The WebLab platform - OW2 Consortium · The WebLab platform Prepared by Patrick GIROUX and Arnaud SAVAL EADS Defense and Security System Design Center, Val-de-Reuil, France ... blibli

Defence and Security

© EADS 2009 – All rights reservedPatrick GIROUX - EADS DS / SDFR1/IPCCPage 1

The WebLab platform

Prepared by Patrick GIROUX and Arnaud SAVAL EADS Defense and Security

System Design Center, Val-de-Reuil, France



Overview

• Who are we?– Our department in EADS

– Our activities

• The WebLab platform– Goals

– Principles

– Basic concepts

– Architecture

– Implementation examples

• Questions



IPCC at a glance

•Information Processing Control & Cognition

•Part of EADS Defense & Security (DS), System Design Centre (SDC)

•SDFR1/IPCC: Competence Centre specialised in Information Processing.

•Carries out R&T and R&D activities in the field of:– Multimedia mining: understanding of multi-media documents

(text, audio, image, video)– Data fusion: multi-sensor data fusion applied to surveillance

dedicated to Military & Civil domain.

•Size of the team: 21 people incl. 7 PhD research engineers

•Location: Val-de-Reuil, Normandy, 100 Km west of Paris



Media-mining

Context : vast amount of digital information in today’s media age (Internet, TV, radio, digital telephony, DVD, etc.).

Ever increasing amount of data available as digital content: :

– text

– audio

– image

– video

Objective : develop advanced semantics tools enabling the automatic or semi-automatic exploitation of unstructured data.



Media-mining as potential Intelligence targets

Public media such as Internet, written press, TV, radio, or CD-ROMs can provide significant information.

Different kinds of data: geopolitical, social, cultural, economic, environmental, etc.

Identification of important events: political, military, terrorist, criminal, etc.

Identification of networks,

Tracking the changes of a crisis,

International situations analysis,

Detection of weak signals (indices, alarms, etc.).



Information retrieval

Information acquisition

Information filtering

Information extraction

Synthesis & Alert

Visualisation

Media mining functions

@@Mastering the complete chain of information



Our competencies in media mining

Multi-disciplinary approach combining :• Statistical analysis• Linguistic analysis • Semantics analysis • Learning techniques

Best selection approach depending on the objective.

Free to choose any COTS.

Positioning as an integrator and expert • Integration of COTS or components developed by external laboratories• Developments of specific EADS components• Patents and scientific publications



What is WebLab ?

An integration platform

– based on recognised standards (SOA, Web Services, Semantic Web)

– allowing the integration of a selection of software components (search engine, information extraction, translation, knowledge management, graphical representation using maps/networks, etc.)

– allowing the interoperation of the selected components.

A set of media mining services for multi-media documents dedicated to technological/economical watch applications and OSINT applications.



An integration eased by the conformity to standards

An open platform willingly based on Web Services and Web Semantic standards which are recognised and

adopted standards by most all software editors.

URI UTF-8

XML Namespaces

XML Schema XPath XQuery RDF

RDF SchemaWSDL

SOAP

OWLBPEL

SOA JBI ESBPortal/Portlets

JSR168

SPARQL



An “open source” technical foundation

WebLab platform includes an open source technicalfoundation called WebLab Core

http://www.weblab-project.org

•developed by EADS and used by more than 30 partners from France and Europe:•used in several projects in various application domains (WebContent, Vitalas, eWokHub & others … ). •recently chosen for new projects and proposals (Virtuoso, SAIMSI, etc.) • allows to manage all the WebLab Services resulting from variouscomponent integration.



The WebLab Platform



The WebLab Logical Architecture

Access

Process

Services

Components

Data

ServiceBus

Messaging & Distribution

AcquisitionComponents

<<component>>

OrchestrationEngine

BusinessApplications

PortalBusiness Process

Editor

Mon

itoring &

Supervision

Security &

QoS

Repository

TechnicalServices

Other Services (evaluation)

AcquisitionServices

ProcessingServices

ProcessingComponents

<<component>>Diffusion

Components

<<component>>Technical

Components

<<component>>

OtherComponents

<<component>>

DiffusionServices

Repository

Infrastructure



Basic principle of the WebLab

A service •process a document or a part of a document•is independant and shall not invoke other services•can enrich the document with new information that will be exploited by the other services (processing chain).

