most citedDeep learning for affective computing: text-based emotion recognition in decision support

352 citations · 489 across the 4 of their papers we have counts for

collaborators

5 papers

q-fin.TR2018★ 93 cited

News-based trading strategies

Stefan Feuerriegel, Helmut Prendinger

The marvel of markets lies in the fact that dispersed information is instantaneously processed and used to adjust the price of goods, services and assets. Financial markets are par…

cs.CL2018

IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets

Edison Marrese-Taylor, Suzana Ilic, Jorge A. Balazs +2

In this paper we introduce our system for the task of Irony detection in English tweets, a part of SemEval 2018. We propose representation learning approach that relies on a multi-…

cs.CL2018★ 31 cited

Putting Question-Answering Systems into Practice: Transfer Learning for Efficient Domain Customization

Bernhard Kratzwald, Stefan Feuerriegel

Traditional information retrieval (such as that offered by web search engines) impedes users with information overload from extensive result pages and the need to manually locate t…

cs.CL2018★ 352 cited

Deep learning for affective computing: text-based emotion recognition in decision support

Bernhard Kratzwald, Suzana Ilic, Mathias Kraus +2

Emotions widely affect human decision-making. This fact is taken into account by affective computing with the goal of tailoring decision support to the emotional states of individu…

cs.CV2017★ 13 cited

Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection

Mohammadamin Barekatain, Miquel Martí, Hsueh-Fu Shih +4

Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios. We pres…