In the different areas of knowledge, textual data are important sources of information. This way, Information Extraction methods have been developed to identify and structure information present in textual documents. In ...

Models of word embeddings are often assessed when solving syntactic and semantic analogies. Among the latter, we are interested in relations that one would find in lexical-semantic knowledge bases like WordNet, also covered ...

The embedded systems are more and more present in daily life. It is present from toys to life support systems. The peculiar characteristics of the system where the software is embedded require care that are not covered by ...

Sequential recommendation aims to predict the user’s next action based on personal action sequences. The major challenge in this task is how to achieve high performance recommendation under the data sparsity problem. ...

Resources for Natural Language Processing (NLP) are less numerous for languages different from English. In the clinical domain, where these resources are vital for obtaining new knowledge about human health and diseases, ...

A teoria espectral em grafos considera propriedades dos grafos através da análise do espectro de matrizes relacionais, como a matriz de modularidade. No contexto de detecção de comunidades, algoritmos espectrais têm alcançado ...

Numerical vector representations are able to represent from words to meanings, in a low-dimensional continuous space. These representations are based on distributional modeling, where the context in which the word occurs ...

Anotações semânticas permitem associar a dados ou porções de dados não-estuturados (e.g., menções relevantes em textos) recursos com semântica bem definida em bases de conhecimento (e.g., DBpedia, Wordnet, Babelnet) que ...

This article explores how a subsidiary of a multi-national enterprise (MNE) in an emerging economy embeds with multiple knowledge sources, both in its corporate network (internal) and in the host country (external), to ...