Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Enhancing Keyphrase Extraction from Academic Articles Using Section Structure Information
LongKey: Keyphrase Extraction for Long Documents
Optimizing Keyphrase Ranking for Relevance and Diversity Using Submodular Function Optimization (SFO)
Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction
NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question Answering
Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study
토론
이 논문과 연결된 포럼 글이 아직 없습니다.