Insights into relevant knowledge extraction techniques: a comprehensive review
Article
Article Title | Insights into relevant knowledge extraction techniques: a comprehensive review |
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ERA Journal ID | 18042 |
Article Category | Article |
Authors | Shahid, Abdul (Author), Afzal, Muhammad Tanvir (Author), Abdar, Moloud (Author), Basiri, Mohammad Ehsan (Author), Zhou, Xujuan (Author), Yen, Neil Y. (Author) and Chang, Jia‑Wei (Author) |
Journal Title | Journal of Supercomputing |
Journal Citation | 76 (3), pp. 1695-1733 |
Number of Pages | 39 |
Year | 2020 |
Place of Publication | New York, United States |
ISSN | 0920-8542 |
1573-0484 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s11227-019-03009-y |
Abstract | More than 50 million journal papers will have been published by the end of 2019 with 2 million more journal papers published every year. The number of conference papers is even higher, and millions of other types of scientific research are added to the knowledge base every year. Scientific databases such as Web of Science, Scopus, and PubMed index millions of scientific papers and Google Scholar indexes a huge amount of scientific knowledge across diverse domains. However, current systems provide long lists of results when users attempt to find relevant papers, leaving them with little choice other than manually skimming through the lists. This article surveys different techniques used to identify relevant research papers by knowledge-based organizations. We categorized current literature content as content, metadata, collaborative filtering, and citation based techniques and identified the strengths and limitation for each approach. Further, we evaluated the published techniques and research-based products used to identify relevant documents and identified the strengths and limitations of each approach. This research will greatly help to understand current state-of-the-art techniques internal workings for finding relevant papers, understand the relevant strengths and limitations, and explore previously proposed techniques targeting this area. |
Keywords | scientific big data; paper related repository; citation analysis; collaborative filtering; content analysis; metadata analysis |
ANZSRC Field of Research 2020 | 460999. Information systems not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Kohat University of Science and Technology, Pakistan |
Capital University of Science and Technology, Pakistan | |
University of Montreal, Canada | |
Shahrekord University, Iran | |
School of Management and Enterprise | |
University of Aizu, Japan | |
National Taichung University of Science and Technology, Taiwan | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q5680/insights-into-relevant-knowledge-extraction-techniques-a-comprehensive-review
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