COOPERATION STRATEGIES FOR INFORMATION INTEGRATION - PowerPoint PPT Presentation

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COOPERATION STRATEGIES FOR INFORMATION INTEGRATION

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Maurizio Panti, Luca Spalazzi, Loris Penserini {panti,spalazzi,pense}_at_inform.unian.it ... Information systems are collections of information sources and ... – PowerPoint PPT presentation

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Title: COOPERATION STRATEGIES FOR INFORMATION INTEGRATION


1
COOPERATION STRATEGIES FORINFORMATION INTEGRATION
Istituto di Informatica - Università degli studi
di Ancona
  • Maurizio Panti, Luca Spalazzi, Loris Penserini
  • panti,spalazzi,pense_at_inform.unian.it

2
Talk Overview
  • Motivations and Goals
  • Local strategies
  • Cooperation strategies
  • the choice of partners
  • the choice of queries
  • the choice of answers
  • Discussion

3
Motivation
  • Information systems are collections of
    information sources and information consumers
  • Distributed
  • Heterogeneous
  • at physical level
  • at logical level
  • at conceptual level (names and schemas)
  • Dynamic
  • changes of information sources or their schemas
  • changes of information consumers or their needs

4
Goal
  • Rewriting a consumers query into queries to
    specific information sources
  • when we have
  • a distributed, heterogeneous, and strongly
    dynamic information system.

5
Related Work
  • Usually query rewriting and information
    integration systems adopt the
  • Mediator Architecture
  • TSIMMIS, Squirrel, WHIPS, Carnot, SIMS,
    Information Manifold, Infomaster
  • dynamic sources systems are overloaded with
    expensive updating operations
  • dynamic consumers systems do not perform user
    profiling.

6
Information Source
  • wrapper
  • a description logic as data modelling and query
    language e.g. C-Classic
  • source query processing is based on rewriting
    query using views over the local source
    adapted by Beeri, Levy, Rousset

7
Mediator
  • mediated schema
  • a description logic as data modelling and query
    language e.g. C-Classic
  • query processing is based on rewriting query
    using views over the distributed sources
    adapted by Beeri, Levy, Rousset

8
Rewriting query using views
Rewriting Composition of rewriting of retrieved
concepts
Retrieval Conjunction of concepts that are
maximally contained in the query
query Q "pub.(ai ? db) ? "pub.acm
9
Query Execution
10
Local Failures
  • In query rewritingthe mediator is not able to
    rewrite (some or all the components) of the input
    query.
  • In query executionthe mediator is not able to
    execute (some or all the components) of the
    rewrited query.

11
Cooperation Strategies

12
Cooperation with MediatorsAsking for Rewriting
Mediator M
Mediator N
13
Cooperation with MediatorsAsking for Data
Mediator M
Mediator N
14
Cooperation with Sources
Mediator M
Mediator N
15
Strategy Comparison
m number of mediators s number of sources s
number of sources that cooperate with Ni
16
Strategy Comparison
17
Conclusion
  • 1st scenario (s ms)
  • mediators can be used for user profiling,
  • mediators can be used to solve name heterogeneity
    and integrate data,
  • in order to solve schema heterogeneity, for a
    mediator the most efficient and effective
    strategy is to directly cooperate with sources,
  • in order to update its schemas, for a mediator a
    lazy approach can be not appropriate.

18
Conclusion
  • 2nd scenario (s gtgt ms)
  • mediators can be used for user profiling,
  • the most efficient strategy is the cooperation
    with other mediators,
  • cooperation with wrappers is useful only when
    mediators are not able to rewrite a given query,
  • in order to update its schemas, for a mediator a
    lazy approach is appropriate.

19
(No Transcript)
20
Ms Mediated Schema
21
Rewriting query using views
Composition of rewriting of retrieved concepts
22
Rewriting query using views
23
Local Failure in Query Rewriting
query Q"pub.(ai?db)?"affiliation.Stanford
24
Local Failure in Query Execution
no answer
25
Cooperation with MediatorsAsking for Rewriting
retrieved concepts"pub.acm_tocl, "pub.acm_tods
rewriteview("pub.acm_tocl),view("pub.acm_tods)
26
Cooperation with MediatorsAsking for Rewriting
Mediator M
rewriteview("pub.acm_tocl),view("pub.acm_tods)
27
Cooperation with MediatorsAsking for Data
retrieved concepts"pub.acm_tocl, "pub.acm_tods
rewriteview("pub.acm_tocl),view("pub.acm_tods)
28
Cooperation with MediatorsAsking for Data
rewriteview("pub.acm_tocl),view("pub.acm_tods)
29
Cooperation with MediatorsAsking for Data
rewriteview("pub.acm_tocl),view("pub.acm_tods)
30
Cooperation with Sources
retrieved"pub.acm_ccs,"pub.acm_jacm,"pub.acm_tod
s
31
Redundancy
Cn(M) mediated schema of M after n interactions
with N C(N) mediated schema of N
32
Recall
Cn(M) mediated schema of M after n interactions
with S1, Sn n information need of a consumer(a
view of S1, Sn )
33
Precision
Cn(M) mediated schema of M after n interactions
with S1, Sn n information need of a consumer(a
view of S1, Sn )
34
Ns Mediated Schema
35
Ms Mediated Schema (updated)
36
Ms Mediated Schema (updated)
37
Ms Mediated Schema (updated)
38
Cooperation with Mediators
Theorem. Cn(M) mediated schema of M after n
interactions with N C(N) mediated schema of N
redundancy
39
Cooperation with Mediators
Theorem. Cn(M) mediated schema of M after n
interactions with N n information need of a
consumer(a view of S1, Sn )
recall
precision
40
Cooperation with Sources
Theorem. Cn(M) mediated schema of M after n
interactions with S1, Sn n information need of
a consumer(a view of S1, Sn )
recall
precision
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