• COMP620
Skip to end of metadata
Go to start of metadata

COMP620: Graduate Seminar in Distributed Computing - Big Data and Analytics Systems

Course Information (Spring 2015)

Instructor:

Prof. Faye Briggs, DH 2062

Graduate TA:Deepak Majeti, DH 2069

Lectures:

Keck 107

Lecture times:

Fri 11:00 am - 11:50 am


Lecture Slides and Notes

 Lecture NameDateSlidesNotes
1

Introduction to the course

1/17/2015PPT 
2

Course outline and student presentation assignment

1/23/2015PPT 
3

Big Data: Applications & Platform Architectures

1/30/2015PPT 
4

Big Data and Analytics Systems: Computer System Architecture

2/6/2015PPT 
5More Applications of Big Data4/24/2015  

Schedule for Student Presentations

Note: The slides and related material for each topic will be provided. Hence, do not hesitate about the workload if you like a topic not in your domain.

 
Topic
Student  Name
Date
Presentation
1

Distributed file systems and map-reduce as a tool for creating parallel algorithms that succeed on very large amounts of data

Yiting Xia

2/13/2015

PPT
2

Similarity search, including the key techniques of min-hashing and locality sensitive hashing

Deepak Majeti2/20/2015PDF
3

Data-stream processing and specialized algorithms for dealing with data that arrives so fast it must be processed immediately or lost

Wei-Cheng Xiao2/27/2015PPTX
4

Anomaly Detection Frequent-itemset mining, including association rules, market-baskets, the A-Priori Algorithm and its improvements

Deepak Majeti3/13/2015PPT
5Omid Pouya3/20/2015PPT1, PPT2
6

Algorithms for clustering very large, high-dimensional datasets

Simbarashe Dzinamarira3/27/2015 
7

Two key problems for Web applications: managing advertising and recommendation systems

Lei Tang4/10/2015 
8

Algorithms for analyzing and mining the structure of very large graphs, especially social-network graphs

Shangyu Luo 4/17/2015 
 

Techniques for obtaining the important properties of a large dataset by dimensionality reduction, including singular-value decomposition

and latent semantic indexing

Zhipeng Wang4/24/2015 
 

Machine-learning algorithms that can be applied to very large data, such as perceptrons, support-vector machines, and gradient descent

Zhipeng Wang4/30/2015 

Resources

Text Book:  Mining of Massive Datasets, Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman


Systems Architecture for Big Data and Analytics : A Big Data Architecture for Large Scale Security Monitoring, by Samuel Marchal, Xiuyan Jiang, Radu State, Thomas Engel

Databases & Tools : Hadoop & HDFS, Hive, SPARK, Map-Reduce Google Big Table & GoogleFS, Google Cluster Experiences with MapReduce

Programming Approaches to Big Data Analytics : OpenMP, MPI, etc

Analytics Algorithms and Applications :

GraphX : Unifying Table and Graph Analytics, Joseph Gonzalez

Analytics for all : Challenges in analytics applications

Machine Learning Review : Machine Learning Foundation, By Jason Brownlee

Modeling and Detection Techniques for Counter-Terror Social Network Analysis and Intent Recognition, by Clifford Weinstein, William Campbell, Brian Delaney, Gerald O’Leary

Visualization Tools :

Cell Phone Mini Challenge Award : Intuitive Social Network Graphs Visual Analytics of Cell Phone Data using MobiVis and OntoVis, by Carlos D. Correa Tarik Crnovrsanin Christopher Muelder Zeqian Shen Ryan Armstrong James Shearer Kwan-Liu Ma

 

 

 

 


  • No labels