人工智能-自然语言处理-命名实体

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命名实体

我们为您提供的命名实体服务，可以帮助您快速识别文本中的实体，进而挖掘各实体间的关系，是进行深度文本挖掘，知识库构建等常用自然语言处理领域里的必备工具。目前主要针对电商领域，识别品牌、产品、型号等，同时也包括一些通用领域实体如人名、地名、机构名、时间日期等。支持英语，泰语，越南语，印尼语。
如有私有化部署（本地部署软件）需求，及商务问题，请联系：nlp-support@list.alibaba-inc.com

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领域更丰富

依托阿里大生态，历经多个领域业务场景锤炼，覆盖电商、娱乐、新闻等多个领域

海量数据建模

基于百亿级别的数据反馈建立分析模型，提升模型的精度和适配性

标签更丰富

结合细分领域，构建细粒度标签，实体类别超过50个

灵活的更新机制

应对层出不穷的新品牌、新品类、新电影等，构建自动的专名识别机制，定期增量更新

适用场景

文本搜索

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舆情分析

挖掘用户评论的核心问题，跟踪产品口碑

知识库构建

根据实体之间、实体与关键词之间的关联，构建相关的知识库

文本搜索

帮助用户快速查找到期望检索的相关内容

舆情分析

挖掘用户评论的核心问题，跟踪产品口碑

知识库构建

根据实体之间、实体与关键词之间的关联，构建相关的知识库

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NLP自学习平台

支持文本实体抽取、文本分类等NLP定制化算法能力，用户无需拥有丰富的算法背景，仅需标注或上传适量文档数据，即可通过平台快速创建算法模型并使用。

了解更多

商品评价解析

基于电商行业的大量语料研发，对消费者历史评价和新增评价的商品维度属性自动解析，将文本转化为结构化属性字段，高效甄别正负面评价，同时根据情感强烈程度进行-1分~1分的打分，可统计可分析，大幅度节省客服人工。

了解更多

多语言分词

将连续的自然语言文本，切分成具有语义合理性和完整性的词汇序列，同时保持对数据、模型的不断迭代更新，目前支持简体中文、英文及泰文。

了解更多

情感分析

又称倾向性分析，或意见挖掘，它是对带有情感色彩的主观性文本进行分析、处理、归纳和推理的过程。利用情感分析能力，可以针对带有主观描述的自然语言文本，自动判断该文本的情感正负倾向并给出相应的结果。