ERCIM News 112
January 2018
Special theme Quantum Computing
Guest editors Jop Briët (CWI) and Simon Perdrix (CNRS, LORIA)
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- Category: Research and Innovation
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by Diego Marcheggiani (University of Amsterdam) and Fabrizio Sebastiani (CNR)
In a joint effort between the University of Amsterdam and ISTI-CNR, researchers have studied the negative impact that low-quality training data (i.e., training data annotated by non-authoritative assessors) has on information extraction (IE) accuracy.
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by Tim Baarslag (CWI)
Computers that negotiate on behalf of humans hold great promise for the future and will even become indispensable in emerging application domains such as the smart grid, autonomous driving, and the Internet of Things. An important obstacle is that in many real-life settings, it is impossible to elicit all information necessary to be sensitive to the individual needs and requirements of users. This makes it a lot more challenging for the computer to decide on the right negotiation strategy; however, new methods are being created at CWI that make considerable progress towards solving this problem.
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by Kubilay Atasu, Vasileios Vasileiadis, Michail Vlachos (IBM Research – Zurich)
A significant portion of today’s data exists in a textual format: web pages, news articles, financial reports, documents, spreadsheets, etc. Searching across this collected text knowledge requires two essential components: a) A measure to quantify what is considered ‘similar’, to discover documents relevant to the users’ queries, b) A method for executing in real-time the similarity measure across millions of documents.
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- Category: Research and Innovation
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by Alessia Amelio (University of Calabria), Darko Brodić, Sanja Petrovska (University of Belgrade), Radmila Janković (Serbian Academy of Sciences and Arts)
“CAPTCHA Samples” is a new website for testing different types of CAPTCHA specifically designed for research and study purposes.
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- Category: Research and Innovation
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by Elisjana Ymeralli, Theodore Patkos and Yannis Roussakis (ICS-FORTH)
APOPSIS is a web-based platform that aims to motivate online users to participate in well-structured dialogues by raising issues and posting ideas or comments, related to goal-oriented topics of discussion. The primary goal of the system is to offer automated opinion analysis features that help identify useful patterns of relations amongst participants and their expressed opinions. Our system is designed to enable more structured and less confusing argumentative discussions, thus helping sense-makers in understanding the dynamic flow of the dialogue.
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by Katharina Holzinger (SBA Research), Klaus Mak, (Austrian Army) Peter Kieseberg (St. Pölten University of Applied Sciences), Andreas Holzinger (Medical University Graz, Austria)
Machine learning has yielded impressive results over the last decade, but one important question that remains to be answered is: How can we explain these processes and algorithms in order to make the results applicable as proof in court?
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- Category: Research and Innovation
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by Maurice ter Beek, Alessandro Fantechi, Alessio Ferrari, Stefania Gnesi (ISTI-CNR, Italy), and Riccardo Scopigno (ISMB, Italy)
Researchers from the Formal Methods and Tools group of ISTI-CNR are working on a review and assessment of the main formal modelling and verification languages and tools used in the railway domain, with the aim of evaluating the actual applicability of the most promising ones to a moving block signalling system model provided by an industrial partner. The research is being conducted in the context of the H2020 Shift2Rail project ASTRail.