A personalized anonymization model needs to provide user-defined privacy rules to meet user's personal privacy preferences. The location obfuscation techniques that are based on the use of geometric methods also needs to consider location semantics to prevent privacy leaks.Such a obfuscation model needs to be extensible towards a probabilistic model to account varying sensitivity. We introduce a combined approach to achieve more comprehensive solution for privacy preservation in such systems. ]]>