Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Automatic Discovery of Functional Dependencies and Conditional Functional Dependencies : A Comparative Study
DFD: Efficient Functional Dependency Discovery
Data-Driven D iscovery of Quantitative Rules in Relational Databases
Database Dependency Discovery: A Machine Learning Approach
Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes
Design by example for SQL table definitions with functional dependencies
Mining Causal Association Rules
Multivalued dependencies and a new normal form for relational databases
New Algorithms for Fast Discovery of Association Rules
Redundancy, Deduction Schemes, and Minimum-Size Bases for Association Rules
Efficient Algorithms for Discovering Association Rules
Fast discovery of association rules
Automatic discovery of attributes in relational databases
The role of Apriori algorithm for finding the association rules in Data mining
Evolutionary mining of relaxed dependencies from big data collections
Efficient Discovery of Statistically Significant Association Rules
AN EXHAUSTIVE STUDY ON ASSOCIATION RULE MINING
Mining quantitative association rules in large relational tables
StatApriori: an efficient algorithm for searching statistically significant association rules
An approach to discovering temporal association rules
Theoretical Foundations of Association Rules
Abstractive Text Summarization based on Improved Semantic Graph Approach
Anencephaly with incomplete twinning (diprosopus).
sparse and low - rank matrix decomposition via alternating direction methods .
Quality Investing
Dynamic itemset counting and implication rules for market basket data