Recommender-based enhancement of discovery in Geoportals

In many cases web search engines like Google are still used for discovery of geographic base information. This can be explained by the fact that existing approaches for Geo-information retrieval still face significant challenges. Discovery in currently available Geoportals is usually restricted to text-based search based on keywords, title and abstract as well as applying spatial and temporal filters. Furthermore, user context as well as search results of other users are not incorporated. In order to improve the quality of search results we propose to extend the suitable searching matches in Geoportals with user behaviour and to present them as non-directly linked recommendations like in e.g. Amazon's “Customers Who Bought This Item Also Bought” approach. As shown in the proof-of-concept EU FP7 EnerGEO Geoportal, it guarantees results that are not in the data itself but rather derived from the context of other users’ searches and views.

[1]  Paul C. Smits,et al.  Resource Discovery in a European Spatial Data Infrastructure , 2007, IEEE Transactions on Knowledge and Data Engineering.

[2]  Abolghasem Sadeghi-Niaraki,et al.  ONTOLOGY BASED SDI TO FACILITATE SPATIALLY ENABLED SOCIETY , 2010 .

[3]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[4]  Joan Masó-Pau,et al.  Tuning the second-generation SDI: theoretical aspects and real use cases , 2012, Int. J. Geogr. Inf. Sci..

[5]  A. Singhal,et al.  Information Discovery--Needles and Haystacks , 2005 .

[6]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[7]  Pepijn A. J. van Oort,et al.  Geoportals: An Internet Marketing Perspective , 2009, Data Sci. J..

[8]  Lior Rokach,et al.  Introduction to Recommender Systems Handbook , 2011, Recommender Systems Handbook.

[9]  A. Rajabifard,et al.  Future directions for SDI development , 2002 .

[10]  Daniel Lemire,et al.  Slope One Predictors for Online Rating-Based Collaborative Filtering , 2007, SDM.

[11]  Meredith G. Farkas.  Social Software in Libraries: Building Collaboration, Communication, and Community Online , 2007 .

[12]  Thomas Blaschke,et al.  The GEOSS - ENERGEO portal: towards an interactive platform to calculate, forecast and monitor the environmental impact of energy carriers , 2010, EnviroInfo.

[13]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[14]  Kostas Kalabokidis,et al.  Towards a semantics-based approach in the development of geographic portals , 2009, Comput. Geosci..

[15]  Eugene Volokh,et al.  Personalization and privacy , 2000, CACM.

[16]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[17]  J. Strobl,et al.  ADDING SEMANTICS TO SPATIAL CONTENT-A LAND COVER SCENARIO , 2012 .

[18]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[19]  Yoav Shoham,et al.  Fab: content-based, collaborative recommendation , 1997, CACM.

[20]  Guy Shani,et al.  An MDP-Based Recommender System , 2002, J. Mach. Learn. Res..

[21]  M. Lutz,et al.  Overcoming semantic heterogeneity in spatial data infrastructures , 2009, Comput. Geosci..

[22]  John Riedl,et al.  Privacy , Shilling , and The Value of Information in Recommender Systems , 2005 .

[23]  Massimo Craglia,et al.  Introduction to the International Journal of Spatial Data Infrastructures Research , 2006, Int. J. Spatial Data Infrastructures Res..

[24]  Li Chen,et al.  Evaluating recommender systems from the user’s perspective: survey of the state of the art , 2012, User Modeling and User-Adapted Interaction.

[25]  I. Masser.  Building European Spatial Data Infrastructures , 2007 .

[26]  Marti A. Hearst.  Search User Interfaces , 2009 .

[27]  Alexander Felfernig,et al.  An Empirical Study on Consumer Behavior in the Interaction with Knowledge-based Recommender Applications , 2006, The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (CEC/EEE'06).

[28]  Barbara Hofer,et al.  The Development and Interlinkage of a Drought Vocabulary in the EuroGEOSS Interoperable Catalogue Infrastructure , 2012, Int. J. Spatial Data Infrastructures Res..

[29]  Dorita F. Bolger,et al.  Social Software in Libraries: Building Collaboration, Communication and Community Online , 2008 .

[30]  Krzysztof Janowicz,et al.  Implementation and Evaluation of a Semantics-based User Interface for Web Gazetteers , 2009 .

[31]  Marcello Paolo Scipioni,et al.  Towards Privacy-Aware Location-Based Recommender Systems , 2011 .

[32]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[33]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[34]  Alejandra Cechich,et al.  Ontology-driven geographic information integration: A survey of current approaches , 2009, Comput. Geosci..

[35]  John F. Canny,et al.  Collaborative filtering with privacy via factor analysis , 2002, SIGIR '02.

[36]  Michael J. Pazzani,et al.  A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.

[37]  Vitaly Shmatikov,et al.  2011 IEEE Symposium on Security and Privacy “You Might Also Like:” Privacy Risks of Collaborative Filtering , 2022 .

[38]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.