binhash 0.2

Algorithm to compress sparse binary data

Compression Techniques for sparse binary data

Prerequisites

• Python 2.7 or higher
• NumPy
• scikit learn
• Libraries: [Pickle], [random], [re]

Usage

''' 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) '''

Please cite these papers in your publications if it helps your research ''' @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} } '''