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Parallel Approach for Document Representation using Dictionary Learning

Publication Type : Conference Proceedings

Publisher : IEEE

Source : 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT)

Url : https://ieeexplore.ieee.org/abstract/document/8993114

Campus : Amritapuri

School : School of Computing

Center : AI (Artificial Intelligence) and Distributed Systems

Year : 2019

Abstract : There has been drastic advancements in data science both in terms of algorithm development and storage is concerned. This work takes into consideration an area which is coming of use in data handling based on sparse representation. The collection of documents which is considered as a dictionary is large with a massive amount of data providing in. So in order to represent an incoming document in sparse mode, we have considered parallelizing the algorithm for dictionary learning and sparse code generation. This work show good improvement in reducing the time for generating sparse representation with help of GPUs. There is a 2x increase in time when compared to CPU usage for generating the same sparse code for an input collection.

Cite this Research Publication : Menon, Remya, K. Harikrishnan, and Ganesh Varier. "Parallel Approach for Document Representation using Dictionary Learning." 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). Vol. 1. IEEE, 2019.

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