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leetcode
Python & JAVA Solutions for LeetcodeHow_to_Search_and_Read_a_Paper
本文档适合于刚入学的硕士和博士(计算机专业最好,其他专业可参考)。Mondrian
Python Implementation for Mondrian Multidimensional K-Anonymity (Mondrian).Basic_Mondrian
The raw mondrian is designed for numerical attributes. When comes to categorical attributes, Mondrian needs to transform categorical attributes to numerical ones. This transformations is not good for some applications. In 2006, LeFevre proposed basic Mondrian, which support both categorical and numerical attributes. This repository is an implementation for basic Mondrian.Deep_Learning_Exercise
Deep Learning Exercise and NotebookClustering_based_K_Anon
cluster based generalization for k-anonymityMondrian_L_Diversity
Mondrian for L-diveristy. It's not available now.image_classification_redis
Image Classification based on Analytics-Zoo and RedisTop_Down_Greedy_Anonymization
Top_Down_Greedy_Anonymization is a Top-down greedy algorithm data anonymization algorithm for relational dataset, proposed by Jian Xu in his papers.Google_APAC
My solution for Google APACPython_Blind_Image_Watermarking
A simple implement Blind_Image_watermark with Python.analyzing_weibo_data_with_spark
try to analyzing weibo data with SparkSEU_Web_Login
This program is a python implement for CLI (command-line interface) web login in Southeast University (China).Zoo_Benchmark
Relational_Transaction_Anon
This repository is an python implement of Relation and Transaction Anonymization for Relational and Transaction dataset anonymization.Semi_Partition
Semi_Partition is a Top-down greedy algorithm data anonymization algorithm for relational dataset. It's more efficient than Mondrian, which is proposed by Kristen LeFevre in his papers.PAA
Partition and Anatomize AnonymizationPartition_for_Transaction
This repository is an open source python implement for Partition_for_Transaction. I implement this algorithm in python for further study.ChatGPT-Web
NEC_based_Anonymization
EC based Anonymization. Improve efficiency without increasing information loss.1M_Generalization
1M_Generalization is a simple anonymization algorithm for 1:M dataset. It contains two sub-algorithms: Mondrian (for relational part) and Partition (transaction part). Both of them are straight forward, and can be repalced by more powerful algorithm with limtied modification.Love Open Source and this site? Check out how you can help us