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  5. RecoMap : an interactive and adaptive map-based recommender
 
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RecoMap : an interactive and adaptive map-based recommender

Author(s)
Ballatore, Andrea  
McArdle, Gavin  
Kelly, Caitriona  
Bertolotto, Michela  
Uri
http://hdl.handle.net/10197/3357
Date Issued
2010-03
Date Available
2011-11-28T16:50:10Z
Abstract
With the growing availability of geo-referenced information on the Web, the problem of spatial information overload has attracted interest both in the commercial and academic world. In order to tackle this issue, personalisation techniques can be used to tailor spatial contents based upon user interests. RecoMap, the system described in this paper, deducts user interests by monitoring user interaction and context to provide personalised spatial recommendations. After an overview of existing recommendation systems within the geospatial domain, the novel approach adopted by RecoMap to produce such recommendations is described. A case study related to a university campus setting is used to outline an application of this technique. Details of the implementation and initial testing of this prototype are provided.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM Special Interest Group on Applied Computing
Copyright (Published Version)
2010 ACM
Subjects

GIS

Recommender systems

Map personalisation

User profiling

Subject – LCSH
Geographic information systems
Web personalization
Recommender systems (Information filtering)
User-centered system design
DOI
10.1145/1774088.1774273
Web versions
http://dl.acm.org/citation.cfm?id=1774273
Language
English
Status of Item
Peer reviewed
Journal
SAC '10 : Proceedings of the 2010 ACM Symposium on Applied Computing
Conference Details
Paper presented at the ACM 25th Symposium On Applied Computing (SAC’10), March 22-26, 2010, Sierre, Switzerland
ISBN
978-1-60558-639-7
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
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2010 - RecoMap - An Interactive and Adaptive Map-Based Recommender - Ballatore McArdle Kelly Bertolotto.pdf

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243.67 KB

Format

Adobe PDF

Checksum (MD5)

412fc2b255ecd03006b8ae1871a3117c

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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