Query Estimation Structures in Geo-Social Networks

MPhil Thesis Defence


Title: "Query Estimation Structures in Geo-Social Networks"

By

Mr. Christos KOUTRAS


Abstract

Over the past few years the amount of information being processed by data 
management systems has grown exponentially, due to various technological 
advancements. Thus, substantial work has been focused on constructing novel 
summarization structures that make it possible to handle large datasets with 
the compromise of estimation errors . Furthermore, the rapid spread of 
GPS-enabled mobile devices and social networking have recently led to the 
growth of Geo-Social Networks (GeoSNs). These have enabled novel location-based 
social interactions through GeoSN queries, which extract useful information 
combining both the social relationships and the current location of the users. 
In this work, we first present numerous summarization structures, focusing on 
the cases of Histograms and Sketches. We highlight the most popular such 
structures and clarify their applicability in estimating specific query types. 
In the second part of the thesis, we introduce the notion of approximately 
answering queries on GeoSN and propose novel hybrid structures that facilitate 
their size estimation. Finally, we examine and evaluate the accuracy and 
efficiency of our proposed structures by conducting an extensive set of 
experiments over real-world datasets.


Date:			Monday, 25 June 2018

Time:			10:00am - 12:00noon

Venue:			Room 5560
 			Lifts 27/28

Committee Members:	Prof. Dimitris Papadias (Supervisor)
 			Dr. Raymond Wong (Chairperson)
 			Dr. Ke Yi


**** ALL are Welcome ****