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Reconciling personalization with privacy has been a continuing interest in user modeling research. This aim has computational, legal and behavioral/attitudinal ramifications. We present a dynamic privacy-enhancing user modeling framework that supports compliance with users' personal privacy preferences and with the privacy laws and regulations that apply to them. The framework is based on a software product line architecture. It dynamically selects personalization methods during runtime thatdoi:10.1007/s11257-011-9114-8 fatcat:jhpcqwfyxbfptlu5cbpiorr3ga