iodides
发表于 2025-3-25 04:34:26
Surrounding Join Query Processing in Spatial Databasesneighbour (NN), namely . and .. In this paper, we propose a new join query which is called . join query. Given two point datasets . and . of multidimensional objects, the . query retrieves for each point in . its all surrounding points in .. As a new spatial join query, we propose algorithms that ar
消灭
发表于 2025-3-25 09:53:39
http://reply.papertrans.cn/27/2636/263526/263526_22.png
LARK
发表于 2025-3-25 11:55:14
http://reply.papertrans.cn/27/2636/263526/263526_23.png
STEER
发表于 2025-3-25 17:36:39
A Multi-way Semi-stream Join for a Near-Real-Time Data Warehousea warehousing. The requirements for semi-stream joins are fast, accurate processing and the ability to function well with limited memory. Currently, semi-stream algorithms presented in the literature such as MeshJoin, Semi-Stream Index Join and CacheJoin can join only one foreign key in the stream d
septicemia
发表于 2025-3-25 21:45:38
http://reply.papertrans.cn/27/2636/263526/263526_25.png
helper-T-cells
发表于 2025-3-26 00:57:37
Searching k-Nearest Neighbor Trajectories on Road Networks Previous work such as [., ., .] has been proposed to answer the search. Such work typically measures the distance between trajectories and queries by the distance between query points and GPS points of trajectories. Such measurement could be inaccurate because those GPS points generated by some sam
delta-waves
发表于 2025-3-26 07:06:16
http://reply.papertrans.cn/27/2636/263526/263526_27.png
minaret
发表于 2025-3-26 08:36:46
http://reply.papertrans.cn/27/2636/263526/263526_28.png
Hla461
发表于 2025-3-26 12:49:32
Provenance-Based Rumor Detectional place for spreading rumors. Although different types of information are available in a post on social media, traditional approaches in rumor detection leverage only the text of the post, which limits their accuracy in detection. In this paper, we propose a provenance-aware approach based on recur
繁忙
发表于 2025-3-26 20:32:56
An Embedded Feature Selection Framework for Hybrid Data irrelevant and redundant features. The majority of feature selection methods, which have been developed in the last decades, can deal with only numerical or categorical features. An exception is the Recursive Feature Elimination under the clinical kernel function which is an embedded feature select