Search Results for author: Daniel Keim

Found 9 papers, 1 papers with code

Is that really a question? Going beyond factoid questions in NLP

1 code implementation IWCS (ACL) 2021 Aikaterini-Lida Kalouli, Rebecca Kehlbeck, Rita Sevastjanova, Oliver Deussen, Daniel Keim, Miriam Butt

Research in NLP has mainly focused on factoid questions, with the goal of finding quick and reliable ways of matching a query to an answer.

A Comparative Analysis of Industry Human-AI Interaction Guidelines

no code implementations22 Oct 2020 Austin P. Wright, Zijie J. Wang, Haekyu Park, Grace Guo, Fabian Sperrle, Mennatallah El-Assady, Alex Endert, Daniel Keim, Duen Horng Chau

We have then used this framework to compare each of the surveyed companies to find differences in areas of emphasis.

Human-Computer Interaction

Should We Trust (X)AI? Design Dimensions for Structured Experimental Evaluations

no code implementations14 Sep 2020 Fabian Sperrle, Mennatallah El-Assady, Grace Guo, Duen Horng Chau, Alex Endert, Daniel Keim

This paper systematically derives design dimensions for the structured evaluation of explainable artificial intelligence (XAI) approaches.

Explainable artificial intelligence

Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections

no code implementations1 Aug 2019 Mennatallah El-Assady, Rebecca Kehlbeck, Christopher Collins, Daniel Keim, Oliver Deussen

We present a framework that allows users to incorporate the semantics of their domain knowledge for topic model refinement while remaining model-agnostic.

Decision Making

Visual Integration of Data and Model Space in Ensemble Learning

no code implementations19 Oct 2017 Bruno Schneider, Dominik Jäckle, Florian Stoffel, Alexandra Diehl, Johannes Fuchs, Daniel Keim

Ensembles of classifier models typically deliver superior performance and can outperform single classifier models given a dataset and classification task at hand.

Classification Ensemble Learning +1

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