Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Tenindra Abeywickrama"'
Publikováno v:
ACM SIGMOD Record. 51:51-58
The Kuhn-Munkres (KM) algorithm is a classical combinatorial optimization algorithm that is widely used for minimum cost bipartite matching in many real-world applications, such as transportation. For example, a ride-hailing service may use it to fin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f49d03ed028dfacd563fb97a3f5186c
https://doi.org/10.1145/3542700.3542713
https://doi.org/10.1145/3542700.3542713
Publikováno v:
2022 23rd IEEE International Conference on Mobile Data Management (MDM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f78bbb981747ab2450b48025b111a21
https://doi.org/10.1109/mdm55031.2022.00031
https://doi.org/10.1109/mdm55031.2022.00031
Publikováno v:
Proceedings of the VLDB Endowment. 14:1150-1158
The Kuhn-Munkres (KM) algorithm is a classical combinatorial optimization algorithm that is widely used for minimum cost bipartite matching in many real-world applications, such as transportation. For example, a ride-hailing service may use it to fin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::989679d56968b87d61c65a53b2b00e96
https://doi.org/10.14778/3450980.3450983
https://doi.org/10.14778/3450980.3450983
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling. 30:2-10
Location-based services rely heavily on efficient methods that search for relevant points-of-interest (POIs) close to a given location. A k nearest neighbors (kNN) query is one such example that finds k closest POIs from an agent's location. While mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e4ae2b2c2c6c70387a1af312bf7d732
https://doi.org/10.1609/icaps.v30i1.6639
https://doi.org/10.1609/icaps.v30i1.6639
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 32:983-997
A significant proportion of all search volume consists of local searches. As a result, search engines must be capable of finding relevant results combining both spatial proximity and textual relevance with high query throughput. We observe that exist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a301164fa2231b4203a92d95ba7d79f
https://doi.org/10.1109/tkde.2019.2894140
https://doi.org/10.1109/tkde.2019.2894140
Publikováno v:
IJCAI
A k nearest neighbors (kNN) query finds k closest points-of-interest (POIs) from an agent's location. In this paper, we study a natural extension of the kNN query for multiple agents, namely, the Aggregate k Nearest Neighbors (AkNN) query. An AkNN qu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a3c0bbbecf8e52d29c581ae393eff534
https://doi.org/10.24963/ijcai.2021/640
https://doi.org/10.24963/ijcai.2021/640
Publikováno v:
Proceedings of the International Symposium on Combinatorial Search. 9:184-185
In the age of smartphones, finding the nearest points of interest (POIs) is a highly relevant problem. A popular way to solve this is to use a k Nearest Neighbor (kNN) query to retrieve POIs by their road network distances from a query location. Howe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a297a0c16d40bfb7498d4b2df72df34
https://doi.org/10.1609/socs.v9i1.18443
https://doi.org/10.1609/socs.v9i1.18443
Publikováno v:
ICDE
Given the prevalence and volume of local search queries, today’s search engines are required to find results by both spatial proximity and textual relevance at high query throughput. Existing techniques to answer such spatial keyword queries employ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f4e062cf914338bd657536bdd75c13e
https://doi.org/10.1109/icde48307.2020.00237
https://doi.org/10.1109/icde48307.2020.00237
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783319556987
DASFAA (2)
DASFAA (2)
The k nearest neighbor (kNN) query on road networks finds the k closest points of interest (POIs) by network distance from a query point. A past study showed that a kNN technique using a simple Euclidean distance heuristic to generate candidate POIs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15ef60c66729642ea09c30f991fa515b
https://doi.org/10.1007/978-3-319-55699-4_26
https://doi.org/10.1007/978-3-319-55699-4_26
