Clustering Reporeapers Using Data Mining Techniques

Saranya K G; Keerthana G

Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India

Research Article

Clustering Reporeapers Using Data Mining Techniques

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@INPROCEEDINGS{10.4108/eai.7-12-2021.2314573,
    author={Saranya  K G and Keerthana  G},
    title={Clustering Reporeapers Using Data Mining Techniques},
    proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India},
    publisher={EAI},
    proceedings_a={ICCAP},
    year={2021},
    month={12},
    keywords={build k-means agglomerative clustering minibatch k-means elbow k-means},
    doi={10.4108/eai.7-12-2021.2314573}
}

Saranya K G
Keerthana G
Year: 2021
Clustering Reporeapers Using Data Mining Techniques
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314573

Saranya K G¹^,*, Keerthana G¹

1: PSG College of Technology

*Contact email: kgs.cse@psgtech.ac.in

Abstract

Artifact play a major role in software development. An artifact in software development is an actual by-product in which the works are documented and stored in a repository so it can be retrieved upon demand. Artifacts in software engineering involves specific development methods or processes. To make the software development outright, the collection of information is organized as artifact set. Build involves in converting source code into software artifact. The presence of build helps to provide tangible and observable results. Document clustering involves in organizing and managing texts in structured format. Document clustering provides feasible results increasing the accuracy and saves time when compared to manual text classification.

Keywords: build k-means agglomerative clustering minibatch k-means elbow k-means

Published: 2021-12-22
Publisher: EAI

: http://dx.doi.org/10.4108/eai.7-12-2021.2314573