TableSeer: Automatic Table Metadata Extraction and Searching in Digital Libraries

Abstract

In this paper, we describe TableSeer, a search engine for tables. TableSeer crawls digi-tal libraries, detects tables from documents, extracts tables metadata, indexes and ranks tables, and provides a user-friendly search interface. We propose an extensive set of medium-independent metadata for tables that scientists and other users can adopt for representing table information. In addition, we devise a novel page box-cutting method to improve the performance of the table detection. Given a query, TableSeer ranks the matched tables using an innova-tive ranking algorithm { TableRank. TableRank rates each <query, table> pair with a tailored vector space model and a speci¯c term weighting scheme. Overall, TableSeer elimi-nates the burden of manually extract table data from digital libraries and enables users to automatically examine tables. We demonstrate the value of TableSeer with empirical studies on scienti¯c documents.