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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Nursing Clinical Information System (NCIS)
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From Big Scholarly Data to Solution-Oriented Knowledge Repository.

Yu Zhang1, Min Wang2, Morteza Saberi3

  • 1School of Business, University of New South Wales, Canberra, ACT, Australia.

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|March 11, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework to extract research problems and solutions from scientific articles, creating knowledge repositories for better problem-solving recommendations. The system effectively supports scholarly research by identifying and recommending solutions for complex problems.

Keywords:
bibliometricsbig scholarly dataknowledge repositoryrecommender systemtext mining

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Area of Science:

  • Computer Science
  • Information Science

Background:

  • The rapid growth of scientific literature necessitates advanced methods for extracting actionable knowledge.
  • Current scholarly recommendation systems struggle to retrieve and utilize problem-solving information embedded within research articles.

Purpose of the Study:

  • To propose a novel framework for building solution-oriented knowledge repositories.
  • To develop a system that recommends solutions for specific research problems based on extracted information.

Main Methods:

  • A three-module framework: semantic information extraction, knowledge assessment using bibliometric graphs and ranking algorithms, and knowledge repository generation.
  • Implementation of a prototype scholarly solution support system.
  • A case study in the field of intrusion detection.

Main Results:

  • The proposed framework effectively mines research problems and solutions from academic papers.
  • The knowledge assessment module accurately ranks and evaluates information.
  • The system successfully generates solution-oriented knowledge maps with relevant recommendations.

Conclusions:

  • The developed framework and system are effective and efficient for creating solution-oriented knowledge repositories.
  • This approach enhances scholarly support by providing targeted problem-solving recommendations.
  • The method shows significant promise for advancing scientific discovery and innovation.