Memory recall-driven multi-view semantic inference for offensive language detection

Key Points

• The analysis reveals a marked increase in detection accuracy for offensive language when using memory recall mechanisms and semantic inference.
• Accuracy improvements reached up to 25% in distinguishing offensive language across diverse text inputs and contexts.
• Multi-view analysis approaches were utilized to evaluate various perspectives, supporting robust language detection capabilities.
• This study highlights the potential for improved natural language processing techniques, emphasizing the benefits of memory-driven methodologies.