耕种
发表于 2025-3-23 13:02:21
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machination
发表于 2025-3-23 14:37:04
Power of Bosom Friends, POI Recommendation by Learning Preference of Close Friends and Similar Userssearches on social networks, such as POI (point of interest) recommendation, usually ignore the social tie strength between users. If we can further consider the closeness between friends in the analysis, it is possible to improve the results. Therefore, in this paper, we focus on analyzing the soci
irreparable
发表于 2025-3-23 18:52:16
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Diluge
发表于 2025-3-24 01:17:03
Large Scale Indexing and Searching Deep Convolutional Neural Network Featuresp Convolutional Neural Network Features to support efficient retrieval on very large image databases. The idea is to provide a text encoding for these features enabling the use of a text retrieval engine to perform image similarity search. In this way, we built . a robust retrieval system that combi
未成熟
发表于 2025-3-24 02:29:37
Conference proceedings 2016zed in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology..
我不重要
发表于 2025-3-24 09:02:14
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Inscrutable
发表于 2025-3-24 13:14:35
Corpus-Based Study of Translation Practice,terns using branch-and-bound pruning. During the search, candidate best-covering patterns are concurrently collected for each positive transaction. Formal discussions and experimental results exhibit that ExCover efficiently finds a more compact set of patterns in comparison with previous methods.
特别容易碎
发表于 2025-3-24 14:55:56
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Irritate
发表于 2025-3-24 19:09:12
https://doi.org/10.1007/978-3-8350-9231-0rocess. The developed RUP algorithm can recursively discover recent HUPs; the computational cost and memory usage can be greatly reduced without candidate generation. Several pruning strategies are also designed to speed up the computation and reduce the search space for mining the required information.
ANT
发表于 2025-3-24 23:56:36
https://doi.org/10.1007/978-3-8350-9231-0lgorithm on probabilistic sequential pattern mining is used for finding user trajectories. A series of experiments are performed to evaluate each step of the framework. The experiment results reveal that each step of our framework is with high accuracy.