Ontology-Driven Extraction of Research Processes

Tracking #: 1668-2880

This paper is currently under review
Authors: 
Vayianos Pertsas
Panos Constantopoulos

Responsible editor: 
Andreas Hotho

Submission type: 
Full Paper
Abstract: 
Extracting information from a research article, associating it with information from other sources and deriving new knowledge constitute a challenging process that has not yet been fully addressed. Here we present Research Spotlight, a system that leverages existing information from DBpedia, retrieves articles from repositories, extracts and interrelates various kinds of named and non-named entities by exploiting article metadata, the structure of text as well as syntactic and semantic constraints, and populates a knowledge base in the form of RDF triples. An ontology specifically designed to represent research processes and practices is driving the whole process, the outcome adhering to linked data standards. The system is evaluated through two experiments that measure the overall accuracy in terms of token- and entity- based precision, recall and F1 scores, as well as entity boundary detection, with promising results. Error analysis provides useful insights into the capabilities and optimization possibilities of each module of the system.
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