Tables are ubiquitous. Unfortunately, no search engine supportstable search. In this paper, we propose a novel table specificsearching engine, TableSeer, to facilitate the table extracting, indexing, searching, and sharing. In addition, wepropose an extensive set of medium-independent metadata to precisely present tables. Given a query, TableSeer ranks the returned results using an innovative ranking algorithm - TableRank with a tailored vector space model and a novel term weightingscheme. Experimental results show that TableSeer outperforms existing search engines on table search. In addition, incorporating multiple weighting factors can significantly improve the ranking results.