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.

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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.