flink_sentiment_analysis_sdk
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情感倾向分析(Sentiment Classification)针对带有主观描述的文本,可自动判断该文本的情感极性类别并给出相应的置信度,能够帮助企业理解用户消费习惯、分析热点话题和危机舆情监控,为企业提供有利的决策支持。

SDK算法:

  • 情感倾向分为两类
  • Negative (消极)
  • Positive (积极)

环境准备

flink连接服务器端口,并从端口读取数据。我们使用最轻量的netcat来测试。
NC(netcat)被称为网络工具中的瑞士军刀,体积小巧,但功能强大。

1. Linux/Mac

nc -l 9000

2. Windows

nc -l -p 9000

运行例子 - SentenceEncoderExample

在nc命令行输入语句

...
CalvindeMacBook-Pro:~ calvin$ nc -l 9000
is alone downstairs...working
I feel bad for doing it
@RyanSeacrest is it just me, or she hates anoop. i mean seriously, she's kinda mean to him.

在IDE命令行可以看到对应的语句情感分类结果

[
	class: "Negative", probability: 0.98781
	class: "Positive", probability: 0.01218
]
[
	class: "Negative", probability: 0.99725
	class: "Positive", probability: 0.00274
]
[
	class: "Negative", probability: 0.99816
	class: "Positive", probability: 0.00183
]

SDK代码下载地址:

Github链接

Gitee链接

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