SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter
abstract: Social media has become popular in the past decade. Facebook for example has 1.59 billion active users monthly. With such massive social networks generating lot of data, everyone is constantly looking for ways of leveraging the knowledge from social networks to make their systems more pers...
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2016
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Online Access: | http://hdl.handle.net/2286/R.I.40219 |
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ndltd-asu.edu-item-402192018-06-22T03:07:41Z SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter abstract: Social media has become popular in the past decade. Facebook for example has 1.59 billion active users monthly. With such massive social networks generating lot of data, everyone is constantly looking for ways of leveraging the knowledge from social networks to make their systems more personalized to their end users. And with rapid increase in the usage of mobile phones and wearables, social media data is being tied to spatial networks. This research document proposes an efficient technique that answers socially k-Nearest Neighbors with Spatial Range Filter. The proposed approach performs a joint search on both the social and spatial domains which radically improves the performance compared to straight forward solutions. The research document proposes a novel index that combines social and spatial indexes. In other words, graph data is stored in an organized manner to filter it based on spatial (region of interest) and social constraints (top-k closest vertices) at query time. That leads to pruning necessary paths during the social graph traversal procedure, and only returns the top-K social close venues. The research document then experimentally proves how the proposed approach outperforms existing baseline approaches by at least three times and also compare how each of our algorithms perform under various conditions on a real geo-social dataset extracted from Yelp. Dissertation/Thesis Pasumarthy, Nitin (Author) Sarwat, Mohamed (Advisor) Papotti, Paolo (Committee member) Sen, Arunabha (Committee member) Arizona State University (Publisher) Computer science Computer engineering database geosocial graph index knn shortest path eng 51 pages Masters Thesis Computer Science 2016 Masters Thesis http://hdl.handle.net/2286/R.I.40219 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2016 |
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English |
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Dissertation |
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Computer science Computer engineering database geosocial graph index knn shortest path |
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Computer science Computer engineering database geosocial graph index knn shortest path SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
description |
abstract: Social media has become popular in the past decade. Facebook for example has 1.59 billion active users monthly. With such massive social networks generating lot of data, everyone is constantly looking for ways of leveraging the knowledge from social networks to make their systems more personalized to their end users. And with rapid increase in the usage of mobile phones and wearables, social media data is being tied to spatial networks. This research document proposes an efficient technique that answers socially k-Nearest Neighbors with Spatial Range Filter. The proposed approach performs a joint search on both the social and spatial domains which radically improves the performance compared to straight forward solutions. The research document proposes a novel index that combines social and spatial indexes. In other words, graph data is stored in an organized manner to filter it based on spatial (region of interest) and social constraints (top-k closest vertices) at query time. That leads to pruning necessary paths during the social graph traversal procedure, and only returns the top-K social close venues. The research document then experimentally proves how the proposed approach outperforms existing baseline approaches by at least three times and also compare how each of our algorithms perform under various conditions on a real geo-social dataset extracted from Yelp. === Dissertation/Thesis === Masters Thesis Computer Science 2016 |
author2 |
Pasumarthy, Nitin (Author) |
author_facet |
Pasumarthy, Nitin (Author) |
title |
SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
title_short |
SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
title_full |
SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
title_fullStr |
SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
title_full_unstemmed |
SPSR Efficient Processing of Socially k-Nearest Neighbors with Spatial Range Filter |
title_sort |
spsr efficient processing of socially k-nearest neighbors with spatial range filter |
publishDate |
2016 |
url |
http://hdl.handle.net/2286/R.I.40219 |
_version_ |
1718701220139368448 |