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Department: Any ÅAU / Department of Information Technologies UTU / Department of Information Technology UTU / Department of Mathematics and Statistics UTU / Turku School of Economics, Institute of Information Systems Sciences

Research Unit: Any Algorithmics and Computational Intelligence Group (ACI) Biomathematics Research Unit (BIOMATH) Communication Systems (ComSys) Computational Biomodeling Laboratory (Combio Lab) Data Mining and Knowledge Management Laboratory Distributed Systems Laboratory (DS Lab) Embedded Computer and Electronic Systems (ECES) Embedded Systems Laboratory (ESLAB) FUNDIM, Fundamentals of Computing and Discrete Mathematics Institute for Advanced Management Systems Research (IAMSR) Learning and Reasoning Lab Software Construction Laboratorium Software Development Laboratory (SwDev) Software Engineering Laboratory (SE Lab) Turku BioNLP Group Turku Optimization Group (TOpGroup) UTU Information Systems Science (ISS)

Publication type: Any Monographs Edited books Edited special issues of journals Edited proceedings Articles in journals Articles in proceedings Chapters in edited books Ph.D. thesis Lic. thesis Technical reports

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Articles in journals (2):

• Samuel Rönnqvist, Peter Sarlin, Bank Distress in the News: Describing Events Through Deep Learning. Neurocomputing 264, 57–70, 2017.
• Samuel Rönnqvist, Peter Sarlin, Bank Networks from Text: Interrelations, Centrality and Determinants. Quantitative Finance 15(10), 1619–1635, 2015.

Articles in proceedings (10):

• Samuel Rönnqvist, Niko Schenk, Christian Chiarcos, A Recurrent Neural Model with Attention for the Recognition of Chinese Implicit Discourse Relations. In: Regina Barzilay, Min-Yen Kan (Eds.), Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2, 256–262, Association for Computational Linguistics, 2017.
• Niko Schenk, Christian Chiarcos, Kathrin Donandt, Samuel Rönnqvist, Evgeny A. Stepanov, Giuseppe Riccardi, Do We Really Need All Those Rich Linguistic Features? A Neural Network-Based Approach to Implicit Sense Labeling. In: Nianwen Xue, Hwee Tou Ng, Sameer Pradhan, Attapol Rutherford, Bonnie Webber, Chuan Wang, Hongmin Wang (Eds.), Proceedings of the CoNLL-16 shared task, 41–49, Association for Computational Linguistics, 2016.
• Samuel Rönnqvist, Exploratory Topic Modeling with Distributional Semantics. In: Elisa Fromont, Tijl De Bie, Matthijs van Leeuwen (Eds.), Advances in Intelligent Data Analysis XIV, 241–252, Springer, 2015.
• Samuel Rönnqvist, Peter Sarlin, Detect & Describe: Deep Learning of Bank Stress in the News. In: 2015 IEEE Symposium Series on Computational Intelligence, 890–897, IEEE, 2015.
• Samuel Rönnqvist, Peter Sarlin, Identifying Bank Stress by Deep Learning of News. In: Barbara Hammer, Thomas Martinetz, Thomas Villmann (Eds.), Machine Learning Reports 02/2015, Machine Learning Reports 3, 112–113, Bielefeld University, 2015.
• Samuel Rönnqvist, Peter Sarlin, Alluvial SOTM: Visualizing Transitions and Changes in Cluster Structure of the Self-Organizing Time Map. In: Robert S Laramee, Min Chen (Eds.), The Eurographics Conference on Visualization (EuroVis), Eurographics, 2014.
• Samuel Rönnqvist, Peter Sarlin, From Text to Bank Interrelation Maps. In: Antoaneta Serguieva, Dietmar Maringer, Vasile Palade, Rui Jorge Almeida (Eds.), 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), 48–54, IEEE, 2014.
• Samuel Rönnqvist, Xiaolu Wang, Peter Sarlin, Interactive Visual Exploration of Topic Models Using Graphs. In: Robert S Laramee, Min Chen (Eds.), The Eurographics Conference on Visualization (EuroVis), Eurographics, 2014.
• Annika Holmbom, Samuel Rönnqvist, Peter Sarlin, Tomas Eklund, Barbro Back, Green vs. Non-Green Customer Behavior: A Self-Organizing Time Map Over Greenness. In: Wei Ding, Takashi Washio (Eds.), IEEE 13th International Conference on Data Mining Workshops, IEEE International Conference on Data Mining, 1–7, IEEE, 2013.
• Peter Sarlin, Samuel Rönnqvist, Cluster Coloring of the Self-Organizing Map: An Information Visualization Perspective. In: Proceedings of the International Conference on Information Visualization, 532–538, IEEE, 2013.

Ph.D. thesis (1):

• Samuel Rönnqvist, Knowledge-Lean Text Mining. TUCS Dissertations 227. Åbo Akademi University, 2017.