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Date of Award
Restricted Project: Campus only access
Master of Science in Computer Science
School of Computer Science and Engineering
First Reader/Committee Chair
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.
Sherikar, Vishnu Vardhan Reddy, "I2MAPREDUCE: DATA MINING FOR BIG DATA" (2017). Electronic Theses, Projects, and Dissertations. 437.