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 speci c 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. •Information systems →Environment-speci c retrieval; Users and interactive retrieval; Recommender systems; Probabilistic retrieval models;
Zhang et al. REF developed generative probabilistic models to equip spreadsheets with smart assistance capabilities.
EntiTables: Smart Assistance for Entity-Focused Tables
SIGIR '17
Computer Science