Link Prediction with Deep Learning Models

منو

" Link Prediction with Deep Learning Models "
Aksakal, Ahmet Salih Al Faruque, Mohammad

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1106461
Doc. No	:	TLpq2394984047
Main Entry	:	Aksakal, Ahmet Salih
	:	Al Faruque, Mohammad
Title & Author	:	Link Prediction with Deep Learning Models\ Aksakal, Ahmet SalihAl Faruque, Mohammad
College	:	University of California, Irvine
Date	:	2019
student score	:	2019
Degree	:	M.S.
Page No	:	50
Abstract	:	Deep Learning has been used extensively in many applications by researchers. With the increased attraction to Deep Learning, more and more unique models are created each year. However, sometimes some of the model details are not included in the publications. This makes using new Deep Learning models for research a time-consuming task for researchers. In order to tackle with this problem, we propose a prediction mechanism for the missing information in the model. By creating a dataset where the Deep Learning models are represented as knowledge graphs, we made it possible to use knowledge graph embedding algorithms which are specifically designed for eliminating missing information in a given data. We inspected 6 different algorithms and compared their performances on a small-scale experiment. After the comparison, we picked the most promising algorithm and used it for link prediction in Deep Learning models.
Subject	:	Artificial intelligence
	:	Computer engineering
	:	Computer science