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There has been considerable interest in development of scholar search engines. A disadvantage of current scholar search engines is that they have not explored the relationship among theses fully. A novel scholar search engine is proposed here to fill this gap, which can detect different topics hidden in a large volume of theses to help researchers find their interested theses easily. A new community detection algorithm in citation networks is proposed here to achieve detecting topics. This algorithm has time complexity O(c*n) in a sparse citation network, where n is the number of nodes, and c is related to the average degree of nodes and the initial number of communities. Initial experiments show that this algorithm produces effective result on a standard test dataset.

TopSeer: A Novel Scholar Search Engine based on Community Detection in Citation Network