Titlebook: Knowledge Engineering and Knowledge Management; 22nd International C C. Maria Keet,Michel Dumontier Conference proceedings 2020 Springer Na

兇猛

modish

Entity-Based Short Text Classification Using Convolutional Neural Networksforms, etc. Due to many difficulties underlying short text for automated processing, i.e, sparsity and insufficient context, the traditional text classification approaches cannot easily be applied to short text. This study discusses a Convolutional Neural Network (CNN) based approach for short text

Ringworm

: Unveiling Topics and Citations Dependencies for Scientific Literature Exploration and Recommendatiirely capture the most salient efforts related to their own research. In this paper, we propose a novel knowledge model for unveiling meaningful and labeled relations among articles based on both topics and latent citation dependencies. An experimentation on the whole literature in the Computer Scie

atopic

Mining Latent Features of Knowledge Graphs for Predicting Missing Relationsted under the Open World Assumption. The problem of KG completeness aims at identifying missing values. While some approaches focus on predicting relations between pairs of known nodes in a graph, other solutions have studied the problem of predicting missing entity properties or relations even in t

隱士

nettle

Perceptron Connectives in Knowledge Representationween statistical learning of models from data and logical reasoning over knowledge bases. We prove that such connectives can be added to the language of most forms of Description Logic without increasing the complexity of the corresponding inference problem. We show, with a practical example over th

critique

On the Formal Representation and Annotation of Cellular Genealogiesn individual cell. The domain of these cellular dynamics is quite complex, and thus, demands a conceptual and computational architecture to support the integration of knowledge obtained across experiments and theories. In previous work, we have addressed the conceptual level and developed an axiomat

信條

啜泣

Projection

A Knowledge Graph Enhanced Learner Model to Predict Outcomes to Questions in the Medical Fieldir learning path, the . national French project aims to extend an existing platform with intelligent learning services. This platform contains a large number of annotated learning resources, from training and evaluation questions to students’ learning traces, available as an RDF knowledge graph. In