Expected Impact

SME E-COMPASS Anti-Fraud

1) an expert system with multiple rules-of-thumb for assessing the riskiness of each transaction,

2) a variety of supervised learning models to be used for extracting patterns of fraudulent activity from the transaction database (DB),

3) anomaly detectors are well suited for online fraud monitoring, as they do not typically rely on experts to provide signatures for all possible types of fraud. Among the great range of candidate technologies, we particularly favour the application of hybrid (semi-supervised) novelty detectors, combining statistical techniques with computational intelligent models,

4) implementation  of an inference engine  to coordinate the risk assessment process and provide an aggregate suspiciousness score through which each transaction can be classified in predefined categories (normal, malicious, under review),

5) transaction analytics technologies that typically provide the fraud analyst with technical or geographical information about each transaction and thus supplement in many ways traditional background investigations on customer profiles.


SME E-COMPASS Data-Mining for e-Sales 

The fundamental idea behind the SME E-COMPASS online data mining services is to support small e‑shops in increasing their conversion rates from visitor to customer by improving the:

- understanding of the customers and their expectations/motivation,

- knowledge about competitors and their activities, especially concerning their prices and price trends,

- examination of potentials for improvements by analysing some selected information of both, customers and competitors,

- initiation of appropriate actions depending on the identification of certain patterns in the analysis results above-mentioned.

 

SME E-COMPASS Integration Framework

The higher integration task in the project is to develop a RDF repository which integrates all required data from different-format data sources and making them available to the services developed into the project (anti-fraud and data mining for e-sales). This RDF repository integrates all the required data using RDF as the data model

Pic3

Consortium

ASOCIACIÓN DE EMPRESARIOS TEXTILES DE LA COMUNIDAD VALENCIANA
http://www.atevalinforma.com/

EXUS
http://www.exus.co.uk

Fraunhofer IAO (FRA)-Germany
http://www.iao.fraunhofer.de

GAIA-ASOCIACIÓN DE INDUSTRIAS DE LAS TECNOLOGIAS ELECTRÓNICAS Y DE LA INFORMACIÓN DEL PAIS VASCO - SPAIN
http://www.gaia.es

E-TRAVEL SA (ETR)-Greece
http://www.e-travel.gr

Fornaro Business Agency OE (FBA)-Greece
http://www.fornaro.gr

MeetNow (MTN)-Germany
http://www.meetnow.eu

Halton Chamber of Commerce and Enterprise (HALTON) – UK
http://www.haltonchamber.co.uk

Centro de Investigación Cooperativa en Turismo (CIC)-Spain
http://www.tourgune.org

Estudio Cero Soluciones Informaticas S.L. (CERO)-Spain
http://www.e0web.com

Korinthos Chamber of Commerce (EPK)-Greece
http://www.korinthcc.gr

University of Malaga (UMA)-Spain
http://www.uma.es
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