Add to ORKGThis work explores and evaluates text and graph mining methods for open domain concept and relation discovery in scientific literature. First results indicate that several different approaches have to be combined to detect a sufficient amount of concepts and meaningful relationships in an open domain corpus
Nowadays there is a tremendous amount of unstructured data, often represented by texts, which is cre...
Knowledge graphs (KG) are large network of entities and relationships, tipically expressed as RDF tr...
Literature mining is the process of extracting and combining facts from scientific publications. In ...
Literature-Based Discovery (LBD) is a technique for generating novel hypotheses from scientific corp...
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
As science advances, the underlying literature grows rapidly providing valuable knowledge mines for ...
Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical litera...
In this paper, we present a preliminary approach that uses a set of NLP and Deep Learning methods fo...
The world is overflowing with text. This ever-growing resource has the ability to capture thoughts, ...
Natural language text, from messages on social media to articles in newspapers, constitutes a signif...
<div><h3>Background</h3><p>Web-based, free-text documents on science and technology have been increa...
Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical litera...
The problem of inferring novel knowledge from implicit facts by logically connecting independent fra...
International audienceDuring the last decade, the need for reliable and massive Knowledge Graphs (KG...
BACKGROUND: Web-based, free-text documents on science and technology have been increasing growing on...
Nowadays there is a tremendous amount of unstructured data, often represented by texts, which is cre...
Knowledge graphs (KG) are large network of entities and relationships, tipically expressed as RDF tr...
Literature mining is the process of extracting and combining facts from scientific publications. In ...
Literature-Based Discovery (LBD) is a technique for generating novel hypotheses from scientific corp...
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
As science advances, the underlying literature grows rapidly providing valuable knowledge mines for ...
Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical litera...
In this paper, we present a preliminary approach that uses a set of NLP and Deep Learning methods fo...
The world is overflowing with text. This ever-growing resource has the ability to capture thoughts, ...
Natural language text, from messages on social media to articles in newspapers, constitutes a signif...
<div><h3>Background</h3><p>Web-based, free-text documents on science and technology have been increa...
Objective Literature-based discovery (LBD) aims to identify “hidden knowledge” in the medical litera...
The problem of inferring novel knowledge from implicit facts by logically connecting independent fra...
International audienceDuring the last decade, the need for reliable and massive Knowledge Graphs (KG...
BACKGROUND: Web-based, free-text documents on science and technology have been increasing growing on...
Nowadays there is a tremendous amount of unstructured data, often represented by texts, which is cre...
Knowledge graphs (KG) are large network of entities and relationships, tipically expressed as RDF tr...
Literature mining is the process of extracting and combining facts from scientific publications. In ...