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Chapitre D'ouvrage Année : 2018

Location Recommendation with Social Media Data

Résumé

Smartphones with inbuilt location-sensing technologies are now creating a new realm for recommender systems research and pratice. In this chapter, we focus on recommender systems that use location data to help users navigate the physical world. We examine various recommendation problems: recommending new places, recommending the next place to visit, events to attend, and recommending neighbourhoods or large areas to explore further. Lastly, we discuss how (personalized) place search is analogous to web search. For each of these domains, we present relevant data, algorithms, and methods, and we illustrate how researchers are investigating them with examples from the literature. We close by summarizing key aspects and suggesting future directions.
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Dates et versions

hal-01794923 , version 1 (18-05-2018)

Identifiants

Citer

Cécile Bothorel, Neal Lathia, Romain Picot-Clémente, Anastasios Noulas. Location Recommendation with Social Media Data. Social Information Access, Volume 10100, Springer, Cham, pp.624 - 653, 2018, Lecture Notes in Computer Science book series (LNCS), 978-3-319-90091-9. ⟨10.1007/978-3-319-90092-6_16⟩. ⟨hal-01794923⟩
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