EntiTables: Smart Assistance for Entity-Focused Tables
This work addresses the need for automated assistance in spreadsheet programs to enhance productivity for users working with entity-focused tables, representing an incremental improvement over prior methods.
The paper tackled the problem of providing smart assistance for entity-focused tables by developing generative probabilistic models to populate rows with entities and columns with headings, using knowledge bases and a large table corpus. The results showed that the models' components are complementary and outperform existing approaches.
Tables are among the most powerful and practical tools for organizing and working with data. Our motivation is to equip spreadsheet programs with smart assistance capabilities. We concentrate on one particular family of tables, namely, tables with an entity focus. We introduce and focus on two specific tasks: populating rows with additional instances (entities) and populating columns with new headings. We develop generative probabilistic models for both tasks. For estimating the components of these models, we consider a knowledge base as well as a large table corpus. Our experimental evaluation simulates the various stages of the user entering content into an actual table. A detailed analysis of the results shows that the models' components are complimentary and that our methods outperform existing approaches from the literature.