommendations using Geographical metrics and sEmantics), an approach that puts forward a recommender system able to return solution sets even when query keywords and object descriptions do not match exactly. In order to do that, semantic techniques are used. A tourism domain has been used throughout the paper to explain the model. Furthermore, an exhaustive set of experiments has been carried out to validate the approach.

Idioma: Inglés

DOI: 10.1080/13658816.2025.2582692

Año: 2025

Publicado en: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2025), 1-38
ISSN: 1365-8816

Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2020-113037RB-I00
Financiación: info:eu-repo/grantAgreement/ES/DGA/T64-23R

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)