Searching for Tables in Digital Documents

Tables are ubiquitous. In scientific documents, tables are widely used to present experimental results or statistical data in a condensed fashion. Current search engines do not allow the end-user to search for relevant tables. In this paper, we describe TableSeer, an automatic table extraction and search engine system. TableSeer crawls scientific documents, identifies documents with tables, extracts tables from documents, indexes them and enables end-users to search for tables. We also propose an extensive set of medium-independent metadata for tables representation. Given a query, TableSeer ranks the returned results using an innovative ranking algorithm - TableRank. Our results show that TableSeer outperforms popular search engines, such as Google Scholar when the end-user seeks for tables.