Unsupervised relation extraction aims to extract the relationship between entities from
natural language sentences without prior information on relational scope or distribution …

We propose a novel knowledge-based technique for inter-document similarity computation,
called Context Semantic Analysis (CSA). Several specialized approaches built on top of …

In this paper, we propose to build a morpho-semantic knowledge graph from Arabic
vocalized corpora. Our work focuses on classical Arabic as it has not been deeply …

Unsupervised relation extraction (URE) extracts relations between named entities from raw
text without manually-labelled data and existing knowledge bases (KBs). URE methods can …

Knowledge Bases (KBs) find applications in many knowledge-intensive tasks and, most
notably, in information retrieval. Wikidata is one of the largest public general-purpose KBs …

We present an approach for ontology population from natural language English texts that
extracts RDF triples according to FrameBase, a Semantic Web ontology derived from …

The knowledge graph is constructed to acquire a large amount of structured knowledge that
can be read by computers. To effectively complete the knowledge graph, embedding …

As concepções dos Sistemas de Recuperação da Informação são retomadas para
contextualizar tanto os atuais mecanismos de busca, considerados Sistemas Digitais ou de …

Entity linking aims to link ambiguous mentions to their corresponding entities in a knowledge
base, which is significant and fundamental for various downstream applications, eg …

Situation awareness is a crucial cognitive skill that enables individuals to perceive,
comprehend, and project the current state of their environment accurately. It involves being …