User data stored in personal information systems is growing massively. Simultaneously, this data is increasingly distributed across multiple organizational domains such as email, music databases, and photo albums, some of which are structured automatically by applications. Powerful search tools are needed to help users locate data in these expanding yet fragmented data sets. In this paper, we present a novel fuzzy search approach that considers approximate matches to structure and content query conditions. Our framework uses unified data and query processing models so that structure conditions can be approximately matched by content and vice versa. Our models also unify external structure (e.g., directories) with internal structure (e.g., XML structure), supporting integrated queries matched to a single data domain. We propose indexes and algorithms for efficient query processing. We evaluate our approach using a real data set, showing that it can leverage structure information to significantly improve search accuracy, yet is robust to mistakes in query conditions.