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']]