Personalization Techniques and Recommender Systems
World Scientific Publishing Company / 2008出版

==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-Fernández 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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