With the increase of resource-sharing web sites such as YouTube1 and Flickr2, personalized search becomes more important and challenging, as users demand higher retrieval quality. To achieve this goal, personalized search needs to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy ) systems allow users to annotate resources with their own tags, which provide a simple but powerful way for organizing, retrieving and sharing different types of social resources. In this paper, we examine the limitations of previous tag-based personalized search. To handle these limitations, we propose a new method to model user profiles and resource profiles in a collaborative tagging environment. A novel search method using such users' and resources' profiles is proposed to facilitate the desired personalization in resource search. We implement a prototype system named as FMRS. Experiments using FMRS data set and MovieLens data set show that our proposed method outperforms baseline methods.