TOXIN
发表于 2025-3-23 12:08:56
Introduction to Representation Learning,earning methods, which transform data instances into a vector space, is that similarities of the original data instances and their relations are expressed as distances and directions in the target vector space, allowing for similar instances to be grouped based on these properties.
endoscopy
发表于 2025-3-23 17:04:39
Book 2021rn data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, e
critic
发表于 2025-3-23 20:26:28
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progestogen
发表于 2025-3-23 23:21:11
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labyrinth
发表于 2025-3-24 06:25:29
Propositionalization of Relational Data, directly from relational data, developed in the Inductive Logic Programming research community, this chapter addresses the propositionalization approach of first transforming a relational database into a single-table representation, followed by a model or pattern construction step using a standard
审问,审讯
发表于 2025-3-24 07:04:55
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bronchiole
发表于 2025-3-24 12:43:14
Unified Representation Learning Approaches,ceted approach to symbolic or numeric feature construction, respectively. At the core of this similarity between different approaches is their common but . use of different similarity functions. In this chapter, we take a step forward by . using similarities between entities to construct the embeddi
ARCHE
发表于 2025-3-24 16:15:58
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single
发表于 2025-3-24 22:38:52
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畸形
发表于 2025-3-25 02:32:29
https://doi.org/10.1007/978-3-030-68817-2embeddings; data fusion; heterogeneous data mining; relational data mining; feature construction; proposi