判断两个文本之间的语义相似性。
语法
AI_AI_SIMILARITY([<resource_name>], <text_1>, <text_2>)
参数
|
参数 |
说明 |
|
|
指定的资源名称 |
|
|
文本 |
|
|
文本 |
返回值
-
返回一个 0 - 10 之间的浮点数。0 表示无相似性,10 表示强相似性;数值越高,则说明相似性越高。
-
当输入有值为 NULL 时返回 NULL。
-
结果为大模型生成,所以返回内容并不固定。
示例
假设我有如下表,代表某家快递公司收到的评论:
CREATE TABLE user_comments (
id INT,
comment VARCHAR(500)
) DUPLICATE KEY(id)
DISTRIBUTED BY HASH(id) BUCKETS 10
PROPERTIES (
"replication_num" = "1"
);
当我想按顾客语气情绪对评论进行排行时可以:
SELECT comment,
AI_SIMILARITY('resource_name', 'I am extremely dissatisfied with their service.', comment) AS score
FROM user_comments ORDER BY score DESC LIMIT 5;
查询结果大致如下:
+-------------------------------------------------+-------+
| comment | score |
+-------------------------------------------------+-------+
| It arrived broken and I am really disappointed. | 7.5 |
| Delivery was very slow and frustrating. | 6.5 |
| Not bad, but the packaging could be better. | 3.5 |
| It is fine, nothing special to mention. | 3 |
| Absolutely fantastic, highly recommend it. | 1 |
+-------------------------------------------------+-------+