Online social networks connect our physical daily life and the virtual Web space. The user generated data is becoming big, heterogeneous, and highly connected. In this talk, I will first present our recently developed methodologies and algorithms for connecting multiple heterogeneous networks (COSNET) and top-k similarity search (Panther). Both algorithms have been deployed to an online academic search and mining system AMiner, which has collected a large scholar dataset, with more than 130,000,000 researcher profiles and 100,000,000 papers from multiple publication databases. With COSNET, we connect AMiner with several professional social networks, such as LinkedIn and VideoLectures, which significantly enriches the scholar metadata. Panther is used to find similar authors in AMiner and can return top-k similar vertices 300× faster than the state-of-the-art methods..