Daedalus
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  • A flurry of research has covered with spatio-temporal data analysis from different perspectives. The definition of new movement patterns. The development of solutions to algorithmic issues, with which to improve existing pattern-mining schemes Little attention has been paid to the definition of a unifying framework, wherein to set the above pattern-mining tools as specific components of the knowledge discovery process. Knowledge discovery is a multi-step process, that involves data preprocessing, different pattern mining stages and pattern postprocessing.
  • A flurry of research has covered with spatio-temporal data analysis from different perspectives. The definition of new movement patterns. The development of solutions to algorithmic issues, with which to improve existing pattern-mining schemes Little attention has been paid to the definition of a unifying framework, wherein to set the above pattern-mining tools as specific components of the knowledge discovery process. Knowledge discovery is a multi-step process, that involves data preprocessing, different pattern mining stages and pattern postprocessing.

Transcript

  • 1. R. Ortale (2) , E. Ritacco (2) , N. Pelekis (3) R. Trasarti (1), F. Giannotti (1) , C. Renso (1) , G. Costa (2) , G. Manco (2) , Y. Theodoridis (3) ‏ (1) ISTI-CNR , Pisa, Italy (2) ICAR-CNR , Rende (CS), Italy (3) Univerity of Pireus , Athens, Greece The DAEDALUS Framework: Progressive Querying and Mining of Movement Data
  • 2. Motivation
    • Knowledge discovery is a multi-step process, that involves data preprocessing, pattern mining stages and pattern postprocessing.
    • Lack of a unifying framework , where mining tools are specific components of the knowledge discovery process.
  • 3. Motivation
    • Which trajectories support T-pattern that are inside a polluted area?
    • SELECT Trajectories.id
    • FROM Patterns, Trajectories, Polluted_Areas
    • WHERE Trajectories.object satisfies Patterns.object
    • AND Polluted_Areas.geometry includes Patterns.object. Geometry
    • This is an example of Join query between patterns, trajectories and background geographic knowledge
  • 4. Motivation
    • Amalgamating elements from different worlds causes an impedence mismatch
    • Different representations, different objectives
    • Idea
    • Explicitly represent objects in these different worlds
    • Provide bridges through the worlds
  • 5. The Two Worlds framework Filtering operators : manipulate basic objects. Mining operators : extract properties from samples. K:D  M Population operators : detect samples exhibiting properties. P:DxM  D
  • 6. From Two Worlds to Daedalus Hermes is the repository of both data and models. Hermes has been extended to represent objects in M-World: Model_TAS, (T-Pattern) The mining operator is realized by calling an external algorithm. The populate operator has been defined on Hermes
  • 7. The Data world
    • Represents the entities to be analyzed, their properties and mutual relationship
    • Our context: trajectory data
    • Example:
    • TABLE Trajectories
    • ID : integer
    • Type : {vehicle, pedestrian}
    • Object : Moving_Point
  • 8. The Data World – Data filtering
    • SELECT t FROM Trajectories t WHERE t.type=“veichle”
    • SELECT count(t) FROM Trajectories t , Polluted a WHERE t.object intersects a.geometry
    • SELECT count(t) FROM Trajectories t , RushHours r WHERE t.object at_period r.period
    • SELECT count(t) FROM Trajectories t , Trajectories y WHERE t.object intersects y.object and y.id=3
  • 9. Model representation For T-Pattern, a Model_Tas is defined in Hermes as: Sequence of <Region, <Minimum travel time, Maximum travel time>> Model_TAS: VARRAY <SDO_Geometry, <TAU_TLL.interval, TAU_TLL.interval>> <A,<10,30>; B<5,60>; C<nd,nd>> A B c 10,30 5,60
  • 10. The Daedalus system DAEDALUS provides a Data Mining Query Language based on SQL, that includes basic mechanisms for interactive queries on D-World and M-World
  • 11. The Daedalus System Architecture HERMES DMQL query Model_TAS Package MOD Mediator Controller Parser Object Translator Mining Engine T-Pattern Algorithm User Interface TAS Translation Library Moving_point Translation Library Object Store
  • 12. Demo
    • We will show the Daedalus prototype
    • It has been developed in Java, based on Hermes and plugged with T-Pattern and clustering algorithms.
    • We will give some query examples to show the expressiveness of the language.
  • 13. Motivation
    • Which trajectories that satisfy cluster 1 also satisfy pattern 3?
    • SELECT r.id
    • FROM Patterns p,
    • (SELECT t.object FROM Clusters c, Trajectories t WHERE c.id = 1 AND t.object satisfies c.object) r
    • WHERE p.id = 3 AND r.object satisfies p.object