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Personalization Techniques And Recommender Systems (Series in Machine Perception and Artificial Intelligence ???) (Series in Machine Perception and Artificial ... Perception and Artifical Intelligence) [Hardcover]

By Gulden Uchyigit (Author)
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Item description for Personalization Techniques And Recommender Systems (Series in Machine Perception and Artificial Intelligence ???) (Series in Machine Perception and Artificial ... Perception and Artifical Intelligence) by Gulden Uchyigit...

The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed.

The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems.

This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.

Contents: User Modeling and Profiling: Personalization-Privacy Tradeoffs in Adaptive Information Access (B Smyth); A Deep Evaluation of Two Cognitive User Models for Personalized Search (F Gasparetti & A Micarelli); Unobtrusive User Modeling for Adaptive Hypermedia (H J Holz et al.); User Modelling Sharing for Adaptive e-Learning and Intelligent Help (K Kabassi et al.); Collaborative Filtering: Experimental Analysis of Multiattribute Utility Collaborative Filtering on a Synthetic Data Set (N Manouselis & C Costopoulou); Efficient Collaborative Filtering in Content-Addressable Spaces (S Berkovsky et al.); Identifying and Analyzing User Model Information from Collaborative Filtering Datasets (J Griffith et al.); Content-Based Systems, Hybrid Systems and Machine Learning Methods: Personalization Strategies and Semantic Reasoning: Working in Tandem in Advanced Recommender Systems (Y Blanco-Fernndez et al.); Content Classification and Recommendation Techniques for Viewing Electronic Programming Guide on a Portable Device (J Zhu et al.); User Acceptance of Knowledge-Based Recommenders (A Felfernig et al.); Using Restricted Random Walks for Library Recommendations and Knowledge Space Exploration (M Franke & A Geyer-Schulz); An Experimental Study of Feature Selection Methods for Text Classification (G Uchyigit & K Clark).



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Item Specifications...


Studio: World Scientific Publishing Company
Pages   336
Est. Packaging Dimensions:   Length: 8.98" Width: 6.06" Height: 0.94"
Weight:   1.32 lbs.
Binding  Hardcover
Release Date   Apr 4, 2008
Publisher   World Scientific Publishing Company
ISBN  9812797017  
ISBN13  9789812797018  


Availability  0 units.


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1Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Computer Mathematics
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