$30 off During Our Annual Pro Sale. View Details »

Soft Cardinality Constaints on XML Data

Emir Muñoz
October 13, 2013

Soft Cardinality Constaints on XML Data

Soft Cardinality Constraints on XML Data, How Exceptions Prove the Business Rule. Research Paper at WISE 2013, Nanjing, China, 14th October 2013.

Emir Muñoz

October 13, 2013
Tweet

More Decks by Emir Muñoz

Other Decks in Research

Transcript

  1. Soft Cardinality Constraints on XML Data
    How Exceptions Prove the Business Rule
    Emir Muñoz
    Fujitsu Ireland Ltd.
    Joint work with F. Ferrarotti, S. Hartmann, S. Link, M. Marin
    @ Nanjing, China, 14th October 2013

    View Slide

  2. Contribution
    • Introduce the definition of soft cardinality
    constraints over XML data.
    • Efficient low-degree polynomial time decision
    algorithm for the implication problem.
    • Empirical evaluation of soft cardinality
    constraints on real XML data.
    Emir M. - WISE, Nanjing, China, 14th October 2013 2

    View Slide

  3. Outline
    1. Introduction
    2. Soft Cardinality Constraints
    3. The Implication Problem
    4. Performance Evaluation
    5. Conclusion
    Emir M. - WISE, Nanjing, China, 14th October 2013 3

    View Slide

  4. Introduction
    Concepts
    • Cardinality constraints:
    – Capture information about the frequency with
    which certain data items occur in particular
    context.
    • Soft cardinality constraints:
    – Constraints which need to be satisfied on average
    only, and thus permit violations in a controlled
    manner.
    Emir M. - WISE, Nanjing, China, 14th October 2013 4

    View Slide

  5. Introduction
    Example (1/2)
    Emir M. - WISE, Nanjing, China, 14th October 2013 5
    Project within a research institute
    support
    research

    View Slide

  6. • Some cardinality constraints:
    – Every scientist is a member of 2, 3, or 4 research
    teams.
    – Every technician can work in up to 4 different
    support teams.
    – A project cannot have more than one manager.
    – In every team, there should be two employees for
    each expertise level.
    Emir M. - WISE, Nanjing, China, 14th October 2013 6
    Introduction
    Example (2/2)

    View Slide

  7. • Some cardinality constraints:
    – Every scientist is a member of 2, 3, or 4 research
    teams.
    – Every technician can work in up to 4 different
    support teams.
    – A project cannot have more than one manager.
    – In every team, there should be two employees for
    each expertise level.
    Emir M. - WISE, Nanjing, China, 14th October 2013 7
    Introduction
    Example (2/2)
    Probably will be exceptions
    Scientist working in 5
    research teams or more
    Soft constraints

    View Slide

  8. Soft Cardinality Constraints
    Definition
    • Expressiveness from the ability to specify soft
    upper bounds (soft-max) as well as soft lower
    bounds (soft-min) on the number of nodes.
    • soft-card(Q, (Q´, {Q1,…, Qk})) = (soft-min, soft-max)
    • With some sources of intractability
    Emir M. - WISE, Nanjing, China, 14th October 2013 8
    Context path
    Target path
    Field paths
    soft-min = 1

    View Slide

  9. • Every scientist is a member of 2, 3, or 4 research
    teams.
    – soft-card(ε, (_.RTeam.Sci, {id})) = (2, 4)
    • Every technician can work in up to 4 different
    support teams.
    – soft-card(ε, (_.STeam.Tech, {id})) = (1, 4)
    • A project cannot have more than one manager.
    – soft-card(_, (Manager, Ø)) = (1, 1)
    • In every team, there should be two employees
    for each expertise level.
    – soft-card(_._, (_, {Expertise.S})) = (2, 2)
    Emir M. - WISE, Nanjing, China, 14th October 2013 9
    Soft Cardinality Constraints
    Examples

    View Slide

  10. The Implication Problem
    Definition and Algorithm
    • Let be a finite set of (soft) constraints.
    • We say that finitely implies , denoted by
    if every finite XML T that satisfies all also
    satisfies
    Emir M. - WISE, Nanjing, China, 14th October 2013 10

    View Slide

  11. Performance Evaluation
    Configuration
    • We compare the performance against XML
    Keys
    • Machine Intel Core i7 2.8GHz, with 4G RAM
    • Documents:
    – 321gone, yahoo (auction data)
    – dblp (bibliographic information on CS)
    – nasa (astronomical data)
    – SigmodRecord (articles from SIGMOD Record)
    – mondial (world geographic db)
    Emir M. - WISE, Nanjing, China, 14th October 2013 11

    View Slide

  12. Performance Evaluation
    Results
    Expressivity
    Time
    Emir M. - WISE, Nanjing, China, 14th October 2013 12
    In comparison with
    previous XML keys

    View Slide

  13. Conclusion
    • We introduced an expressive class of soft
    cardinality constraints, sufficiently flexible to
    boost XML applications such as data exchange
    and integration.
    • Slight extensions result in the intractability of the
    associated implication problem.
    • We give an axiomatization for this new class.
    • Present an empirical performance test that
    indicate its efficient application in real use cases.
    Emir M. - WISE, Nanjing, China, 14th October 2013 13

    View Slide

  14. Discussion
    • Questions & Answers
    – Soft Cardinality Constraints on XML Data
    THANKS!
    Emir Muñoz
    [email protected]
    Emir M. - WISE, Nanjing, China, 14th October 2013 14

    View Slide