Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Herstellerkennzeichnung
Die Herstellerinformationen sind derzeit nicht verfügbar.
Autorenporträt
Bamshad Mobasher, DePaul University, Chicago, IL, USA / Sarabjot Singh Anand, University of Warwick, Coventry, UK
Inhaltsangabe
Intelligent Techniques for Web Personalization.- Intelligent Techniques for Web Personalization.- User Modelling.- Modeling Web Navigation: Methods and Challenges.- The Traits of the Personable.- Addressing Users' Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation.- Recommender Systems.- Case-Based Recommender Systems: A Unifying View.- Improving the Performance of Recommender Systems That Use Critiquing.- Hybrid Systems for Personalized Recommendations.- Enabling Technologies.- Collaborative Filtering Using Associative Neural Memory.- Scaling Down Candidate Sets Based on the Temporal Feature of Items for Improved Hybrid Recommendations.- Discovering Interesting Navigations on a Web Site Using SAM I .- Personalized Information Access.- Personalisation of Web Search.- The Compass Filter: Search Engine Result Personalization Using Web Communities.- Predicting Web Information Content.- Systems and Applications.- Mobile Portal Personalization: Tools and Techniques.- IKUM: An Integrated Web Personalization Platform Based on Content Structures and User Behavior.- A Semantic-Based User Privacy Protection Framework for Web Services.- Web Personalisation for Users Protection: A Multi-agent Method.
Intelligent Techniques for Web Personalization.- Intelligent Techniques for Web Personalization.- User Modelling.- Modeling Web Navigation: Methods and Challenges.- The Traits of the Personable.- Addressing Users' Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation.- Recommender Systems.- Case-Based Recommender Systems: A Unifying View.- Improving the Performance of Recommender Systems That Use Critiquing.- Hybrid Systems for Personalized Recommendations.- Enabling Technologies.- Collaborative Filtering Using Associative Neural Memory.- Scaling Down Candidate Sets Based on the Temporal Feature of Items for Improved Hybrid Recommendations.- Discovering Interesting Navigations on a Web Site Using SAM I .- Personalized Information Access.- Personalisation of Web Search.- The Compass Filter: Search Engine Result Personalization Using Web Communities.- Predicting Web Information Content.- Systems and Applications.- Mobile Portal Personalization: Tools and Techniques.- IKUM: An Integrated Web Personalization Platform Based on Content Structures and User Behavior.- A Semantic-Based User Privacy Protection Framework for Web Services.- Web Personalisation for Users Protection: A Multi-agent Method.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826
