Knowledge fusion through academic articles: a survey of definitions, techniques, applications and challenges
- PDF / 1,204,593 Bytes
- 30 Pages / 439.37 x 666.142 pts Page_size
- 88 Downloads / 146 Views
Knowledge fusion through academic articles: a survey of definitions, techniques, applications and challenges Yu Zhang1 · Min Wang2 · Morteza Saberi3 · Elizabeth Chang1 Received: 26 May 2020 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract The ever growing volume of academic articles stresses the need for a new generation of knowledge management method to intelligently reuse the academic knowledge and facilitate the development of scientific research. Knowledge fusion (KF) serves a key element of such method addressing those needs, and breakthrough progress has taken place in the field of KF. This brings a great opportunity for the academic community to expedite the process of literature review and automatically retrieve the required knowledge from academic publications. Therefore, a survey reviewing the KF studies in terms of the related technologies and applications for valuable insights to reuse academic knowledge, which is missing from the state-of-the-art literature, is in need. Motivated to bridge this gap, this paper conducts a systematic survey reviewing the existing studies on KF, meanwhile discussing the opportunities and challenges of applying KF through academic articles. To this end, we revisit the definitions of knowledge and KF in the context of academic articles, and summarise the fusion patterns and their usage in existing applications. Furthermore, we review the techniques and applications of KF, especially those with academic articles as sources of knowledge. Finally, we discuss the challenges and future directions in order to bring new insights to researchers and practitioners to deepen their understanding of knowledge fusion and to develop versatile functions. Keywords Knowledge fusion · Knowledge retrieval · Knowledge management · Data mining · Information retrieval
* Yu Zhang [email protected] Min Wang [email protected] Morteza Saberi [email protected] Elizabeth Chang [email protected] 1
School of Business, UNSW Canberra, Canberra, Australia
2
School of Engineering and Information Technology, UNSW Canberra, Canberra, Australia
3
Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, Australia
13
Vol.:(0123456789)
Scientometrics
Introduction The rapidly growing volume of academic articles generates a huge amount of valuable knowledge for the world (Mudrak 2016). Such continuous knowledge accumulation leads to advanced scientific research and discovery, meanwhile, the enormous amount has brought about challenges for the users who leverage the published knowledge to deliver theoretical contributions or solve practical problems. In order to make greater use of the scientific knowledge and support researchers and practitioners with a deeper understanding of the existing research outcomes, effective and efficient knowledge management is needed to extract, convert and reuse knowledge from academic articles. Knowledge fusion (KF) which supports knowledge discovery, extraction, organisation and representation is developed to ta
Data Loading...
