Cluster Insight: A Weighted Clustering Tool for Large Textual Data Exploration

Authors

Mohamed Nadif (ORCID: https://orcid.org/0000-0002-0007-3950)
Séverine Affeldt (ORCID: https://orcid.org/0000-0002-4107-0887)
Amine Ferdjaoui (ORCID: https://orcid.org/0009-0008-3284-030X)

Institutions

Université Paris Cité (FR)
Sorbonne Paris Cité (FR)
Capgemini (France) (FR)

Publication Details

Published: 2025-02-26
DOI: https://doi.org/10.1145/3701551.3704127
Primary Topic: Data Mining Algorithms and Applications
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Cluster Insight: A Weighted Clustering Tool for Large Textual Data Exploration

Mohamed Nadif, Séverine Affeldt, Amine Ferdjaoui

Feb 26, 2025

Data Mining Algorithms and Applications

article

Cluster Insight: A Weighted Clustering Tool for Large Textual Data Exploration

Mohamed Nadif, Séverine Affeldt, Amine Ferdjaoui

February 26, 2025article en

Abstract

No abstract available for this paper.

Université Paris Cité (FR), Sorbonne Paris Cité (FR), Capgemini (France) (FR)

Openalex Percentile: Top 100%

Data Mining Algorithms and Applications

DOI Source OpenAlex

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.

Cluster Insight: A Weighted Clustering Tool for Large Textual Data Exploration — Mohamed Nadif, Séverine Affeldt, et al. · (2025) | TGRS Research Map | TGRS