pysparnn 模块使用,相似句子召回
import pysparnn.cluster_index as ci
from sklearn.feature_extraction.text import TfidfVectorizer
data = [
    "hello world",
    "oh hello there",
    "Play it",
    "Play it again Sam",
]
tv = TfidfVectorizer()
tv.fit(data)
#特征向量
features_vec = tv.transform(data)
#建立搜索索引
cp = ci.MultiClusterIndex(features_vec,data)
#搜索带有索引的
search_data = [
    "oh there",
    "Play it again Frank"
]
search_feature_vec = tv.transform(search_data)
#k是返回的个数,k_clusters代表聚类的个数
print(cp.search(search_feature_vec,k = 1,k_clusters=2,return_distance=False))
[['oh hello there'], ['Play it again Sam']]
    多思考也是一种努力,做出正确的分析和选择,因为我们的时间和精力都有限,所以把时间花在更有价值的地方。

                
            
        
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