Semantic Publishing Challenge - Assessing the Quality of Scientific Output by Information Extraction and Interlinking

TL;DR

This paper discusses the Semantic Publishing Challenge's efforts to enhance scholarly publishing by extracting and interlinking information from computer science proceedings using Linked Data, aiming to improve quality assessment and enable advanced services.

Contribution

It introduces improved information extraction techniques and interlinking methods for scholarly data, connecting datasets within the LOD Cloud to facilitate better quality assessment and services.

Findings

Enhanced information extraction accuracy

Successful interlinking with LOD Cloud datasets

Foundation for advanced scholarly services

Abstract

The Semantic Publishing Challenge series aims at investigating novel approaches for improving scholarly publishing using Linked Data technology. In 2014 we had bootstrapped this effort with a focus on extracting information from non-semantic publications - computer science workshop proceedings volumes and their papers - to assess their quality. The objective of this second edition was to improve information extraction but also to interlink the 2014 dataset with related ones in the LOD Cloud, thus paving the way for sophisticated end-user services.