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2020 – today
- 2023
[j8]Hans-Christian Schmitz
, Bernhard Lutz, Dominik Wolff, Dirk Neumann:
When machines trade on corporate disclosures: Using text analytics for investment strategies. Decis. Support Syst. 165: 113892 (2023)- [j7]Katharina Baur, Markus Rosenfelder, Bernhard Lutz:
Automated real estate valuation with machine learning models using property descriptions. Expert Syst. Appl. 213(Part): 119147 (2023) - 2022
- [j6]Janis Brammer, Bernhard Lutz, Dirk Neumann:
Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning. Eur. J. Oper. Res. 299(1): 75-86 (2022) - [j5]Janis Brammer, Bernhard Lutz, Dirk Neumann:
Stochastic mixed model sequencing with multiple stations using reinforcement learning and probability quantiles. OR Spectr. 44(1): 29-56 (2022) - 2021
- [j4]Janis Brammer, Bernhard Lutz, Dirk Neumann:
Solving the mixed model sequencing problem with reinforcement learning and metaheuristics. Comput. Ind. Eng. 162: 107704 (2021) - 2020
- [j3]Simon Albrecht, Bernhard Lutz, Dirk Neumann:
The behavior of blockchain ventures on Twitter as a determinant for funding success. Electron. Mark. 30(2): 241-257 (2020) - [j2]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
Predicting sentence-level polarity labels of financial news using abnormal stock returns. Expert Syst. Appl. 148: 113223 (2020) - [j1]Nicolas Pröllochs, Stefan Feuerriegel, Bernhard Lutz, Dirk Neumann:
Negation scope detection for sentiment analysis: A reinforcement learning framework for replicating human interpretations. Inf. Sci. 536: 205-221 (2020)
2010 – 2019
- 2019
- [c6]Simon Albrecht, Bernhard Lutz, Dirk Neumann:
How Sentiment Impacts the Success of Blockchain Startups - An Analysis of Social Media Data and Initial Coin Offerings. HICSS 2019: 1-10 - [c5]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
Sentence-Level Sentiment Analysis of Financial News Using Distributed Text Representations and Multi-Instance Learning. HICSS 2019: 1-10 - [c4]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
The Longer the Better? The Interplay Between Review Length and Line of Argumentation in Online Consumer Reviews. ICIS 2019 - [i3]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
Sentence-Level Sentiment Analysis of Financial News Using Distributed Text Representations and Multi-Instance Learning. CoRR abs/1901.00400 (2019) - [i2]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
The Longer the Better? The Interplay Between Review Length and Line of Argumentation in Online Consumer Reviews. CoRR abs/1909.05192 (2019) - 2018
- [c3]Raymond Chiong, Zongwen Fan, Zhongyi Hu, Marc T. P. Adam, Bernhard Lutz, Dirk Neumann:
A sentiment analysis-based machine learning approach for financial market prediction via news disclosures. GECCO (Companion) 2018: 278-279 - [c2]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
Understanding the Role of Two-Sided Argumentation in Online Consumer Reviews: A Language-Based Perspective. ICIS 2018 - [i1]Bernhard Lutz, Nicolas Pröllochs, Dirk Neumann:
Understanding the Role of Two-Sided Argumentation in Online Consumer Reviews: A Language-Based Perspective. CoRR abs/1810.10942 (2018) - 2016
- [c1]Peter M. Fischer, Io Taxidou, Bernhard Lutz, Michael Huber:
Distributed streaming reconstruction of information diffusion: poster. DEBS 2016: 368-371
Coauthor Index
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