Making Sense of (Multi-) Relational Data

“Making Sense of (Multi-) Relational Data”

Tutorial at ECML-PKDD 2015.

11 September 2015, Porto, Portugal

diagram

The slides are now available: part 1, part 2, part 3, part 4, part 5, part 6.

Outline:

PART I: Mining relational data — an overview (40 mins)

  • Data types: Codd’s relational data model, triple stores (linked data), networks, n-ary relations
  • Pattern syntax
  • Algorithmic approach (e.g. exhaustive enumeration or not)
  • `Supervised’ or not, or in between
  • Interestingness measures

PART II: Exploration through targeted modelling (20 mins)

  • Safarii
  • RDB-Krimp
  • (Probabilistic) ILP

PART III: Exploration by descriptive modelling – semi-relational local algorithms (20 mins)

  • Frequent itemset mining on the join
  • SMuRFIG

— BREAK

PART IV: Exploration by descriptive modeling – fully-relational local algorithms (40 mins)

  • N-set mining
  • RMiner \& variants
  • Constraint programming for closed relational sets
  • Uncovering the plot

PART V: Exploration by descriptive modeling – fully-relational global algorithms (40 mins)

  • Joint matrix-tensor factorisations

PART VI: Perspectives (20 mins)

  • General conclusions and recommendations
  • Open problems and opportunities