Titlebook: Advances in Artificial Intelligence -- IBERAMIA 2012; 13th Ibero-American Juan Pavón,Néstor D. Duque-Méndez,Rubén Fuentes-Fe Conference pr

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Adrenal-Glands

https://doi.org/10.1007/978-3-030-82602-4tion bottleneck. In this paper, we attempt to alleviate this problem by proposing an iterative unsupervised approach to identifying and extracting ontological class instances from the Web. The proposed approach considers the Web as a big corpus and relies on a confidence-weighted metric based on sem

Lacunar-Stroke

Peace Work, Traumas & The Here and Now,s, minimum density or distance threshold) in advance to work properly. In this paper, we eliminate the necessity of setting the minimum cluster size parameter of the Randomized Gravitational Clustering algorithm proposed by Gomez et al. Basically, the minimum cluster size is estimated using a heuris