32 citations · 50 across the 7 of their papers we have counts for
4 papers · 1 filter
FrameFinder: Explorative Multi-Perspective Framing Extraction from News Headlines
Markus Reiter-Haas, Beate Klösch, Markus Hadler +1
Revealing the framing of news articles is an important yet neglected task in information seeking and retrieval. In the present work, we present FrameFinder, an open tool for extrac…
Predicting Music Relistening Behavior Using the ACT-R Framework
Markus Reiter-Haas, Emilia Parada-Cabaleiro, Markus Schedl +3
Providing suitable recommendations is of vital importance to improve the user satisfaction of music recommender systems. Here, users often listen to the same track repeatedly and a…
Should we Embed? A Study on the Online Performance of Utilizing Embeddings for Real-Time Job Recommendations
Markus Reiter-Haas, Emanuel Lacic, Tomislav Duricic +2
In this work, we present the findings of an online study, where we explore the impact of utilizing embeddings to recommend job postings under real-time constraints. On the Austrian…
Beyond Accuracy Optimization: On the Value of Item Embeddings for Student Job Recommendations
Emanuel Lacic, Dominik Kowald, Markus Reiter-Haas +2
In this work, we address the problem of recommending jobs to university students. For this, we explore the utilization of neural item embeddings for the task of content-based recom…