The International Conference on Personalization and Recommender Systems in E-Commerce (ICPRSEC - 27) features a diverse range of session tracks designed to cover key research areas, emerging trends and interdisciplinary innovations within the field of Data Analytics,E-commerce,Marketing.
These sessions provide a platform for researchers, academicians, industry professionals and practitioners to present their work, exchange ideas and explore the advancements shaping the future of the domain.
Each track is carefully curated to encourage knowledge sharing, collaboration and meaningful discussion, and is aligned with the United Nations Sustainable Development Goals.
Submit Your AbstractInternational Conference on Personalization and Recommender Systems in E-Commerce (ICPRSEC - 27) 设有多个分会主题,涵盖重要研究领域、前沿趋势与跨学科创新成果。
各分会主题为研究人员、学者、行业专家及实务工作者提供展示研究成果、交流学术思想、探讨领域发展的平台。
每个分会主题均经过精心设置,旨在促进知识共享、学术合作与深入研讨,并与联合国可持续发展目标(SDGs)保持一致。
提交摘要The session tracks of International Conference on Personalization and Recommender Systems in E-Commerce (ICPRSEC - 27) support the following United Nations Sustainable Development Goals through research, collaboration and knowledge exchange.
本次会议的分会主题通过科研、合作与知识交流,支持以下联合国可持续发展目标。
Browse every track scheduled for this conference.
浏览本次会议的全部分会主题。
This track focuses on the latest developments in recommendation algorithms, including collaborative filtering, content-based filtering, and hybrid models. Researchers are encouraged to present innovative approaches that enhance the accuracy and efficiency of personalization in e-commerce.
SDG 9
SDG 12
This session explores the intricacies of consumer preferences and behaviors in online shopping environments. Papers should delve into how these factors influence the effectiveness of personalization strategies and recommendation systems.
SDG 12
SDG 17
This track examines the role of data analytics in optimizing e-commerce platforms. Contributions should highlight how data-driven insights can enhance user experience and drive sales through effective personalization.
SDG 8
SDG 9
This session invites research on context-aware systems that adapt recommendations based on situational variables. Studies should illustrate how contextual factors can significantly improve user engagement and satisfaction.
SDG 10
SDG 12
This track investigates the application of behavioral targeting techniques in digital marketing strategies. Papers should discuss the implications of targeting based on user behavior for enhancing personalization and marketing effectiveness.
SDG 8
SDG 12
This session focuses on methodologies for effective user profiling in e-commerce settings. Contributions should explore how detailed user profiles can lead to more personalized and relevant recommendations.
SDG 9
SDG 12
This track addresses the critical need for robust evaluation metrics in assessing the performance of recommendation systems. Researchers are invited to propose new metrics or frameworks that can better capture the effectiveness of personalization efforts.
SDG 16
This session highlights recent innovations in collaborative filtering methods for recommendation systems. Papers should focus on novel algorithms that improve the scalability and accuracy of collaborative approaches.
SDG 9
SDG 12
This track explores the challenges and solutions associated with cross-domain recommendation systems. Contributions should discuss how insights from one domain can enhance personalization in another, fostering a more integrated e-commerce experience.
SDG 9
SDG 12
This session examines the ethical implications of data usage in personalization and recommendation systems. Papers should address privacy concerns, data security, and the balance between personalization and user autonomy.
SDG 10
SDG 16
This track invites forward-looking research on emerging trends and technologies in e-commerce personalization. Contributions should speculate on the future landscape of recommendation systems and their potential impact on consumer behavior.
SDG 9
SDG 12
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