DISCLAIMER: This is a work-in-progress post CSO Classifier The CSO Classifier is a novel application that takes as input the text from abstract, title, and keywords of a research paper and outputs a list of relevant concepts from CSO. It consists of two main components: (i) the syntactic module and (ii) the semantic module. […]
Analysing the relationship between academia and industry allows us to understand how the knowledge produced by the universities is being adopted and enriched by the industrial sector, and ultimately affects society through the release of relevant products and services. In this paper, we present a preliminary approach to assess and compare the research outputs of academia and industry. This solution integrates data from several knowledge graphs describing scientific articles (Microsoft Academics Graph), research topics (Computer Science Ontology), organizations (Global Research Identifier Database), and types of industry (DBpedia). We focus on the Semantic Web as exemplary field and report several insights regarding the different behaviours of academia and industry, and the types of industries most active in this field.
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environment. In this paper, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive ontology of research areas in the field of Computer Science. The CSO Classifier takes as input the metadata associated with a research paper (title, abstract, keywords) and returns a selection of research concepts drawn from the ontology. The approach was evaluated on a gold standard of manually annotated articles yielding a significant improvement over alternative methods.
Simple answer: no. However, before getting into a more detailed answer, allow me to briefly introduce the concept of citation networks, then I will describe why citation networks cannot be considered acyclic anymore. In the scholarly domain, citation networks is an information network in which each node represents a scientific paper and a link between […]