Matches in SemOpenAlex for { <https://semopenalex.org/work/W2605432848> ?p ?o ?g. }
Showing items 1 to 79 of
79
with 100 items per page.
- W2605432848 endingPage "2038" @default.
- W2605432848 startingPage "2034" @default.
- W2605432848 abstract "The problem of hyper-local place ranking. Given a user location and query string (e.g., “Indian restaurant), hyper-local ranking provides a list of top-k points of interest influenced by previously logged directional queries (e.g., map direction searches from point A to point B).This paper proposes LARS*, a location-aware recommender system that uses their location-based ratings to show recommendations. Traditional recommender systems do not have spatial properties of users nor items; LARS*, next, supports a taxonomy of three novel classes of location-based ratings, namely, spatial ratings for non-spatial items, non-spatial ratings for spatial items, and spatial ratings for spatial items. LARS* exploits user rating locations through user partitioning, a technique that influences recommendations with ratings spatially close to querying users in a manner that maximizes system scalability while not sacrificing recommendation quality. LARS* exploits item locations using travel penalty, a technique that favors recommendation candidates closer in travel distance to querying users in a way that avoids exhaustive access to all spatial items. LARS* can apply these techniques separately, or together, depending on the type of location-based rating available. Experimental evidence using large-scale real-world data from both the Foursquare location-based social network and the Movie Lens movie recommendation system reveals that LARS* is efficient, scalable, and capable of producing recommendations twice as accurate compared to existing recommendation approaches. Our proposed location-aware recommender system, tackles a problem untouched by traditional recommender systems by dealing with three types of location-based ratings: spatial ratings for non-spatial items, non-spatial ratings for spatial items, and spatial ratings for spatial items. LARS* employs user partitioning and travel penalty techniques to support spatial ratings and spatial items, respectively." @default.
- W2605432848 created "2017-04-28" @default.
- W2605432848 creator A5013095594 @default.
- W2605432848 creator A5018297175 @default.
- W2605432848 creator A5065329038 @default.
- W2605432848 date "2017-01-01" @default.
- W2605432848 modified "2023-09-27" @default.
- W2605432848 title "LARS*: An Efficient and Scalable Location-Aware Recommender System" @default.
- W2605432848 hasPublicationYear "2017" @default.
- W2605432848 type Work @default.
- W2605432848 sameAs 2605432848 @default.
- W2605432848 citedByCount "0" @default.
- W2605432848 crossrefType "journal-article" @default.
- W2605432848 hasAuthorship W2605432848A5013095594 @default.
- W2605432848 hasAuthorship W2605432848A5018297175 @default.
- W2605432848 hasAuthorship W2605432848A5065329038 @default.
- W2605432848 hasConcept C124101348 @default.
- W2605432848 hasConcept C150140777 @default.
- W2605432848 hasConcept C154945302 @default.
- W2605432848 hasConcept C155292070 @default.
- W2605432848 hasConcept C165696696 @default.
- W2605432848 hasConcept C189430467 @default.
- W2605432848 hasConcept C23123220 @default.
- W2605432848 hasConcept C2524010 @default.
- W2605432848 hasConcept C28719098 @default.
- W2605432848 hasConcept C33923547 @default.
- W2605432848 hasConcept C38652104 @default.
- W2605432848 hasConcept C41008148 @default.
- W2605432848 hasConcept C48044578 @default.
- W2605432848 hasConcept C557471498 @default.
- W2605432848 hasConcept C76155785 @default.
- W2605432848 hasConcept C77088390 @default.
- W2605432848 hasConceptScore W2605432848C124101348 @default.
- W2605432848 hasConceptScore W2605432848C150140777 @default.
- W2605432848 hasConceptScore W2605432848C154945302 @default.
- W2605432848 hasConceptScore W2605432848C155292070 @default.
- W2605432848 hasConceptScore W2605432848C165696696 @default.
- W2605432848 hasConceptScore W2605432848C189430467 @default.
- W2605432848 hasConceptScore W2605432848C23123220 @default.
- W2605432848 hasConceptScore W2605432848C2524010 @default.
- W2605432848 hasConceptScore W2605432848C28719098 @default.
- W2605432848 hasConceptScore W2605432848C33923547 @default.
- W2605432848 hasConceptScore W2605432848C38652104 @default.
- W2605432848 hasConceptScore W2605432848C41008148 @default.
- W2605432848 hasConceptScore W2605432848C48044578 @default.
- W2605432848 hasConceptScore W2605432848C557471498 @default.
- W2605432848 hasConceptScore W2605432848C76155785 @default.
- W2605432848 hasConceptScore W2605432848C77088390 @default.
- W2605432848 hasIssue "2" @default.
- W2605432848 hasLocation W26054328481 @default.
- W2605432848 hasOpenAccess W2605432848 @default.
- W2605432848 hasPrimaryLocation W26054328481 @default.
- W2605432848 hasRelatedWork W1533286933 @default.
- W2605432848 hasRelatedWork W1990608327 @default.
- W2605432848 hasRelatedWork W2032611833 @default.
- W2605432848 hasRelatedWork W2054560962 @default.
- W2605432848 hasRelatedWork W2056472980 @default.
- W2605432848 hasRelatedWork W2083970309 @default.
- W2605432848 hasRelatedWork W2127474081 @default.
- W2605432848 hasRelatedWork W2134716712 @default.
- W2605432848 hasRelatedWork W2143666245 @default.
- W2605432848 hasRelatedWork W2153385788 @default.
- W2605432848 hasRelatedWork W2275478794 @default.
- W2605432848 hasRelatedWork W2518488075 @default.
- W2605432848 hasRelatedWork W2595589185 @default.
- W2605432848 hasRelatedWork W2597181650 @default.
- W2605432848 hasRelatedWork W2742932702 @default.
- W2605432848 hasRelatedWork W2890184170 @default.
- W2605432848 hasRelatedWork W3040386790 @default.
- W2605432848 hasRelatedWork W2234043815 @default.
- W2605432848 hasRelatedWork W2279511891 @default.
- W2605432848 hasRelatedWork W2524501412 @default.
- W2605432848 hasVolume "3" @default.
- W2605432848 isParatext "false" @default.
- W2605432848 isRetracted "false" @default.
- W2605432848 magId "2605432848" @default.
- W2605432848 workType "article" @default.