  The growing use of digital communication platforms has given rise to various
criminal activities, such as grooming and drug dealing, which pose significant
challenges to law enforcement and forensic experts. This paper presents a
supervised keyphrase extraction approach to detect relevant information in
high-volume chat logs involving grooming and drug dealing for forensic
analysis. The proposed method, JointKPE++, builds upon the JointKPE keyphrase
extractor by employing improvements to handle longer texts effectively. We
evaluate JointKPE++ using BERT-based pre-trained models on grooming and drug
dealing datasets, including BERT, RoBERTa, SpanBERT, and BERTimbau. The results
show significant improvements over traditional approaches and demonstrate the
potential for JointKPE++ to aid forensic experts in efficiently detecting
keyphrases related to criminal activities.
