{"title":"Data mining model for scientific research classification: the case of digital workplace accessibility","authors":"Radka Nacheva, Maciej Czaplewski, Pavel Petrov","doi":"10.1007/s40622-024-00378-z","DOIUrl":null,"url":null,"abstract":"<p>Research classification is an important aspect of conducting research projects because it allows researchers to efficiently identify papers that are in line with the latest research in each field and relevant to projects. There are different approaches to the classification of research papers, such as subject-based, methodology-based, text-based, and machine learning-based. Each approach has its advantages and disadvantages, and the choice of classification method depends on the specific research question and available data. The classification of scientific literature helps to better organize and structure the vast amount of information and knowledge generated in scientific research. It enables researchers and other interested parties to access relevant information in a fast and efficient manner. Classification methods allow easier and more accurate extraction of scientific knowledge to be used as a basis for scientific research in each subject area. In this regard, this paper aims to propose a research classification model using data mining methods and techniques. To test the model, we selected scientific articles on digital workplace accessibility for the disabled retrieved from Scopus and Web of Science repositories. We believe that the classification model is universal and can be applied in other scientific fields.</p>","PeriodicalId":43923,"journal":{"name":"Decision","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40622-024-00378-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
Research classification is an important aspect of conducting research projects because it allows researchers to efficiently identify papers that are in line with the latest research in each field and relevant to projects. There are different approaches to the classification of research papers, such as subject-based, methodology-based, text-based, and machine learning-based. Each approach has its advantages and disadvantages, and the choice of classification method depends on the specific research question and available data. The classification of scientific literature helps to better organize and structure the vast amount of information and knowledge generated in scientific research. It enables researchers and other interested parties to access relevant information in a fast and efficient manner. Classification methods allow easier and more accurate extraction of scientific knowledge to be used as a basis for scientific research in each subject area. In this regard, this paper aims to propose a research classification model using data mining methods and techniques. To test the model, we selected scientific articles on digital workplace accessibility for the disabled retrieved from Scopus and Web of Science repositories. We believe that the classification model is universal and can be applied in other scientific fields.
研究分类是开展研究项目的一个重要方面,因为它可以让研究人员高效地识别符合各领域最新研究并与项目相关的论文。研究论文分类有不同的方法,如基于主题的分类、基于方法的分类、基于文本的分类和基于机器学习的分类。每种方法都有其优缺点,选择哪种分类方法取决于具体的研究问题和可用数据。科学文献分类有助于更好地组织和结构化科学研究中产生的大量信息和知识。它使研究人员和其他相关人员能够快速有效地获取相关信息。分类方法可以更容易、更准确地提取科学知识,作为各学科领域科学研究的基础。为此,本文旨在利用数据挖掘方法和技术提出一个科研分类模型。为了测试该模型,我们选择了从 Scopus 和 Web of Science 资源库中检索到的有关残疾人数字工作场所无障碍环境的科学文章。我们相信,该分类模型具有通用性,可应用于其他科学领域。
期刊介绍:
The aim of the Journal, Decision, is to publish qualitative, quantitative, survey-based, simulation-based research articles at the national and sub-national levels. While there is no stated regional focus of the journal, we are more interested in examining if and how individuals, firms and governments in emerging economies may make decisions differently. Published for the management scholars, business executives and managers, the Journal aims to advance the management research by publishing empirically and theoretically grounded articles in management decision making process. The Editors aim to provide an efficient and high-quality review process to the authors.
The Journal accepts submissions in several formats such as original research papers, case studies, review articles and book reviews (book reviews are only by invitation).
The Journal welcomes research-based, original and insightful articles on organizational, individual, socio-economic-political, environmental decision making with relevance to theory and practice of business. It also focusses on the managerial decision-making challenges in private, public, private-public partnership and non-profit organizations. The Journal also encourages case studies that provide a rich description of the business or societal contexts in managerial decision-making process including areas – but not limited to – conflict over natural resources, product innovation and copyright laws, legislative or policy change, socio-technical embedding of financial markets, particularly in developing economy, an ethnographic understanding of relations at a workplace, or social network in marketing management, etc.
Research topics covered in the Journal include (but not limited to):
Finance and Accounting
Organizational Theory and Behavior
Decision Science
Public Policy-Economic Insights
Operation Management
Innovation and Entrepreneurship
Information Technology and Systems Management
Optimization and Modelling
Supply Chain Management
Data Analytics
Marketing Management
Human Resource Management