<<service>>WebCrawling

<resource … document"><annotation uri= …><data …><rdf:RDF><dc:source … ><dc:title … ><dc:author …>

</rdf:RDF></data></annotation>

source>

<resource … document"> <annotation uri= …><data …><rdf:RDF><dc:source … ><dc:title … ><dc:author … >

</rdf:RDF></data></annotation><mediaUnit … text>blablablibliediaUnit >ource>

<<service>>Normalisation

<<Service>>Segmentation

doc.pdf

blablabla


</rdf:RDF></data></annotation><mediaUnit … composedUnit>

<mediaUnit … text>blabla

</mediaUnit><mediaUnit … text>

blibli/mediaUnit>ediaUnit >ource>




source>






doc.pdf

Blablibli

blabla









source>






doc.pdf

blablabla









source>






doc.pdf

Blablibli

blabla








Annotation system

<rdf:RDFxmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"xmlns:dc="http://purl.org/dc/elements/1.1/"xmlns="http://my/name/space/"><item rdf:about=« file://webConten/paper"><dc:date>30-11-2008</dc:date><dc:title>Warehousing Web Resources with the WebContent Platform</dc:title><dc:language>en</dc:language><dc:publisher>WWW2009</dc:publisher><dc:type>Research paper</dc:type><dc:format>.pdf</dc:format></item></rdf:RDF>

SeparationSeparation betweenbetween contents andcontents andannotationsannotations



Annotation systemAnnotation system

SplittingSplitting a document in mediaa document in media--unitsunits



Modeling objects used by media-miningservices

Document

1

1..*

ComposedUnit

MediaUnit

Text BinaryMediaUnit

Video AudioImage

Resource Annotation1 0..*

PieceOfKnowledge



The WebLab exchange model

Resource

+uri: URI

MediaUnit

Service

Document

ComposedUnit

+synchronised: boolean

1

1..*

Text

<<optional>>+content: String

Segment

1

*

VideoAudio Image

Ontology

Query

ResourceCollection

*

BinaryMediaUnit

<<optional>>+content: Binary

User

Annotation

1

0..*

LinearSegment

+start: int+end: int

SpatialSegment

Coordinate

+x: int+y: int

2..*

LowLevelDescriptor

+key: StringTemporalSegment

+start: int+end: int

BinaryContent

+data: Binary

TextContent

+data: String

Content

+offset: int+size: int

UsageContext

0..*

ComposedQuery

+boolOperator: {AND,OR,NOT}

1..*

SimilarityQuery

1..*

StringQuery

+request: String

Feature

<<optional>>+label: String+value: List <any>

1..*

PieceOfKnowledge

data: RDF/XML

ResultSet0..*

0..1

ElementaryQuery

weight: float = 1.0



Classification of WebLab services independentfrom any COTS (in French)

Acquisition<<service>>

Normalisation<<service>>

Epuration<<service>>

Pré-traitement<<service>>

Reconnaissancede l'écriture

<<service>>

Transcriptionaudio

<<service>>

Classification<<service>>

Extractiond'information

<<service>>

Résumé<<service>>

Traduction<<service>>

Indexationet

recherche

<<service>>

Alerte<<service>>

Service Métier<<service>>

Acquisitiondes

données duWeb

<<service>>Acquisition

desdonnéespapier

<<service>>

Acquisition desdonnées télé

ouradio-diffusées

<<service>>

Normalisationdu texte

<<service>>

Normalisationde l'audio

<<service>>

Normalisationde la vidéo


de l'image

<<service>>

Epurationdu texte

<<service>>

Epurationde l'audio

<<service>>

Epurationde l'image

<<service>>

Epurationde la vidéo

<<service>>

Prétraitementdu texte

<<service>>

Prétraitementde l'audio

<<service>>

Prétraitementde la vidéo

<<service>>

Reconnaissanced’écriture

dactylographiée

<<service>>Reconnaissance

d’écrituremanuscrite

<<service>>

Classificationdes données

textuelles

<<service>>Classificationdes données

images

<<service>>

Extractiond’information

dans lesdonnées

textuelles

<<service>>


dans desdonnéesimages

<<service>>


dans desdonnées

audio

<<service>>

Résumé detexte

<<service>>Résumé

vidéo

<<service>>

Requêtestextuelles

et surannotations

<<service>>Requêtes surles images etmultimodales

<<service>>



Example of WebLab’isation of COTS (in French)


<<service>>

Extraction d’informationdans les données

textuelles

<<service>>

+definirModele()+extraireEntités()+extraireRelations()

Extractiond’information dans

des données images

<<service>>

+reconnaitreTexte()+reconnaitreVisage()+reconnaitreForme()

