摘要
旨在理清图书情报领域机器学习的研究现状,为未来机器学习在图书情报领域的深入开展提供实践探索和理论研究方面的参考。文章从机器学习的相关概念、图书情报领域内机器学习的研究热点主题以及机器学习在图书情报领域发展面临的机遇与挑战三个方面展开论述。研究表明,当前图书情报领域机器学习的研究热点主题主要集中在个性化推荐服务、智能信息检索和自动文本分类三个方面,图书情报领域机器学习的发展迎来了政策及战略红利,新信息技术迅猛发展和新算法效应所带来的发展机遇,也面临着摩尔定律及香农定理接近尾声的理论障碍和数据资源不够开放及专业型、全面型人才匮乏的实践障碍的挑战。
To clarify the current research situation of machine learning in the field of library and information and provide theoretical research material and practical exploration reference for the future development of digital reading field, the paper discusses the related concepts of machine learning,the research hotspots of machine learning in the field,and the opportunities and challenges faced by machine learning in the field. The results show the current research hotspots of machine learning in the field of library and information mainly focus on three aspects: personalized recommendation service,intelligent information retrieval and automatic text classification. Machine learning ushered in policy and strategic dividend,the rapid development of new information technology and new algorithm effect brought about by the development opportunities. In addition,it faces the theoretical barriers,such as the theory of Moore' s law and Shannon' s theorem is close to the end. It also faces the challenge of practical obstacles,such as lack of open data resources and professional and comprehensive talents.
出处
《图书馆学研究》
CSSCI
北大核心
2018年第1期47-52,共6页
Research on Library Science
基金
国家自然科学基金资助项目"差错文化
归因倾向和差错报告:作用机制和情景因素研究"(项目编号:71273109)成果之一
关键词
机器学习
深度学习
增强学习
machine learning
deep learning
reinforcement learning