Enhancing Bibliometric Insights: A Novel Overlapping Clustering Framework for Citation Networks

The primary contribution of this work is the Assembling Overlapping Clusters (AOC) framework, which extends Iterative K-core Clustering (IKC) to produce overlapping clusters for citation networks. AOC retains the original km-valid cores while adding overlapping non-core members, and it does not alter the core-periphery organization of the underlying IKC clusters. AOC creates node-to-cluster memberships by reassigning candidate nodes to additional clusters under either a core-connectivity rule (AOC m) or a relaxed k-link rule (AOC k). This enables the representation of publications with cross-domain relevance without modifying the km-valid cores. AOC operates in a single pass, is order-independent, and preserves the structural integrity of the original IKC output. Applied to a curated extracellular vesicle citation network, AOC increases marker-node coverage and reveals inter-cluster connectivity that is invisible under disjoint clustering.

Authors

Institutions

Publication Details

Journal
International Journal of Intelligent Systems and Data Science
Published
2026-10-31
DOI
https://doi.org/10.67231/jksh5987
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Bibliometric Insights: A Novel Overlapping Clustering Framework for Citation Networks

Akhil Veluru
International Journal of Intelligent Systems and Data Science
Complex Network Analysis Techniques
article

Enhancing Bibliometric Insights: A Novel Overlapping Clustering Framework for Citation Networks

Akhil Veluru
article en

Abstract

The primary contribution of this work is the Assembling Overlapping Clusters (AOC) framework, which extends Iterative K-core Clustering (IKC) to produce overlapping clusters for citation networks. AOC retains the original km-valid cores while adding overlapping non-core members, and it does not alter the core-periphery organization of the underlying IKC clusters. AOC creates node-to-cluster memberships by reassigning candidate nodes to additional clusters under either a core-connectivity rule (AOC m) or a relaxed k-link rule (AOC k). This enables the representation of publications with cross-domain relevance without modifying the km-valid cores. AOC operates in a single pass, is order-independent, and preserves the structural integrity of the original IKC output. Applied to a curated extracellular vesicle citation network, AOC increases marker-node coverage and reveals inter-cluster connectivity that is invisible under disjoint clustering.

International Journal of Intelligent Systems and Data ScienceVol. 1(6)
The University of Texas at Dallas (US)
Openalex Percentile: Top 13%
Complex Network Analysis Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Enhancing Bibliometric Insights: A Novel Overlapping Clustering Framework for Citation Networks — Akhil Veluru · International Journal of Intelligent Systems and Data Science (2026) | TGRS Research Map | TGRS