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Open Access
Article
Publication date: 7 June 2018

Zhang Yanjie and Sun Hongbo

For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure. However, how to find the…

Abstract

Purpose

For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure. However, how to find the useful rules or knowledge hidden in the data is very important and challengeable. Rule extraction methods are very useful in mining the important and heuristic knowledge hidden in the original high-dimensional data. It can help us to construct predictive models with few attributes of the data so as to provide valuable model interpretability and less training times.

Design/methodology/approach

In this paper, a novel rule extraction method with the application of biclustering algorithm is proposed.

Findings

To choose the most significant biclusters from the huge number of detected biclusters, a specially modified information entropy calculation method is also provided. It will be shown that all of the important knowledge is in practice hidden in these biclusters.

Originality/value

The novelty of the new method lies in the detected biclusters can be conveniently translated into if-then rules. It provides an intuitively explainable and comprehensive approach to extract rules from high-dimensional data while keeping high classification accuracy.

Details

International Journal of Crowd Science, vol. 2 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 17 October 2024

Priyanka, Shikha N. Khera and Pradeep Kumar Suri

This study aims towards developing a conceptual framework by systematically reviewing the available literature with reference to job crafting under the lens of an emerging economy…

Abstract

Purpose

This study aims towards developing a conceptual framework by systematically reviewing the available literature with reference to job crafting under the lens of an emerging economy from South Asia, i.e. India, which is the largest country and the largest economy in the South Asian region.

Design/methodology/approach

The study employs a hybrid methodology of a systematic literature review (SLR) and bibliometric analysis using VOSviewer and Biblioshiny. Bibliometric analysis provides glimpses into the current state of knowledge like-trend of publication, influential authors, collaboration with foreign authors, the major themes and studied topics on job crafting in India etc. Further, a detailed SLR of the selected articles led to the development of the conceptual framework consisting of the enablers and outcomes of job crafting.

Findings

It discusses implications for academia, business and society at large, and also provides valuable insights to policymakers and practitioners paving the way for better adoption, customization and implementation of job crafting initiatives.

Originality/value

Owing to its own unique social, cultural, and economic characteristics, the dynamics of job crafting in India may vary from other countries and regions which can also be reflective of how job crafting operates in South Asia in general. As job crafting was conceptualized and later evolved mostly in the western context, our study assumes greater significance as it is the first study which attempts to systematically review the job crafting literature to understand how job crafting manifests in the Indian context and presents a conceptual framework for the same.

Details

Business Analyst Journal, vol. 45 no. 2
Type: Research Article
ISSN: 0973-211X

Keywords

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