Zobrazeno 1 - 10
of 610
pro vyhledávání: '"Kian Lee, Tan"'
Publikováno v:
Proceedings of the VLDB Endowment. 16:1249-1263
In this paper, we seek to perform a rigorous experimental study of main-memory hash joins in storage class memory (SCM). In particular, we perform a design space exploration in real SCM for two state-of-the-art join algorithms: partitioned hash join
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c78e25530578efc549f8c2d78decaa48
https://doi.org/10.14778/3583140.3583144
https://doi.org/10.14778/3583140.3583144
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 34:431-445
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::867de0ee0337448037149082cdb5d2bf
https://doi.org/10.1109/tpds.2022.3221821
https://doi.org/10.1109/tpds.2022.3221821
Publikováno v:
The VLDB Journal. 32:887-904
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0737f807588ee22e544674d49e4ec493
https://doi.org/10.1007/s00778-022-00777-7
https://doi.org/10.1007/s00778-022-00777-7
Towards One-Size-Fits-Many: Multi-Context Attention Network for Diversity of Entity Resolution Tasks
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:6018-6032
Entity resolution (ER) identifies data instances referring to the same real-world entity and has received enormous research attention. In this paper, we examine the task of ER from a broader perspective, with its input extended from textual records,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f094be036ba0ae84cd4955ace152562
https://doi.org/10.1109/tkde.2021.3060790
https://doi.org/10.1109/tkde.2021.3060790
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4690-4704
In this paper, we study a new variant of trajectory similarity search from the context of continuous query processing. Given a moving object from s to $d$ , following a reference route $T_r$ , we monitor the trajectory similarity between the referenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01fb075f3d01197a7853f04796a0e4b8
https://doi.org/10.1109/tkde.2020.3046670
https://doi.org/10.1109/tkde.2020.3046670
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:4231-4244
Subgraph enumeration is important for many applications such as network motif discovery, community detection, and frequent subgraph mining. To accelerate the execution, recent works utilize graphics processing units (GPUs) to parallelize subgraph enu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d77dbe365660154020d6af6d201505b
https://doi.org/10.1109/tkde.2020.3035564
https://doi.org/10.1109/tkde.2020.3035564
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:3714-3726
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::195e339b39e402fc2565a732e778ecd2
https://doi.org/10.1109/tkde.2020.3034611
https://doi.org/10.1109/tkde.2020.3034611
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:
IEEE Transactions on Knowledge and Data Engineering. 34:1501-1515
Entity resolution identifies all records in a database that refer to the same entity. In this paper, we propose an unsupervised framework for entity resolution using blocking and graph algorithms. The records are partitioned into blocks with no redun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18dd48f3bbf5db3ac19c4b77e75fb0f2
https://doi.org/10.1109/tkde.2020.2991063
https://doi.org/10.1109/tkde.2020.2991063