Enhancements in Meta-Analytical Approaches for Deep Learning-Powered Conversational Agents

EasyChair Preprint no. 12027

Abstract

This paper explores recent advancements in meta-analysis techniques applied to deep learningbased chatbots. Meta-analysis methodologies are increasingly being utilized to synthesize findings across multiple studies, providing insights into the effectiveness and performance of various chatbot models. By systematically aggregating and analyzing data from diverse sources, researchers can identify trends, strengths, and limitations of existing approaches, ultimately guiding the development of more robust and efficient conversational agents. This paper reviews key methodologies, discusses their applications in the context of deep learning-based chatbots, and outlines future directions for research in this rapidly evolving field.

Keyphrases: Chatbots, conversational agents, deep learning, meta-analysis, performance evaluation, synthesis

@Booklet{EasyChair:12027,
  author = {Asad Ali},
  title = {Enhancements in Meta-Analytical Approaches for Deep Learning-Powered Conversational Agents},
  howpublished = {EasyChair Preprint no. 12027},

  year = {EasyChair, 2024}}