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樓主: 萬能
41#
發(fā)表于 2025-3-28 17:00:34 | 只看該作者
Concurrent Reasoning with Inference Graphs, perform very well in forward, backward, bi-directional, and focused reasoning. Tests demonstrate the usefulness of our scheduling heuristics, and show significant speedup in both best case and worst case inference scenarios as the number of processors increases.
42#
發(fā)表于 2025-3-28 22:43:09 | 只看該作者
43#
發(fā)表于 2025-3-28 23:48:53 | 只看該作者
44#
發(fā)表于 2025-3-29 05:04:26 | 只看該作者
https://doi.org/10.1007/978-3-658-18992-1ommendation domain, where search queries include multiple sentences. We draw the comparison for search relevance improvement by pair-wise sentence generalization, phrase-level generalization, and generalizations of PTs as graphs.
45#
發(fā)表于 2025-3-29 07:26:09 | 只看該作者
46#
發(fā)表于 2025-3-29 14:10:51 | 只看該作者
47#
發(fā)表于 2025-3-29 17:13:00 | 只看該作者
Finding Maximal Common Sub-parse Thickets for Multi-sentence Search,ommendation domain, where search queries include multiple sentences. We draw the comparison for search relevance improvement by pair-wise sentence generalization, phrase-level generalization, and generalizations of PTs as graphs.
48#
發(fā)表于 2025-3-29 21:41:04 | 只看該作者
Learning Bayes Nets for Relational Data with Link Uncertainty,t the link structure. Our base line method learns a Bayes net from join tables directly. This is a statistically powerful procedure that finds many correlations, but does not scale well to larger datasets. We compare join table search with a hierarchical search strategy.
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