Paper Info
Title
On the Road to Speed-Reading and Fast Learning with CONCEPTUM
Abstract
This work introduces CONCEPTUM, an advanced knowledge discovery system for speed-reading natural language texts and allowing faster and more effective learning. CONCEPTUM sports a huge plethora of features, ranging from language detection and conceptualization, up to semantic categorization, named entity recognition and automatic ontology building, effectively turning an unstructured textual source into concepts, topics, relationships and summaries to quickly and easily browse it and classify it. The system does not require any training or configuration and at present can be applied as-is on general-purpose English and Italian texts, providing disparate kinds of users with a powerful means to significantly speed up and improve their learning and research activities. In this work, a challenging experimentation on the Biochemistry field is reported to highlight and discuss the arising critical issues in the application of the system on a highly-technical domain.
Year
DOI
Venue
2016
10.1109/INCoS.2016.30
2016 International Conference on Intelligent Networking and Collaborative Systems (INCoS)
Keywords
Field
DocType
information extraction,knowledge discovery,literature mining,natural language processing,conceptualization,summarization,semantic categorization,language detection,named entity recognition,ontology building,semantic graph
Ontology (information science),Data science,Computer science,Conceptualization,Knowledge-based systems,Human–computer interaction,Natural language,Language identification,Knowledge extraction,Named-entity recognition,Semantics,Distributed computing
Conference
ISSN
ISBN
Citations 
2470-9166
978-1-5090-4125-1
4
PageRank 
References 
Authors
0.41
16
2
Name
Order
Citations
PageRank
Daniele Toti110513.86
Marco Rinelli260.79