Matches in SemOpenAlex for { <https://semopenalex.org/work/W4290943511> ?p ?o ?g. }
Showing items 1 to 86 of
86
with 100 items per page.
- W4290943511 abstract "Service time is a part of time cost in the last-mile delivery, which is the time spent on delivering parcels at a certain location. Predicting the service time is fundamental for many downstream logistics applications, e.g., route planning with time windows, courier workload balancing and delivery time prediction. Nevertheless, it is non-trivial given the complex delivery circumstances, location heterogeneity, and skewed observations in space. The existing solution trains a supervised model based on aggregated features extracted from parcels to deliver, which cannot handle above challenges well. In this paper, we propose MetaSTP, a meta-learning based neural network model to predict the service time. MetaSTP treats the service time prediction at each location as a learning task, leverages a Transformer-based representation layer to encode the complex delivery circumstances, and devises a model-based meta-learning method enhanced by location prior knowledge to reserve the uniqueness of each location and handle the imbalanced distribution issue. Experiments show MetaSTP outperforms baselines by at least 9.5% and 7.6% on two real-world datasets. Finally, an intelligent waybill assignment system based on MetaSTP is deployed and used internally in JD Logistics." @default.
- W4290943511 created "2022-08-13" @default.
- W4290943511 creator A5006117974 @default.
- W4290943511 creator A5012026072 @default.
- W4290943511 creator A5019034106 @default.
- W4290943511 creator A5039820086 @default.
- W4290943511 creator A5044478333 @default.
- W4290943511 creator A5044528555 @default.
- W4290943511 creator A5056217038 @default.
- W4290943511 creator A5060363706 @default.
- W4290943511 creator A5072813755 @default.
- W4290943511 date "2022-08-14" @default.
- W4290943511 modified "2023-10-16" @default.
- W4290943511 title "Service Time Prediction for Delivery Tasks via Spatial Meta-Learning" @default.
- W4290943511 cites W2085429457 @default.
- W4290943511 cites W2809128166 @default.
- W4290943511 cites W2904628589 @default.
- W4290943511 cites W2973092067 @default.
- W4290943511 cites W3014778557 @default.
- W4290943511 cites W3080707569 @default.
- W4290943511 cites W3080956811 @default.
- W4290943511 cites W3109908389 @default.
- W4290943511 cites W3168146412 @default.
- W4290943511 cites W3170553237 @default.
- W4290943511 cites W3175962266 @default.
- W4290943511 cites W3213113370 @default.
- W4290943511 cites W4220859026 @default.
- W4290943511 doi "https://doi.org/10.1145/3534678.3539027" @default.
- W4290943511 hasPublicationYear "2022" @default.
- W4290943511 type Work @default.
- W4290943511 citedByCount "3" @default.
- W4290943511 countsByYear W42909435112023 @default.
- W4290943511 crossrefType "proceedings-article" @default.
- W4290943511 hasAuthorship W4290943511A5006117974 @default.
- W4290943511 hasAuthorship W4290943511A5012026072 @default.
- W4290943511 hasAuthorship W4290943511A5019034106 @default.
- W4290943511 hasAuthorship W4290943511A5039820086 @default.
- W4290943511 hasAuthorship W4290943511A5044478333 @default.
- W4290943511 hasAuthorship W4290943511A5044528555 @default.
- W4290943511 hasAuthorship W4290943511A5056217038 @default.
- W4290943511 hasAuthorship W4290943511A5060363706 @default.
- W4290943511 hasAuthorship W4290943511A5072813755 @default.
- W4290943511 hasConcept C111919701 @default.
- W4290943511 hasConcept C119857082 @default.
- W4290943511 hasConcept C124101348 @default.
- W4290943511 hasConcept C136264566 @default.
- W4290943511 hasConcept C154945302 @default.
- W4290943511 hasConcept C162324750 @default.
- W4290943511 hasConcept C190839683 @default.
- W4290943511 hasConcept C205649164 @default.
- W4290943511 hasConcept C2778476105 @default.
- W4290943511 hasConcept C2780378061 @default.
- W4290943511 hasConcept C41008148 @default.
- W4290943511 hasConcept C58640448 @default.
- W4290943511 hasConcept C79403827 @default.
- W4290943511 hasConceptScore W4290943511C111919701 @default.
- W4290943511 hasConceptScore W4290943511C119857082 @default.
- W4290943511 hasConceptScore W4290943511C124101348 @default.
- W4290943511 hasConceptScore W4290943511C136264566 @default.
- W4290943511 hasConceptScore W4290943511C154945302 @default.
- W4290943511 hasConceptScore W4290943511C162324750 @default.
- W4290943511 hasConceptScore W4290943511C190839683 @default.
- W4290943511 hasConceptScore W4290943511C205649164 @default.
- W4290943511 hasConceptScore W4290943511C2778476105 @default.
- W4290943511 hasConceptScore W4290943511C2780378061 @default.
- W4290943511 hasConceptScore W4290943511C41008148 @default.
- W4290943511 hasConceptScore W4290943511C58640448 @default.
- W4290943511 hasConceptScore W4290943511C79403827 @default.
- W4290943511 hasFunder F4320321001 @default.
- W4290943511 hasFunder F4320335777 @default.
- W4290943511 hasLocation W42909435111 @default.
- W4290943511 hasOpenAccess W4290943511 @default.
- W4290943511 hasPrimaryLocation W42909435111 @default.
- W4290943511 hasRelatedWork W2039836583 @default.
- W4290943511 hasRelatedWork W2314755979 @default.
- W4290943511 hasRelatedWork W2329086085 @default.
- W4290943511 hasRelatedWork W2390710122 @default.
- W4290943511 hasRelatedWork W2392884863 @default.
- W4290943511 hasRelatedWork W2929716001 @default.
- W4290943511 hasRelatedWork W2961085424 @default.
- W4290943511 hasRelatedWork W4306674287 @default.
- W4290943511 hasRelatedWork W638424813 @default.
- W4290943511 hasRelatedWork W4224009465 @default.
- W4290943511 isParatext "false" @default.
- W4290943511 isRetracted "false" @default.
- W4290943511 workType "article" @default.