Recep Sinan Arslan profile image
Recep Sinan Arslan Assoc. Prof. Kayseri University
Publication 11 Review 0 CrossRef Cited 22 TR Dizin Cited 14
11 Publication
0 Review
22 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 1262

3

1

1262

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 460

0

1

460

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 460

1

460

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 677

0

677

0

1290

0

1823

0

4313

A Deep Learning Model for Malicious Url Filtering
DOI: 10.31590/ejosat.1011961
FAVORITE 1 TOTAL DOWNLOAD COUNT 1262

1

1262

A Detection Method for Malicious Web Pages using Doc2vec Model and Machine Learning
DOI: 10.31590/ejosat.981450
FAVORITE 0 TOTAL DOWNLOAD COUNT 1394

0

1394

0

797

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Publications

1

0

433

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 677

1

0

677

2

0

1290

3

0

1823

3

0

4313

A Deep Learning Model for Malicious Url Filtering
DOI: 10.31590/ejosat.1011961
CITED 3 FAVORITE 1 TOTAL DOWNLOAD COUNT 1262

3

1

1262

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 1394

7

0

1394

2

0

797