Adult Content Detection in Search Engine Queries

Levent Soykan, Cihan Karsak, Ilknur Durgar El-Kahlout
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Abstract

It is important to detect adult content in search engine queries in order to filter adult sites depending on the safe internet choices of the user. In this study, we investigate adult content classification in search engine entries for Turkish. Firstly, we collected and labeled data, and then we carried out classification experiments with both machine learning and deep learning methods. As a result of the experiments, we observed that deep learning methods performs better than machine learning methods. We obtained the best accuracy scores with the transformer based Electra model with 0.94 F1 score.
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搜索引擎查询中的成人内容检测
在搜索引擎查询中检测成人内容是很重要的,以便根据用户的安全互联网选择过滤成人网站。在这项研究中,我们调查成人内容分类在搜索引擎条目土耳其。我们首先对数据进行收集和标注,然后用机器学习和深度学习两种方法进行分类实验。通过实验,我们观察到深度学习方法比机器学习方法表现得更好。基于变压器的Electra模型获得了最好的精度分数,F1得分为0.94。
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