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We address the task of auto-completing data cells in relational tables. Suchtables describe entities (in rows) with their attributes (in columns). Wepresent the CellAutoComplete framework to tackle several novel aspects of thisproblem, including: (i) enabling a cell to have multiple, possibly conflictingvalues, (ii) supplementing the predicted values with supporting evidence, (iii)combining evidence from multiple sources, and (iv) handling the case where acell should be left empty. Our framework makes use of a large table corpus anda knowledge base as data sources, and consists of preprocessing, candidatevalue finding, and value ranking components. Using a purpose-built testcollection, we show that our approach is 40\% more effective than the bestbaseline.

Auto-completion for Data Cells in Relational Tables