ATCS 2016-2017

Advanced Topics in Computer Science

This course (6 CFU) will be held by three external professors, the first is Prof. Kevin Koidl from the Trinity College, Dublin, Ireland, Prof. Divesh Srivastava from AT&T Labs-Research, New Jersey, USA, and Prof. Denilson Barbosa from University of Alberta, Edmonton, Canada.

Prof. Kevin Koidl holds a PhD in Computer Science from the Trinity College in Dublin, Ireland (2013), and is currently a Research Fellow at the same university. Prof. Divesh Srivastava holds a PhD in Computer Sciences, University of Wisconsin, Madison, USA (1993), and is currently the Head of Database Research at the AT&T Labs-Research. Prof. Denilson Barbosa holds a PhD in Computer Science from the University of Toronto, Canada (2005), and is currently Associate Professor at the Department of Computing Science at the University of Alberta, Canada.

Schedule

  • Monday and Wednesday, 2.00pm-4.00pm, room N13 (subject to changes)

Machine Learning for NLP

Prof. Kevin Koidl

Tentative Dates: 6/3, 13/3, 20/3, 27/3



Big data integration

Prof. Divesh Srivastava

Tentative Dates: 3/4, 5/4, 10/4, 12/4

Motivation: Challenges and Opportunities for BDI

  • Traditional Data Integration
  • BDI: Challenges
  • BDI: Opportunities

Schema Alignment

  • Traditional Schema Alignment
  • Addressing the Variety, Velocity, and Volume Challenges

Record Linkage

  • Traditional Record Linkage
  • Addressing the Volume, Velocity, Variety, and Veracity Challenges

BDI: Data Fusion

  • Traditional Data Fusion
  • Addressing the Volume, Velocity, Variety, and Veracity Challenges

BDI: Emerging Topics

  • Role of Crowdsourcing
  • Source Selection
  • Source Profiling

Knowledge extraction from the web

Prof. Denilson Barbosa

Tentative Dates: 15/5, 17/5, 22/5, 24/5, 29/5, 31/5, 5/6, 7/6

Kinds of Knowledge

  • Factual
  • Ontological
  • Temporal
  • Common sense

Knowledge Representation

  • Reasoning
  • Querying (SPARQL)

Knowledge bases vs knowledge graphs

Knowledge extraction

  • Class identification
  • Instance identification
  • Organizing classes into a hierarchy
  • Relation identification
  • Validation of information extracted from the Web

Applications

  • Query understanding
  • Question answering