稀疏二进制数据压缩算法
binhash的Python项目详细描述
稀疏二进制数据的压缩技术
开发中
先决条件
- Python2.7或更高版本
- NumPy
- scikit learn
- 库：[Pickle]，[random]，[re]
用法
from BinHash import hasher
corpus = 'path_to_the_folder_containing_documents'
d = 10000
k = 500
myhasher = hasher(corpus, d, k)
sample_text = "this is a sample text"
sample_hash = myhasher.hash_text(sample_text)
引文
如果有助于你的研究，请在你的出版物中引用这些论文
@inproceedings{DBLP:conf/pakdd/PratapSK18,
author = {Rameshwar Pratap and
Ishan Sohony and
Raghav Kulkarni},
title = {Efficient Compression Technique for Sparse Sets},
booktitle = {Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia
Conference, {PAKDD} 2018, Melbourne, VIC, Australia, June 3-6, 2018,
Proceedings, Part {III}},
pages = {164--176},
year = {2018},
crossref = {DBLP:conf/pakdd/2018-3},
url = {https://doi.org/10.1007/978-3-319-93040-4\_14},
doi = {10.1007/978-3-319-93040-4\_14},
timestamp = {Tue, 19 Jun 2018 09:13:55 +0200},
biburl = {https://dblp.org/rec/bib/conf/pakdd/PratapSK18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{compression,
author = {Rameshwar Pratap and
Raghav Kulkarni and
Ishan Sohony},
title = {Efficient Dimensionality Reduction for Sparse Binary Data},
booktitle = {IEEE International Conference on BIG DATA, Accepted},
year = {2018}
}
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