Home of Data - Databases and Information Systems

We are a subdivision of the Department of Computer Science at the University of Innsbruck.

 

Our passion lies in developing innovative methods for efficient data storage and analyses aiming to assist users and businesses to meet their information needs.

 

 

News

Paper accepted at 15th Sound and Music Computing Conference

Our paper "#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems", co-authored by Asmita Poddar (National Institute of Technology, Rourkela, India), Eva Zangerle (DBIS) and Yi-Hsuan Yang (Research Center for IT Innovation, Academia Sinica, Taiwan) has been accepted at this year's Sound and Music Computing Conference.


DBIS featured in Datenbank-Spektrum

Our research group is featured in the current issue of the Datenbank-Spektrum journal, which is the central outlet of the Fachgruppe Datenbanksysteme (working group for databases) of the German Informatics Society (GI). In this article, we present a short retrospective of the group's history and, more importantly, briefly present our research activities and accomplishments. You can find the article here.


DBIS@The Web Conference

It's a busy week for DBIS - Eva and Benjamin are presenting their work at The Web Conference in Lyon, France. 

Eva is presenting her paper "Recommendation-Assisted Data Curation for Wikidata" together with Claudia Müller-Birn of Freie Universität Berlin at the Wikipedia Workshop. Benjamin is presenting his paper "Detecting Music Genre Using Extreme Gradient Boosting" at the Challenges track, participating in the WWW 2018 Challenge: Learning to Recognize Musical Genre.


Paper and Poster @CICLing

Segmentation of Job AdsDBIS is represented twice on the 19th CICLing conference in Hanoi, Vietnam. On March 19th, Benjamin presented his paper "On the Influence of Machine Translation on Language Origin Obfuscation", which explains how the original language of translated documents can be detected. Later that day, Michaels work "Algorithmic Segmentation of Job Ads Using Textual Analysis" was presented as part of the poster session, yielding interesting discussions from many different fields.