Ruijie implemented NLQxform, a question-answering system to answer natural language questions on scholarly knowledge graphs. The system integrates a fine-tuned transformed-based BART model to translate natural language questions to SPARQL queries. Check out the NLQxform poster for more information!

In his Bachelor Thesis, Viktor Lakic investigated the decay happening in datasets when the resources that Web-URLs point to become unavailable. This Link-Rot can cause problems for reproducibility, as datasets can shrink over time, potentially changing the outcome of experiments which use them. A paper based on the data that Viktor collected in his thesis, co-authored by Luca Rossetto and Abraham Bernstein, was recently presented at the 2023 International Conference on Multimedia Modeling in the Special Session on ‘Multimedia Datasets for Repeatable Experimentation’. The paper was awarded the ‘Best Special Session Paper Award’, honoring the best contribution across all special sessions of the conference. Congratulations!

In order to facilitate and coordinate this evaluation campaign, we implemented a Web-based software infrastructure – dubbed Alan’s Speakeasy – that provides a graphical interface for human users to connect and have conversations in chatrooms and allows students to connect their conversational agents. Speakeasy also allows students to evaluate the conversational agents they talk to, using a survey that asks users to assess the accuracy of the conversational agents.   

We are honored to have been granted new funding by the UZH Teaching Fund via the innovation program that will allow us to extend the scope of Speakeasy. This project has a two-fold goal: Firstly, we would like to extend the implementation of the current software infrastructure – Speakeasy – to incorporate further features that will make the software more usable and more elaborate for running evaluation campaigns for conversational agents within the ATAI class.  Secondly, we would like to expand the scope of our software to reach a larger audience. Specifically, we would like to make our software useful for other organizations. We would like other research groups working on various aspects of AI (inside and outside UZH) to be able to reuse our software for teaching practical aspects of AI. 

On Tuesday, June 3, UZH Professor Abraham Bernstein and his former PhD student Prof. Katharina Reinecke (now at the University of Michigan) were awarded the European Research Paper of the Year Award  of 2014.

As the Web Site States:

The CIONET European Research Paper of the Year Election identifies the European research paper that embodies most excellence in both rigour and relevance of research. In order to promote the exchange of ideas, experiences and knowledge among professionals and academics in the area of information and communications systems and technology management, the CIONET European Research Paper of the Year acclaims a yearly best research paper.

The paper was chosen from the 28 papers published by European authors in either MISQ or ISR — the two top journals in information systems — which ensures that only top-rated research studies qualify. What makes the award especially remarkable is that the jury is entirely composed of CIOs. Hence, the award goes to a top research paper that has a profound practical impact.

This year’s jury comprised the following highly regarded CIOs: Carsten Trapp (SICK AG), Manuel Fischer (Amazon Europe), Edwin Erckens (Teva Pharmaceuticals Europe), Jean-Claude Blaimont (McCain Foods), Roberto Parra (CIONET Spain), Jorge Coelho (Portuguese Institute of Process Business Management), Frédéric Charles (Lyonnaise des Eaux/Suez Environnement), and Gerry Pennell (London Organising Committee for the Olympic and Paralympic Games) .

The paper called “Knowing What a User Likes: A Design Science Approach to Interfaces that Automatically Adapt to Culture” published in MISQ (PDF here) presents a method for automatically adapting to cultural differences between users. A brief interview with an explanation is available at o Youtube.

The award was announced at the CIOCITY annual convention of the European CIO association CIONET, which has roughly 4200 CIOs as members.

Full citation of the paper: Reinecke, Katharina and Bernstein, Abraham. 2013. “Knowing What a User Likes: A Design Science Approach to Interfaces that Automatically Adapt to Culture,” MIS Quarterly, (37: 2) pp.427-453.