Kim, Jeongil

Kim, Keehyun Kum

Lee

Leen

Lim bae

Jung, Kim

ikona


<<service>>

Extraction d’informationdans les données

textuelles

<<service>>

+definirModele()+extraireEntités()+extraireRelations()

Extractiond’information dans

des données images

<<service>>

+reconnaitreTexte()+reconnaitreVisage()+reconnaitreForme()

Kim, Jeongil

Kim, Keehyun Kum

Lee

Leen

Lim bae

Jung, Kim

ikonaikona

Classificationdes données

images

<<service>>Classificationdes données

images

<<service>>


+configurer()+collecter()

Acquisition desdonnées du Web

<<service>>Acquisition desdonnées télé ouradio-diffusées

<<service>>

+enregistrer()

Lee, Minkyu

Lim, Heejin

Jung, Yoontae Kim, Hyunsoo


+configurer()+collecter()

Acquisition desdonnées du Web

<<service>>Acquisition desdonnées télé ouradio-diffusées

<<service>>

+enregistrer()

Lee, Minkyu

Lim, Heejin

Jung, Yoontae Kim, Hyunsoo



Component already integrated as WebLab services

• Exalead• Sinequa• Pertimm• Temis – Luxid• Nstein - TME• Mondeca - ITM• SailLabs• Systran• Analyst’s NoteBook / I Base• Digimind• Autonomy • IMEDIA • …• HTTrack• MythTV• Tyka• Apache- Lucene Solr• GATE• Google Map• INRIA Edelweiss – Corese• Prefuse• …

And many more to come



WebLab services

Non-exhaustive list of services available in the WebLab platform

•Data acquisition (Web, data bases, folders)•Normalisation of textual content•Language identification (> 30 languages)•Speech to text transcription•Manual annotation and cotation•Named entities extraction •Semantics analysis and relation extraction•Thematic categorization and clustering•Automatic summarisation•Indexing•Full Text Search (keywords, annotation, boolean, etc.)•Semantics search•Information mapping



Generic interfaces for services

Analyser<<interface>>

+process(uc: UsageContext, res: Resource): Resource

Configurable<<interface>>

+configure(uc: UsageContext, configuration: PieceOfKnowledge)+resetConfiguration(uc: UsageContext)

Trainable<<interface>>

+addTrainResource(uc: UsageContext, res: Resource)+train(uc: UsageContext)+resetTrainedModel(uc: UsageContext)

ContentProvider<<interface>>

+getContent(contentId: URI, offset: int, limit: int): Content

ContentConsumer<<interface>>

+setContent(content: Content): URI

ResourceContainer<<interface>>

+saveResource(uc: UsageContext, res: Resource): URI+getResource(uc: UsageContext, resourceId: URI): Resource

ReportProvider<<interface>>

+addInformation(uc: UsageContext, res: Resource)+buildReport(uc: UsageContext): Resource

Indexer<<interface>>

+index(uc: UsageContext, res: Resource)

Generic Interface<<interface>>

Searcher<<interface>>

search(uc: UsageContext, q: Query, offset: int, limit: int): ResultSet

SourceReader<<interface>>

getResource(uc: UsageContext, offset: int, limit: int): ResourceCollection



An example of a processing chain: from TV to annotations

Videosegmentation

Audiotranscription

iran trying to established new facts on the ground there's a couple different timelines even mind that the time line of most intense discussions how long before iran is able to produce enough highly enriched uranium for a nuclear weapon

VIDEO AUDIO VOCAL AUDIO

TEXTANNOTATED TEXTiran trying to established new facts

on the ground there's a couple different timelines even mind that the time line of most intense discussions how long before iran is able toproduce enough enriched uraniumfor a nuclear weapon

Audiorefinement

Information extraction



Architecture VITALAS



Using portlet technology to build specificapplication from generic HCI modules

A A WebLabWebLab application application cancan bebe

implementedimplemented by by

assemblingassembling//orchestratingorchestrating a set a set

of of existingexisting portletsportlets..

A Portlet is

– Composable in a page– Integrable in an application– Displayable as an information

block– Normalised



Example of WebLab interface using portlet technology



Thanks for your attention …

Questions ?

Demo application: http://forge.ow2.org/projects/weblab

Contacts: [email protected]@eads.com

Documents

The WebLab platform - OW2 Consortium · The WebLab platform Prepared by Patrick GIROUX and Arnaud SAVAL EADS Defense and Security System Design Center, Val-de-Reuil, France ... blibli