Titlebook: Knowledge Engineering and Knowledge Management; 21st International C Catherine Faron Zucker,Chiara Ghidini,Yannick Tous Conference proceedi

壁畫

CRATE

A Semantic Use Case Simulation Framework for Training Machine Learning Algorithmsng SHACL/RDF(S) and SPARQL CONSTRUCT queries. The main benefits of this approach are (1) portability to other domains, (2) applicability to various ML algorithms, and (3) mitigation of the cold-start problem or sparse data.

使成整體

An Empirical Evaluation of RDF Graph Partitioning Techniqueses. We evaluate the selected RDF graph partitioning techniques in terms of their partitioning time, partitioning imbalance (in sizes), and query run time performances achieved, based on real-world data sets and queries selected using the . benchmark generation framework.

擁擠前

Fuzzy Semantic Labeling of Semi-structured Numerical Datasetsng beforehand, and it avoids tedious and costly manual training to match values with .. We evaluate our approach against manually annotated datasets. The results show that the proposed approach classifies most of the types correctly for our test sets.

optic-nerve

https://doi.org/10.1007/978-3-030-03667-6artificial intelligence; data mining; data security; data stream; databases; description logic; Human-Comp

新字

978-3-030-03666-9Springer Nature Switzerland AG 2018

的染料

影響深遠(yuǎn)

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/543897.jpg

人充滿活力

10樓

MURKY

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