Add to ORKGInternational audienceWe propose a hybrid method for the extraction and characterization of citations in scientic papers using machine learning combined with rule-based approaches. Our protocol consists of the extraction of metadata, bibliography parsing, section titles processing, and nd-grained semantic annotation on the sentece level of texts. This allows us to generate Linked Open Data from a set of research papers in XML
Motivation. Finding relevant scientific literature is one of the essential tasks researchers are fac...
Recent advancements in information retrieval systems significantly rely on the context-based feature...
International audienceThe Open Access movement in scientific publishing and search engines like Goog...
International audienceDuring the last decade, the availability of scientific papers in full text and...
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
Comunicació presentada al International Workshop on Semantic, Analytics, Visualization (SAVE-SD 2016...
This work deals with the Metadata Extraction from Scienti c Papers. There is generally described iss...
International audienceThe Open Access movement in scientific publishing and search engines like Goog...
In recent years we have seen the emergence of a variety of scholarly datasets. Typically these captu...
The continuous development of the Linked Data Web depends on the advancement of the underlying extra...
We describe methods for extracting interesting factual relations from scientific texts in computatio...
International audienceEach domain, along with its knowledge base, changes over time and every timefr...
With the currently growing interest in the Semantic Web, keywords/metadata extraction is coming to p...
Abstract—Each domain, along with its knowledge base, changes over time and every timeframe is center...
The contents and topologies of inter-document linkages, such as citations and references among scien...
Motivation. Finding relevant scientific literature is one of the essential tasks researchers are fac...
Recent advancements in information retrieval systems significantly rely on the context-based feature...
International audienceThe Open Access movement in scientific publishing and search engines like Goog...
International audienceDuring the last decade, the availability of scientific papers in full text and...
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
Comunicació presentada al International Workshop on Semantic, Analytics, Visualization (SAVE-SD 2016...
This work deals with the Metadata Extraction from Scienti c Papers. There is generally described iss...
International audienceThe Open Access movement in scientific publishing and search engines like Goog...
In recent years we have seen the emergence of a variety of scholarly datasets. Typically these captu...
The continuous development of the Linked Data Web depends on the advancement of the underlying extra...
We describe methods for extracting interesting factual relations from scientific texts in computatio...
International audienceEach domain, along with its knowledge base, changes over time and every timefr...
With the currently growing interest in the Semantic Web, keywords/metadata extraction is coming to p...
Abstract—Each domain, along with its knowledge base, changes over time and every timeframe is center...
The contents and topologies of inter-document linkages, such as citations and references among scien...
Motivation. Finding relevant scientific literature is one of the essential tasks researchers are fac...
Recent advancements in information retrieval systems significantly rely on the context-based feature...
International audienceThe Open Access movement in scientific publishing and search engines like Goog...