Abstract
Information overload is a well known issue across many domains. Due to an increase in the quantity of information associated with geographic data, information overload is now also prevalent in the spatial domain. This makes interacting with maps tedious and difficult, as extracting relevant information becomes laborious. Map personalisation offers a solution to this problem. By implicitly monitoring user behaviour and interaction with maps, common patterns, preferences and interests can be identified. Using this approach, personalised maps can be generated which match user preferences and contribute to resolving information overload in the spatial domain. Traditionally data mining techniques are used to identify preferences however, visual analytics has proven useful in detecting interests and patterns not apparent via data mining. This paper presents a visual analysis tool called VizAnalysisTools, which can be used by developers and analysts to detect patterns in Web map usage among groups of users. The knowledge gained through this visual analysis can be used to strengthen map personalisation techniques.
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References
Andrienko, G., Andrienko, N., Demsar, U., Dranschc, D., Dykesd, J., Fabrikante, S., Jernf, M., Kraakg, M., Schumannh, H., Tominskih, C.: Space, Time and Visual Analytics. International Journal of Geographical Information Science 24(10), 1577–1600 (2010)
Andrienko, G., Andrienko, N., Wrobel, S.: Visual Analytics Tools for Analysis of Movement Data. ACM SIGKDD Explorations Newsletter 9(2), 38–46 (2007)
Andrienko, N., Andrienko, G., Voss, H., Bernardo, F., Hipolito, J., Kretchmer, U.: Testing the Usability of Interactive Maps in CommonGIS. Cartography and Geographic Information Science 29(4), 325–343 (2002)
Arroyo, E., Selker, T., Wei, W.: Usability Tool for Analysis of Web Designs Using Mouse Tracks. In: CHI 2006 Extended Abstracts on Human Factors in Computing Systems, pp. 484–489. ACM, New York (2006)
Ballatore, A., McArdle, G., Kelly, C., Bertolotto, M.: RecoMap: An Interactive and Adaptive Map-based Recommender. In: Proceedings of the 2010 ACM Symposium on Applied Computing, pp. 887–891. ACM, New York (2010)
Chen, C.: Information Visualization. Wiley Interdisciplinary Reviews: Computational Statistics 2(4), 387–403 (2010)
Claypool, M., Le, P., Wased, M., Brown, D.: Implicit Interest Indicators. In: Proceedings of the 6th International Conference on Intelligent User Interfaces, pp. 33–40. ACM, New York (2001)
Curbera, F., Duftler, M., Khalaf, R., Nagy, W., Mukhi, N., Weerawarana, S.: Unraveling the Web Services Web: An Introduction to SOAP, WSDL, and UDDI. IEEE Internet Computing 6(2), 86–93 (2002)
Demsar, U., Virrantaus, K.: Space-time Density of Trajectories: Exploring Spatio-temporal Patterns in Movement Data. International Journal of Geographical Information Science 24(10), 1527–1542 (2010)
Fisher, D.: Hotmap: Looking at Geographic Attention. IEEE Transactions on Visualization and Computer Graphics 13(6), 1184–1191 (2007)
Ginige, A., Murugesan, S.: Web Engineering: An Introduction. IEEE Multimedia 8(1), 14–18 (2002)
Hagerstrand, T.: What About People in Regional Science? Papers in Regional Science 24(1), 6–21 (1970)
Haklay, M., Singleton, A., Parker, C.: Web Mapping 2.0: The Neogeography of the Geoweb. Geography Compass 2(6), 2011–2039 (2008)
Keim, D.: Information Visualization and Visual Data Mining. IEEE Transactions on Visualization and Computer Graphics 8(1), 1–8 (2002)
Mac Aoidh, E., Bertolotto, M., Wilson, D.: Analysis of Implicit Interest Indicators for Spatial Data. In: Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems, p. 47. ACM, New York (2007)
Mac Aoidh, E., Bertolotto, M., Wilson, D.: Understanding Geospatial Interests by Visualizing Map Interaction Behavior. Information Visualization 7(3), 275–286 (2008)
Mac Aoidh, E., McArdle, G., Petit, M., Ray, C., Bertolotto, M., Claramunt, C., Wilson, D.: Personalization in Adaptive and Interactive GIS. Annals of GIS 15(1), 23–33 (2009)
McArdle, G., Ballatore, A., Tahir, A., Bertolotto, M.: An Open-Source Web Architecture for Adaptive Location Based Services. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Hong Kong, vol. 38(2), pp. 296–301 (2010)
Mueller, F., Lockerd, A.: Cheese: Tracking Mouse Movement Activity on Websites, A Tool for User Modeling. In: CHI 2001 Extended Abstracts on Human Factors in Computing Systems, pp. 279–280. ACM, New York (2001)
O’reilly, T.: What is Web 2.0. Design Patterns and Business Models for the Next Generation of Software 1, 17 (2007), available at SSRN: http://ssrn.com/abstract=1008839
Seffah, A., Donyaee, M., Kline, R., Padda, H.: Usability Measurement and Metrics: A Consolidated Model. Software Quality Journal 14(2), 159–178 (2006)
Tahir, A., McArdle, G., Ballatore, A., Bertolotto, M.: Collaborative Filtering- A Group Profiling Algorithm for Personalisation in a Spatial Recommender System. In: Proceedings Geoinformatik, Kiel, Germany, pp. 44–50 (2010)
Wu, W., Noble, W.: Genomic Data Visualization on the Web. Bioinformatics, 1541 (2004)
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Tahir, A., McArdle, G., Bertolotto, M. (2011). A Web-Based Visualisation Tool for Analysing Mouse Movements to Support Map Personalisation. In: Xu, J., Yu, G., Zhou, S., Unland, R. (eds) Database Systems for Adanced Applications. DASFAA 2011. Lecture Notes in Computer Science, vol 6637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20244-5_13
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DOI: https://doi.org/10.1007/978-3-642-20244-5_13
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