Recep Sinan Arslan profile image
Recep Sinan Arslan Assoc. Prof. Kayseri University
Publication 11 Review 0 CrossRef Cited 23 TR Dizin Cited 14
11 Publication
0 Review
23 CrossRef Cited
14 TR Dizin Cited

Research Fields

Information and Computing Sciences Natural Language Processing

Institution

Kayseri University

Popular Publications

A Deep Learning Model for Malicious Url Filtering
DOI: 10.31590/ejosat.1011961
CITED 3 FAVORITE 1 TOTAL DOWNLOAD COUNT 1336

3

1

1336

Crime Prediction with DistilBERT-based Feature Extraction and Machine Learning
Authors: Emel Çolakoğlu, Serhat Hızlısoy , Recep Sinan Arslan
DOI: 10.21605/cukurovaumfd.1606169
CITED 0 FAVORITE 1 TOTAL DOWNLOAD COUNT 583

0

1

583

Publications

Crime Prediction with DistilBERT-based Feature Extraction and Machine Learning
Authors: Emel Çolakoğlu, Serhat Hızlısoy , Recep Sinan Arslan
DOI: 10.21605/cukurovaumfd.1606169
FAVORITE 1 TOTAL DOWNLOAD COUNT 583

1

583

A Design of Crime Category Detection Framework using Stacking Ensemble Model
Authors: Recep Sinan Arslan , Burak Dülgeroğlu
DOI: 10.21605/cukurovaumfd.1410642
FAVORITE 0 TOTAL DOWNLOAD COUNT 836

0

836

0

1501

0

2024

0

4577

A Deep Learning Model for Malicious Url Filtering
DOI: 10.31590/ejosat.1011961
FAVORITE 1 TOTAL DOWNLOAD COUNT 1336

1

1336

A Detection Method for Malicious Web Pages using Doc2vec Model and Machine Learning
DOI: 10.31590/ejosat.981450
FAVORITE 0 TOTAL DOWNLOAD COUNT 1551

0

1551

0

955

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Publications

1

0

599

A Design of Crime Category Detection Framework using Stacking Ensemble Model
Authors: Recep Sinan Arslan , Burak Dülgeroğlu
DOI: 10.21605/cukurovaumfd.1410642
CITED 1 FAVORITE 0 TOTAL DOWNLOAD COUNT 836

1

0

836

2

0

1501

4

0

2024

3

0

4577

A Deep Learning Model for Malicious Url Filtering
DOI: 10.31590/ejosat.1011961
CITED 3 FAVORITE 1 TOTAL DOWNLOAD COUNT 1336

3

1

1336

A Detection Method for Malicious Web Pages using Doc2vec Model and Machine Learning
DOI: 10.31590/ejosat.981450
CITED 7 FAVORITE 0 TOTAL DOWNLOAD COUNT 1551

7

0

1551

2

0

955