Qiyuan Gong (SII)

leetcode. Python & JAVA Solutions for Leetcode

How_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).

Deep_Learning_Exercise. Deep Learning Exercise and Notebook

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.

Clustering_based_K_Anon. cluster based generalization for k-anonymity

Mondrian_L_Diversity. Mondrian for L-diveristy. It's not available now.

Top_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.

image_classification_redis. Image Classification based on Analytics-Zoo and Redis

Google_APAC. My solution for Google APAC

Apriori_based_Anonymization. This repository is an python implement of Apriori_based_Anonymization for set-valued dataset anonymization.

SEU_Web_Login. This program is a python implement for CLI (command-line interface) web login in Southeast University (China).

Python_Blind_Image_Watermarking. A simple implement Blind_Image_watermark with Python.

analyzing_weibo_data_with_spark. try to analyzing weibo data with Spark

claw-fleet-manager. UI Mangement tool for openclaw fleet

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.

Zoo_Benchmark. Scala

Relational_Transaction_Anon. This repository is an python implement of Relation and Transaction Anonymization for Relational and Transaction dataset anonymization.

arx. ARX is a comprehensive open source data anonymization tool that has been designed from the ground up to provide high scalability and ease of use. It supports risk-based anonymization, methods for analyzing data quality and re-identification risks, as well as privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy

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.

NEC_based_Anonymization. EC based Anonymization. Improve efficiency without increasing information loss.

ChatGPT-Web. Vue

PAA. Partition and Anatomize Anonymization

Machine_Learning_in_Action. Machine_Learning_in_Action Python code

Partition_for_Transaction. This repository is an open source python implement for Partition_for_Transaction. I implement this algorithm in python for further study.