中国科学院“十三五”信息化专项科学大数据工程项目——重点数据库建设申请指南

1 Introduction Problem Definition Existing Methods 2 Isotropic Hashing Model Learning Experiment 3 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 4 Conclusion 5 Reference

1 Introduction Problem Definition Existing Methods Motivation and Contribution 2 Isotropic Hashing Model Learning Experimental Results 3 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 4 Conclusion 5 Reference

电子科技大学：《大数据分析与挖掘 Big Data Analysis and Mining》课程教学资源（课件讲稿）Lecture 7 Hadoop-Spark

Key Node Identification Community Detection

 What is data stream?  What is Concept Drift?  Data stream classification  Data stream clustering

电子科技大学：《大数据分析与挖掘 Big Data Analysis and Mining》课程教学资源（课件讲稿）Lecture 4 Sampling for Big Data

Locality-Sensitive Hashing Find Similar Items CASE STUDY Finding Similar Documents Min-Hashing Locality-Sensitive Hashing Learn to Hash

电子科技大学：《大数据分析与挖掘 Big Data Analysis and Mining》课程教学资源（课件讲稿）Lecture 2 BasicConcepts（Foundations of Data Mining）

电子科技大学：《大数据分析与挖掘 Big Data Analysis and Mining》课程教学资源（课件讲稿）Lecture 1 Intro（主讲：邵俊明）