Improved link prediction for location based social networks with novel features and contextual feature reduction

Download

index.pdf

Date

2019

Author

Bayrak, Ahmet Engi

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

211
views

78
downloads

High penetration of broadband Internet access has made a revolution on the web usage, where users have become content generators rather than just consuming. People started to communicate, interact, maintain relationship and share data (image, video, note, location, etc.) with their acquaintances through varying online social network sites which are the key factors of that internet usage revolution. Online social networks with location sharing and interaction between people are called Location Based Social Networks (LBSNs). To use and benefit more from social networks, real life social links (friendship, acquaintanceship) should be represented well on them. Link Prediction problem has a motivation of studying social network evolution and trying to predict future possible links for representing the real-life relations better. In this work, we studied a comprehensive feature set which combines topological features with features calculated from temporal interaction data on LBSNs. We proposed novel features which are calculated by using time, category and common friend details of candidates and their social interaction in LBSNs. In addition, we proposed an effective feature reduction mechanism which helps to determine best feature subset in two steps. Contextual feature clustering is applied to remove redundant features and then a non-monotonic selection of relevant features from the calculated clusters are done by a custom designed genetic algorithm. Results depict that both new features and the proposed feature reduction method improved link prediction performance for LBSNs.

Subject Keywords

Social networks, Social networks Computer network resources, Keywords: link prediction, social networks, location based social networks, feature extraction, feature reduction.

URI

http://etd.lib.metu.edu.tr/upload/12624757/index.pdf
https://hdl.handle.net/11511/45231

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Improving performance of network intrusion detection systems through concurrent mechanisms Atakan, Mustafa; Şener, Cevat; Department of Computer Engineering (2003) As the bandwidth of present networks gets larger than the past, the demand of Network Intrusion Detection Systems (NIDS) that function in real time becomes the major requirement for high-speed networks. If these systems are not fast enough to process all network traffic passing, some malicious security violations may take role using this drawback. In order to make that kind of applications schedulable, some concurrency mechanism is introduced to the general flowchart of their algorithm. The principal aim is...
Parallel and pipelined architectures for high speed ip packet forwarding Erdem, Oğuzhan; Bazlamaçcı, Cüneyt Fehmi; Department of Electrical and Electronics Engineering (2011) A substantial increase in the number of internet users and the traffic volume bring new challenges for network router design. The current routers need to support higher link data rates and large number of line cards to accommodate the growth of the internet traffic, which necessitate an increase in physical space, power and memory use. Packet forwarding, which is one of the major tasks of a router, has been a performance bottleneck in internet infrastructure. In general, most of the packet forwarding algori...
Software implementations of QoS scheduling algorithms for high speed networks / Pehlivanlı, Aydın; Schmidt, Şenan Ece; Department of Electrical and Electronics Engineering (2015) The end to end Quality of Service (QoS) support for the dominating multimedia traffic in the contemporary computer networks is achieved by implementing schedulers in the routers and deploying traffic shapers. To this end, realistic modeling and simulation of these components is essential for network performance evaluation. The first contribution of this thesis is the design and implementation of a C++ simulator QueST (Quality of Service simulaTor) for this task. QueST is a modular cycle accurate simulator w...
Mobile multi-access IP: a proposal for mobile multi-access management in future wireless IP networks Altuntas, S; Baykal, Buyurman (Elsevier BV, 2005-03-15) As the wireless networking technologies advance rapidly, providing mobile users with roaming freely in heterogeneous wireless access domains, the need for multi-access arises. This paper introduces the Mobile Multi-Access Management Architecture (MMA-IP) for IP-based future wireless networks. MMA-IP enables mobile users to utilize multiple access domains synchronously and to switch between different access domains. In order to handle multi-access operations, MMA-IP defines a new special mobility agent, call...
Application of binary PSO for public cloud resources allocation system of video on demand (VoD) services Aygun, Betul; Günel Kılıç, Banu; ARICI, NURSAL; Coşar, Ahmet; Tuncsiper, Bedriye (Elsevier BV, 2020-01-01) Video streaming, whether on demand or live, has become one of the most popular internet applications. However, financial investments required for it is a severe problem since it needs more real time storage, higher data transfer and a significant amount of computation than other kinds of multimedia data. To tackle this problem, cloud computing, offering services without investing in hardware or software, emerges as a preferred technology. However, there are a large number of cloud service providers and they...

Citation Formats

A. E. Bayrak, “Improved link prediction for location based social networks with novel features and contextual feature reduction,” Thesis (Ph.D.) -- Graduate School of Natural and Applied Sciences. Computer Engineering., Middle East Technical University, 2019.