Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis
This work addresses the challenge for law enforcement and forensic experts in analyzing digital communication for criminal activities like grooming and drug dealing, but it is incremental as it builds upon an existing method.
The paper tackles the problem of detecting relevant information in high-volume chat logs for grooming and drug dealing forensic analysis by proposing JointKPE++, a supervised keyphrase extraction method that builds upon JointKPE with improvements for longer texts. The results show significant improvements over traditional approaches, demonstrating its potential to aid forensic experts in efficiently detecting keyphrases related to criminal activities.
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.