Scholarlink

With the evergrowing need for digitalization and the increasing importance of tourism, we present Trailblazer, an innovative Destination Management System (DMS) that leverages advanced machine learning techniques, such as auto-tagging, sentiment analysis, and predictive analytics, to provide real-time data insights for the tourism industry. By integrating a modular microservices architecture, Trailblazer addresses the challenges of data fragmentation and delayed insights, thereby enabling destination managers to make informed, timely decisions. The system demonstrates enhanced data aggregation, user engagement, and operational efficiency through rigorous testing and evaluation.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Trailblazer: A Machine Learning Augmented Destination Management System

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Daniel Ferreira,
  • Hugo Correia,
  • Duarte Cruz,
  • Joaquim Rosa,
  • André Oliveira,
  • Alexandre Cotorobai,
  • Bernardo Figueiredo,
  • Osvaldo Pacheco

摘要

With the evergrowing need for digitalization and the increasing importance of tourism, we present Trailblazer, an innovative Destination Management System (DMS) that leverages advanced machine learning techniques, such as auto-tagging, sentiment analysis, and predictive analytics, to provide real-time data insights for the tourism industry. By integrating a modular microservices architecture, Trailblazer addresses the challenges of data fragmentation and delayed insights, thereby enabling destination managers to make informed, timely decisions. The system demonstrates enhanced data aggregation, user engagement, and operational efficiency through rigorous testing and evaluation.