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The growing use of digital communication platforms has given rise to variouscriminal activities, such as grooming and drug dealing, which pose significantchallenges to law enforcement and forensic experts. This paper presents asupervised keyphrase extraction approach to detect relevant information inhigh-volume chat logs involving grooming and drug dealing for forensicanalysis. The proposed method, JointKPE++, builds upon the JointKPE keyphraseextractor by employing improvements to handle longer texts effectively. Weevaluate JointKPE++ using BERT-based pre-trained models on grooming and drugdealing datasets, including BERT, RoBERTa, SpanBERT, and BERTimbau. The resultsshow significant improvements over traditional approaches and demonstrate thepotential for JointKPE++ to aid forensic experts in efficiently detectingkeyphrases related to criminal activities.

Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis