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Eventshop: from heterogeneous web streams to personalized situation detection and control

Published: 22 June 2012 Publication History

Abstract

The Web now has enormous volume of heterogeneous data being continuously reported by different sensors and humans from different locations. These data flows can be considered as spatio-temporal-thematic streams. Combined effectively, these streams can be used for detecting situations and saving lives and resources. We describe a system to combine streams from heterogeneous data sources, process them to detect situations, and use the detected situations to aid millions of users. This system uses a unified data model to integrate different web streams, and provides a set of generic operators to detect spatio-temporal characteristics of individual or combined data streams to detect complex situations. The detected situations can be combined with user parameters to provide personalized information and action alerts.

References

[1]
M. Montanari, S. Mehrotra, and N. Venkatasubramanian. Architecture for an automatic customized warning system. In ISI, 2007.
[2]
V. Singh, M. Gao, and R. Jain. Social pixels: genesis and evaluation. In ACM MM, 2010.

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  • (2020)Application of Machine Learning in Wireless Sensor NetworkEncyclopedia of Wireless Networks10.1007/978-3-319-78262-1_282(21-27)Online publication date: 30-Aug-2020
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  • (2019)Flooding disaster resilience information framework for smart and connected communitiesJournal of Reliable Intelligent Environments10.1007/s40860-019-00073-2Online publication date: 26-Feb-2019
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cover image ACM Conferences
WebSci '12: Proceedings of the 4th Annual ACM Web Science Conference
June 2012
531 pages
ISBN:9781450312288
DOI:10.1145/2380718
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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New York, NY, United States

Publication History

Published: 22 June 2012

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  • Research-article

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WebSci '12
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WebSci '12: Web Science 2012
June 22 - 24, 2012
Illinois, Evanston

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Overall Acceptance Rate 245 of 933 submissions, 26%

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Cited By

View all
  • (2020)Application of Machine Learning in Wireless Sensor NetworkEncyclopedia of Wireless Networks10.1007/978-3-319-78262-1_282(21-27)Online publication date: 30-Aug-2020
  • (2019)A Navigational Approach to Health: Actionable Guidance for Improved Quality of LifeComputer10.1109/MC.2018.288328052:4(12-20)Online publication date: Apr-2019
  • (2019)Flooding disaster resilience information framework for smart and connected communitiesJournal of Reliable Intelligent Environments10.1007/s40860-019-00073-2Online publication date: 26-Feb-2019
  • (2018)Application of Machine Learning in Wireless Sensor NetworkEncyclopedia of Wireless Networks10.1007/978-3-319-32903-1_282-1(1-7)Online publication date: 30-Nov-2018
  • (2017)BibliographyFrontiers of Multimedia Research10.1145/3122865.3122878(315-377)Online publication date: 19-Dec-2017
  • (2017)Towards a platform for community-centric smart connected servicesProceedings of the 2nd International Workshop on Science of Smart City Operations and Platforms Engineering10.1145/3063386.3063769(40-45)Online publication date: 18-Apr-2017
  • (2017)Integration of Diverse Data Sources for Spatial PM2.5 Data InterpolationIEEE Transactions on Multimedia10.1109/TMM.2016.261363919:2(408-417)Online publication date: 1-Feb-2017
  • (2017)Frontiers of Multimedia ResearchundefinedOnline publication date: 19-Dec-2017
  • (2016)Using Photos as Micro-Reports of EventsProceedings of the 2016 ACM on International Conference on Multimedia Retrieval10.1145/2911996.2912020(87-94)Online publication date: 6-Jun-2016
  • (2016)Case Studies: Using EventShop for Creating Multiple Situation Recognition ApplicationsSituation Recognition Using EventShop10.1007/978-3-319-30537-0_9(121-135)Online publication date: 1-Jun-2016
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