ACM: Article content miner for assessing the quality of scientific output

This paper presents the Article Content Miner (a.k.a. ACM), i.e., a method for processing the research papers in PDF format available for the 2016 edition of the Semantic Publishing Challenge in order to extract relevant semantic data and publish them in a RDF triplestore according to the Semantic Publishing And Referencing (SPAR) Ontologies (http://www.sparontologies.net). In particular, the extraction of all the information needed for addressing the queries of the second task of the challenge (https://github.com/ceurws/lod/wiki/SemPub16_Task2) is guaranteed by ACM by using techniques based on Natural Language Processing (i.e., Combinatory Categorial Grammar, Discourse Representation Theory, Linguistic Frames), Semantic Web technologies and good Ontology Design practices (i.e., Content Analysis, Ontology Design Patterns, Discourse Referent Extraction and Linking, Topic Extraction).

Publication type: 
Contributo in volume
Author or Creator: 
Nuzzolese, Andrea Giovanni
Peroni, Silvio
Reforgiato Recupero, Diego
Publisher: 
Springer-Verlag, Berlin, DEU
Source: 
Semantic Web Challenges, edited by Sack, Harald; Dietze, Stefan; Tordai, Anna; Lange, Christoph, pp. 281–292. Berlin: Springer-Verlag, 2016
Date: 
2016
Resource Identifier: 
http://www.cnr.it/prodotto/i/366565
https://dx.doi.org/10.1007/978-3-319-46565-4_22
info:doi:10.1007/978-3-319-46565-4_22
http://www.scopus.com/record/display.url?eid=2-s2.0-84992450924&origin=inward
Language: 
Eng
ISTC Author: 
Andrea Nuzzolese's picture
Real name: