【24h】

A Survey on Recommender System

机译:推荐系统的调查

获取原文
获取原文并翻译 | 示例
       

摘要

Recommender systems have gained its importance because of the availability of enormous online information. In current time, deep learning has gained appreciable attention in many researches such as natural language processing, artificial intelligence due to high performance and great learning feature representations. The effect of deep learning is also persistent, lately showing its usefulness when put to retrieval of information and recommenders work which eventually have resulted in the flourish of deep learning approaches in recommender system. Hybrid approaches for designing recommender models have been gaining popularity in recent years. The paper aims in giving a comprehensive insight of recent research works on recommender systems.
机译:由于巨大的在线信息,推荐系统已获得其重要性。 在当前的时间内,深入学习在许多研究中获得了可观的关注,例如自然语言处理,人工智能由于高性能和伟大的学习特征表示。 深度学习的影响也持续,最近展示了当检索信息和推荐工作时的有用性,这些工作最终导致了推荐系统中深入学习方法的蓬勃发展。 近年来,用于设计推荐模型的混合方法已经获得了受欢迎程度。 本文旨在为近期研究工作提供全面的思想思考。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号