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Openings in Knowledge Engineering

PhD Position: Knowledge Extraction for the Internet of Things

The aim of the SPIRIT project is to investigate the Proof-of Concept of employing novel secure and privacy-ensuring techniques in services set-up in the Internet of Things (IoT) environment, aiming to increase the trust of users in IoT-based systems. The proposed system will address distinct issues related to security and privacy, hence, overcoming the lack of user confidence, which inhibits utilisation of IoT technology.

One of the key points of the project is to study the notion of Semantic firewall. A semantic firewall must be able to allow or deny the transmission of data derived from an IoT device according to the information contained within the data and the information gathered about the requester, hence ensuring that access to such data is governed by the access permissions commensurate with the requester.

The PhD student will work on the Data Analysis and Semantic Extraction work package, within the Knowledge engineering team (KE@ISS) of the University of Geneva's Center for computing (CUI)

This step consists in applying information extraction (IE) techniques to attach semantics to the analysed raw data coming from IoT objects, and to produce semantic descriptors (attribute-value pairs) that are needed by the semantic firewall. The analysed raw data are (scanned) images, digital sound recording, measurements (collected by sensors), etc., accompanied by first level analysis results (document layout, component tags, extracted texts, …) Each category of raw data may in turn represent different types of content. For instance, an IoT scanned document may be a national ID card, a payslip, a medical record, etc. The aim of this WP is to devise an information extraction technique that 1) recognizes the type of content represented in the raw data and 2) adapts to the content type and utilizes background knowledge (eg. an ontology of content types) to efficiently extract the information that characterize it’s content (specific attribute values such id card number, account number, product name, …) It will be based on a combination of techniques from the fields of information extraction and knowledge representation.

Required qualifications

  • Master in Computer Science or Information Systems or Computational Linguistics
  • Motivation, creativity, and independence, to solve complex biological problems
  • Excellent communication skills (to work in an international team)

Starting date: 1 January 2017 or later

Deadline for applications 15 November 2016