Date post: | 24-May-2015 |
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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
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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
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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
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The Two Worlds framework
Filtering operators: manipulate basic objects.
Mining operators: extract properties from samples. K:DM
Population operators: detect samples exhibiting properties. P:DxMD
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From Two Worlds to DaedalusHermes 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
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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
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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
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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
10,305,60
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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
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The Daedalus System Architecture
HERMES
Model_TASPackage
MODMediator
Controller
Parser
ObjectTranslator
MiningEngine
T-PatternAlgorithm
User Interface
TASTranslation
Library
Moving_pointTranslation
Library
ObjectStore
DMQL query
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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.