StarSpace:学习嵌入以进行分类,检索和排名-源码

上传者: 42162171 | 上传时间: 2021-02-27 22:03:42 | 文件大小: 420KB | 文件类型: ZIP
C++
星际空间 StarSpace是一种通用的神经模型,用于有效学习实体嵌入以解决各种问题: 学习单词,句子或文档级别的嵌入。 信息检索:对实体/文档或对象集的排名,例如对Web文档的排名。 文本分类或任何其他标记任务。 度量/相似度学习,例如学习句子或文档相似度。 基于内容或基于协作过滤的推荐,例如推荐音乐或视频。 嵌入图,例如多关系图,例如Freebase。 图像分类,排名或检索(例如,通过使用现有的ResNet功能)。 在一般情况下,它学会将不同类型的对象表示为一个通用的矢量嵌入空间,因此,名称中的星形('*',通配符)和空间会相互比较。 在给定查询实体/文档或对象的情况下,它学习对一组实体/文档或对象进行排名,该查询不一定与该集中的项目具有相同的类型。 有关其工作原理的更多详细信息,请参见。 消息 StarSpace在Python中可用:请查看“部分以获取详细信息。

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