Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/516177
Title: | Enhanced Affinity Measures using Local Properties for Spectral Clustering |
Researcher: | Chintalapati, Lalith Srikanth |
Guide(s): | Sarma, Rachakonda Raghunatha |
Keywords: | Computer Science Computer Science Interdisciplinary Applications Engineering and Technology |
University: | Sri Sathya Sai Institute of Higher Learning |
Completed Date: | 2020 |
Abstract: | Our research work consists of contribution in terms of devising three novel newlinesimilarity metrics in three major areas viz., a) Topological Node Features (TNF) newlinebased similarity b) Conformal Prediction (CP) based similarity and c) Steering newlinekernel covariance matrix based similarity. In the thesis, one can also see the role of newlineneighborhood information in the construction of effective similarity metrics for newlineSpectral Clustering(SC) framework. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/516177 |
Appears in Departments: | Department of Mathematics and Computer Science |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 202.99 kB | Adobe PDF | View/Open |
abstract.pdf | 120.51 kB | Adobe PDF | View/Open | |
chapter 1.pdf | 1.3 MB | Adobe PDF | View/Open | |
chapter 2.pdf | 277.03 kB | Adobe PDF | View/Open | |
chapter 3.pdf | 1.73 MB | Adobe PDF | View/Open | |
chapter 4.pdf | 877.4 kB | Adobe PDF | View/Open | |
chapter 5.pdf | 571.15 kB | Adobe PDF | View/Open | |
chapter 6.pdf | 83.75 kB | Adobe PDF | View/Open | |
contents.pdf | 66.44 kB | Adobe PDF | View/Open | |
prelim.pdf | 1.9 MB | Adobe PDF | View/Open | |
title.pdf | 328.14 kB | Adobe PDF | View/Open |
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