摘要
[目的/意义]研究基于深度学习的数字图书馆跨媒体语义检索方法。[方法/过程]分析深度学习的概念、深度结构以及深度学习的必备条件,研究深度学习与数字图书馆跨媒体语义检索的关系,指出基于深度结构的数字图书馆跨媒体相关性学习技术,构建基于深度学习的数字图书馆跨媒体语义检索框架。[结果/结论]深度学习与跨媒体语义检索的结合,作为数字图书馆全新的信息检索模式,可以解决跨媒体寻找语义信息和高效处理复杂维度数据的问题,大幅度提高数据检索、整合效率,必然会替代现有的信息检索工具,成为大数据时代提升知识服务水平的利剑。
[Purpose/significance ]The paper is to study cross-media semantic retrieval method of digital library based on deep learning. [Method/process ＂The paper analyzes the concept of deep learning, the depth structure and the prerequisites for deep learn-ing, studies the relationship between deep learning and digital library cross-media semantic retrieval, points out cross-media correla-tion learning technology of digital library based on depth structure, and builds a framework based on deep learning for digital library cross-media semantic retrieval. [Result/conclusion] As a new digital library information retrieval model, the combination of deep learning and cross-media semantic retrieval can solve the problems of retrieving semantic information across the media and efficiently process-ing complex dimensional data, greatly improve the efficiency of data retrieval and integration, certainly replace the existing information retrieval tools, and become a sword to enhance the level of knowledge service in the era of big data.
出处
《情报探索》
2018年第2期16-19,共4页
Information Research
关键词
深度学习
数字图书馆
跨媒体
语义检索
deep learning
digital library
cross-media
semantic retrieval
