Automatic Searching of Tables in Digital Libraries
Tables are ubiquitous. Unfortunately, no search engine supports table search. In this paper, we propose a novel table specific searching engine, TableSeer, to facilitate the table extracting, indexing, searching, and sharing. In addition, we propose 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 weighting scheme. Experimental results show that TableSeer outperforms existing search engines on table search. In addition, incorporating multiple weighting factors can significantly improve the ranking results.