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Identifying website communities in mobile internet based on affinity measurement

Authors:

Nirwan AnsariAuthors Info & Claims

Computer Communications, Volume 41

Pages 22 - 30

https://doi.org/10.1016/j.comcom.2013.12.008

Published: 01 March 2014 Publication History

Abstract

With the rapid development of mobile devices and wireless technologies, mobile internet websites play an essential role for delivering networked services in our daily life. Thus, identifying website communities in mobile internet is of theoretical and practical significance in optimizing network resource and improving user experience. Existing solutions are, however, limited to retrieve website communities based on hyperlink structure and content similarities. The relationships between user behaviors and community structures are far from being understood. In this paper, we develop a three-step algorithm to extract communities by affinity measurement derived from user accessing information. Through experimental evaluation with massive detailed HTTP traffic records captured from a cellular core network by high performance monitoring devices, we show that our affinity measurement based method is effective in identifying hidden website communities in mobile internet, which have evaded previous link-based and content-based approaches.

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Cited By

Fang CLiu B(2018)Exploration of Web Page Structural Patterns Based on Request Dependency Graph DecompositionInternational Journal of Digital Crime and Forensics10.4018/IJDCF.20161001018:4(1-13)Online publication date: 13-Dec-2018
https://dl.acm.org/doi/10.4018/IJDCF.2016100101
Fang CLiu JAnsari N(2018)Revealing connectivity structural patterns among web objects based on co-clustering of bipartite request dependency graphWireless Networks10.1007/s11276-016-1345-524:2(439-451)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11276-016-1345-5
Yin BLu XHuang JKang Y(2016)Analysis of topology dynamics for unstructured P2P networksComputer Communications10.1016/j.comcom.2016.01.00980:C(72-81)Online publication date: 15-Apr-2016
https://dl.acm.org/doi/10.1016/j.comcom.2016.01.009
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Published In

cover image Computer Communications

Computer Communications Volume 41, Issue

March, 2014

94 pages

ISSN:0140-3664

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2014.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 March 2014

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Cited By

Fang CLiu B(2018)Exploration of Web Page Structural Patterns Based on Request Dependency Graph DecompositionInternational Journal of Digital Crime and Forensics10.4018/IJDCF.20161001018:4(1-13)Online publication date: 13-Dec-2018
https://dl.acm.org/doi/10.4018/IJDCF.2016100101
Fang CLiu JAnsari N(2018)Revealing connectivity structural patterns among web objects based on co-clustering of bipartite request dependency graphWireless Networks10.1007/s11276-016-1345-524:2(439-451)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1007/s11276-016-1345-5
Yin BLu XHuang JKang Y(2016)Analysis of topology dynamics for unstructured P2P networksComputer Communications10.1016/j.comcom.2016.01.00980:C(72-81)Online publication date: 15-Apr-2016
https://dl.acm.org/doi/10.1016/j.comcom.2016.01.009
Bedogni LDiźFelice MBononi L(2016)Context-aware Android applications through transportation mode detection techniquesWireless Communications & Mobile Computing10.1002/wcm.270216:16(2523-2541)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1002/wcm.2702

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