research-article

Location-based team recommendation in computer gaming scenarios

Authors:

Michele Brocco,

Wolfgang WoerndlAuthors Info & Claims

QUeST '11: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data

Pages 21 - 28

https://doi.org/10.1145/2064969.2064973

Published: 01 November 2011 Publication History

Abstract

Computer games have evolved from rather simple single player games to multi player games played online in virtual or mixed/augmented reality worlds. This paper presents ideas to support team composition in different computer gaming scenarios. The approach is based on a generic team composition model. Various recommender techniques can be used in this framework. We explain how to extend this framework to integrate location using spatial operations in two different ways: location as constraints in the meta model and location as part of team member variables that describe attributes of potential team members. We then show how to utilize the proposed solution in location-based team recommenders ranging from games running in completely virtual environments to games whose course of action takes almost completely place in the real world.

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Cited By

Zeng YShen GChen BTang J(2019)Team Composition in PES2018 Using Submodular Function OptimizationIEEE Access10.1109/ACCESS.2019.29194477(76194-76202)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2919447
Han YWan YChen LXu GWu J(2017)Exploiting Geographical Location for Team Formation in Social Coding SitesAdvances in Knowledge Discovery and Data Mining10.1007/978-3-319-57454-7_39(499-510)Online publication date: 23-Apr-2017
https://doi.org/10.1007/978-3-319-57454-7_39

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Location-based team recommendation in computer gaming scenarios

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cover image ACM Conferences

QUeST '11: Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data

November 2011

42 pages

ISBN:9781450310376

DOI:10.1145/2064969

Copyright © 2011 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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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

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Published: 01 November 2011

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SIGSPATIAL

GIS '11: 19th SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 1, 2011

Illinois, Chicago

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Cited By

Zeng YShen GChen BTang J(2019)Team Composition in PES2018 Using Submodular Function OptimizationIEEE Access10.1109/ACCESS.2019.29194477(76194-76202)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2919447
Han YWan YChen LXu GWu J(2017)Exploiting Geographical Location for Team Formation in Social Coding SitesAdvances in Knowledge Discovery and Data Mining10.1007/978-3-319-57454-7_39(499-510)Online publication date: 23-Apr-2017
https://doi.org/10.1007/978-3-319-57454-7_39

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