Recent Approaches of Partitioning a Set into Overlapping Clusters, Distance Metrics and Evaluation Measures

Authors

  • Gursimran Pal Mata Gujri Khalsa College Kartarpur, Jalandhar, Punjab
  • Sahil Kakkar Guru Jambheshwar University, Hisar, Haryana, India

DOI:

https://doi.org/10.24297/ijrem.v10i0.8403

Keywords:

Partitioning Approache, Graph Theory, Co-Clustering, Distance Measures, Quality Measures, Dimensional Metric Space

Abstract

This paper reviews recently proposed overlapping co-clustering approaches and related evaluation measures. An overlap captures multiple views of the partitions in data set, hence is more expressive than traditional flat partitioning approaches. We present a graph-theoretic formulation of co-clustering which allows nodes to possess multiple memberships and hence finds usage in diverse applications like text mining, web mining, collaborative filtering and community detection. We also study proposed quality measures specifically adjusted to overlapping scenarios.particular subject.

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Author Biographies

Gursimran Pal, Mata Gujri Khalsa College Kartarpur, Jalandhar, Punjab

Mata Gujri Khalsa College Kartarpur (Jalandhar), Punjab, India

Sahil Kakkar, Guru Jambheshwar University, Hisar, Haryana, India

Department of Computer Science & Engineering, Guru Jambheshwar University, Hisar, Haryana, India

Published

2019-09-05

How to Cite

Pal, G., & Kakkar, S. (2019). Recent Approaches of Partitioning a Set into Overlapping Clusters, Distance Metrics and Evaluation Measures. INTERNATIONAL JOURNAL OF RESEARCH IN EDUCATION METHODOLOGY, 10, 3377-3383. https://doi.org/10.24297/ijrem.v10i0.8403

Issue

Section

Articles