I2MAPREDUCE: DATA MINING FOR BIG DATA

<p>This project is an extension of i²MapReduce: Incremental MapReduce for Mining Evolving Big Data . i²MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), Generalized Iterated Matrix-Vector Multiplication(GIM-V), Single Source Shortest Path(SSSP). The main purpose of this project is to reduce input/output overhead, to avoid incurring the cost of re-computation and avoid stale data mining results. Finally, the performance of i²MapReduce is analyzed by comparing the resultant graphs.</p>

Name thesis:degree_name

Master of Science in Computer Science

Level thesis:degree_level

Restricted Project: Campus only access

Discipline thesis:degree_discipline

School of Computer Science and Engineering

Year dc:date.available

2017

Author dc:creator

• Sherikar, Vishnu Vardhan Reddy

Contributors dc:contributor

• Owen, Murphy

• Mapreduce
• Other Computer Sciences

Repository record dc:identifier

https://scholarworks.lib.csusb.edu/etd/437

OAI identifier oai:identifier

oai:scholarworks.lib.csusb.edu:etd-1497