research-article

Optimizing web traffic via the media scheduling problem

Authors:

Lars Backstrom,

Ravi KumarAuthors Info & Claims

KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 89 - 98

https://doi.org/10.1145/1557019.1557036

Published: 28 June 2009 Publication History

Abstract

Website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. When providing media content to visitors, it is important to present repeat visitors with new content so that they keep coming back. In this paper we present an algorithm to balance the need to keep a website fresh with new content with the desire to present the best content to the most visitors at times of peak traffic. We formulate this as the media scheduling problem, where we attempt to maximize total clicks, given the overall traffic pattern and the time varying clickthrough rates of available media content. We present an efficient algorithm to perform this scheduling under certain conditions and apply this algorithm to real data obtained from server logs, showing evidence of significant improvements in traffic from our algorithmic schedules. Finally, we analyze the click data, presenting models for why and how the clickthrough rate for new content declines as it ages.

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Cited By

Marques JObelheiro R(2017)Escada: Predicting Virtual Machine Network Bandwidth Demands for Elastic Provisioning in IaaS Clouds2017 International Conference on Cloud and Autonomic Computing (ICCAC)10.1109/ICCAC.2017.9(10-21)Online publication date: Sep-2017
https://doi.org/10.1109/ICCAC.2017.9
Ugarte WBoizumault PCrmilleux BLepailleur ALoudni SPlantevit MRassi CSoulet A(2017)Skypattern miningArtificial Intelligence10.1016/j.artint.2015.04.003244:C(48-69)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1016/j.artint.2015.04.003
Teng FTang RYang YWang HDai R(2017)Temporal Prediction Model for Social Information PropagationRough Sets10.1007/978-3-319-60837-2_38(465-476)Online publication date: 22-Jun-2017
https://doi.org/10.1007/978-3-319-60837-2_38
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Index Terms

Optimizing web traffic via the media scheduling problem
1. Theory of computation
  1. Design and analysis of algorithms
    1. Approximation algorithms analysis
      1. Scheduling algorithms
    2. Online algorithms
      1. Online learning algorithms
        Scheduling algorithms
  2. Theory and algorithms for application domains
    1. Machine learning theory
      1. Reinforcement learning
        Sequential decision making

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Published In

cover image ACM Conferences

KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining

June 2009

1426 pages

ISBN:9781605584959

DOI:10.1145/1557019

General Chairs:
John Elder
Elder Research, Inc., USA
,
Françoise Soulié Fogelman
KXEN, France
,
Program Chairs:
Peter Flach
University of Bristol, UK
,
Mohammed Zaki
RPI, USA

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 June 2009

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KDD09

Sponsor:

KDD09: The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

June 28 - July 1, 2009

Paris, France

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Marques JObelheiro R(2017)Escada: Predicting Virtual Machine Network Bandwidth Demands for Elastic Provisioning in IaaS Clouds2017 International Conference on Cloud and Autonomic Computing (ICCAC)10.1109/ICCAC.2017.9(10-21)Online publication date: Sep-2017
https://doi.org/10.1109/ICCAC.2017.9
Ugarte WBoizumault PCrmilleux BLepailleur ALoudni SPlantevit MRassi CSoulet A(2017)Skypattern miningArtificial Intelligence10.1016/j.artint.2015.04.003244:C(48-69)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1016/j.artint.2015.04.003
Teng FTang RYang YWang HDai R(2017)Temporal Prediction Model for Social Information PropagationRough Sets10.1007/978-3-319-60837-2_38(465-476)Online publication date: 22-Jun-2017
https://doi.org/10.1007/978-3-319-60837-2_38
Spyrou EMylonas P(2016)Analyzing Flickr metadata to extract location-based information and semantically organize its photo contentNeurocomputing10.1016/j.neucom.2014.12.104172:C(114-133)Online publication date: 8-Jan-2016
https://dl.acm.org/doi/10.1016/j.neucom.2014.12.104
May AChaintreau AKorula NLattanzi S(2014)Filter & followACM SIGMETRICS Performance Evaluation Review10.1145/2637364.259201042:1(43-55)Online publication date: 16-Jun-2014
https://dl.acm.org/doi/10.1145/2637364.2592010
May AChaintreau AKorula NLattanzi SSanghavi SShakkottai SLelarge MSchroeder B(2014)Filter & followThe 2014 ACM international conference on Measurement and modeling of computer systems10.1145/2591971.2592010(43-55)Online publication date: 16-Jun-2014
https://dl.acm.org/doi/10.1145/2591971.2592010
Yang JLeskovec JKing INejdl WLi H(2011)Patterns of temporal variation in online mediaProceedings of the fourth ACM international conference on Web search and data mining10.1145/1935826.1935863(177-186)Online publication date: 9-Feb-2011
https://dl.acm.org/doi/10.1145/1935826.1935863
Vithanage WAtukorale A(2011)A novel classifier for engineering web trafficProceedings of the 2011 IEEE Symposium on Computers and Communications10.1109/ISCC.2011.5983974(1009-1016)Online publication date: 28-Jun-2011
https://dl.acm.org/doi/10.1109/ISCC.2011.5983974
Bindel DKleinberg JOren S(2011)How Bad is Forming Your Own Opinion?Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science10.1109/FOCS.2011.43(57-66)Online publication date: 22-Oct-2011
https://dl.acm.org/doi/10.1109/FOCS.2011.43
Feng YNiazadeh R(undefined)Optimal Multi-stage Configuration Allocation with Applications to Video AdvertisingSSRN Electronic Journal10.2139/ssrn.3924687
https://doi.org/10.2139/ssrn.3924687
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