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Introducing CAPER, a Collaborative Platform for Open and Closed Information Acquisition, Processing and Linking

The goal of CAPER is to create a common platform for the prevention of organised crime through sharing, exploitation and linking of Open and Closed information sources. CAPER will support collaborative multilingual analysis of audiovisual content and biometrics information, based on Visual Analytics and Text Mining technologies. CAPER will permit Law Enforcement Agencies (LEAs) to share informational, investigative and experiential knowledge. The paper will detail the CAPER platform elements: Open and Closed Data Sources: TV, Radio, and Information in closed legacy systems are the data sources to be mined and evaluated by CAPER, in addition to Open Internet data sources, and Semantic Web data collections.

Data Acquisition: Depending on the information source type, different acquisition patterns will be applied to ensure acquired information is the richest possible and has a suitable format for analysis.

Information Analysis: Each analysis module is geared towards a specific content type, i.e. Text, Image, Video, Audio and Speech or Biometric data. These modules interact with the ‘Semantic mash-up’ component, to link Semantic Web data.

Information and Reference Repositories: source data and mined information will be stored in these repositories, separated by content type. Repositories will also store the reference images, text, keywords, biometric data etc. of interest to the LEAs,

Interoperability and Management Application: This is the end users’ workbench., built on a web based collaborative platform. It will allow LEAs to create and configure their monitoring requests and analysis petitions.

Visual Analytics (VA) and Data Mining (DM): VA and DM will provide the intelligence necessary to support the output of the system. They will allow LEAs to effectively mine processed data both from Closed and Open information sources, and to further relate it to Semantic Web sources when required.


14th International Conference on Human - Computer Interaction (HCI 2011), Orlando, 2011

Autori esterni: Carlo Aliprandi (Synthema)
Autori IIT:

Tipo: Articoli su riviste ISI
Area di disciplina: Information Technology and Communication Systems

Attività: Social and Semantic Web
Web of Data