Publications
2024
Analyzing the Use of Metaphors in News Editorials for Political Framing
M. Sengupta, R. El Baff, M. Alshomary, H. Wachsmuth, in: K. Duh, H. Gomez, S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Association for Computational Linguistics, Mexico City, Mexico, 2024, pp. 3621–3631.
Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
M. Spliethöver, S.N. Menon, H. Wachsmuth, in: L.-W. Ku, A. Martins, V. Srikumar (Eds.), Findings of the Association for Computational Linguistics: ACL 2024, Association for Computational Linguistics, Bangkok, Thailand, 2024, pp. 9294–9313.
Modeling the Quality of Dialogical Explanations
M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, H. Wachsmuth, in: N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, Torino, Italia, 2024, pp. 11523–11536.
2023
Conclusion-based Counter-Argument Generation
M. Alshomary, H. Wachsmuth, in: A. Vlachos, I. Augenstein (Eds.), Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, Dubrovnik, Croatia, 2023, pp. 957–967.
Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation
F.S. Bäumer, W.-F. Chen, M. Geierhos, J. Kersting, H. Wachsmuth, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 65–84.
Identifying Feedback Types to Augment Feedback Comment Generation
M. Stahl, H. Wachsmuth, in: Proceedings of the 16th International Natural Language Generation Conference, n.d.
Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms
M. Sengupta, M. Alshomary, I. Scharlau, H. Wachsmuth, in: H. Bouamor, J. Pino, K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023, Association for Computational Linguistics, Singapore, 2023, pp. 4636–4659.
On-The-Fly Computing -- Individualized IT-services in dynamic markets
C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim, On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023.
2022
"Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain
H. Wachsmuth, M. Alshomary, in: Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 344–354.
“Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations
H. Wachsmuth, M. Alshomary, in: N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T.K. Lee, E. Santus, F. Bond, S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 344–354.
Analyzing Culture-Specific Argument Structures in Learner Essays
W.-F. Chen, M.-H. Chen, G. Mudgal, H. Wachsmuth, in: Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022), 2022, pp. 51–61.
Argument Novelty and Validity Assessment via Multitask and Transfer Learning
M. Alshomary, M. Stahl, in: Proceedings of the 9th Workshop on Argument Mining, International Conference on Computational Linguistics, Online and in Gyeongju, Republic of Korea, 2022, pp. 111–114.
Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning
M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.
Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks
J. Palushi, Domain-Aware Text Professionalization Using Sequence-to-Sequence Neural Networks, 2022.
Generating Contrastive Snippets for Argument Search
M. Alshomary, J. Rieskamp, H. Wachsmuth, in: Proceedings of the 9th International Conference on Computational Models of Argument, 2022, pp. 21–31.
Identifying the Human Values behind Arguments
J. Kiesel, M. Alshomary, N. Handke, X. Cai, H. Wachsmuth, B. Stein, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022, pp. 4459–4471.
Investigating the argumentation structures of EFL learners from diverse language backgrounds
M.-H. Chen, G. Mudgal, W.-F. Chen, H. Wachsmuth, in: EUROCALL, 2022.
Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing
M. Ahmed, Knowledge Base Enhanced & User-Centric Dialogue Design for OTF Computing, 2022.
No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media
M. Spliethöver, M. Keiff, H. Wachsmuth, in: Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Association for Computational Linguistics, 2022.
On the Role of Knowledge in Computational Argumentation
A. Lauscher, H. Wachsmuth, I. Gurevych, G. Glavaš, Transactions of the Association for Computational Linguistics (2022).
Overview of Touché 2022: Argument Retrieval
A. Bondarenko, M. Fröbe, J. Kiesel, S. Syed, T. Gurcke, M. Beloucif, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Lecture Notes in Computer Science, Springer International Publishing, Cham, 2022.
Propaganda Technique Detection Using Connotation Frames
V. Budanurmath, Propaganda Technique Detection Using Connotation Frames, 2022.
2021
Argument Undermining: Counter-Argument Generation by Attacking Weak Premises
M. Alshomary, S. Syed, M. Potthast, H. Wachsmuth, in: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Association for Computational Linguistics, 2021, pp. 1816–1827.
Assessing the Sufficiency of Arguments through Conclusion Generation
T. Gurcke, M. Alshomary, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 67–77.
Belief-based Generation of Argumentative Claims
M. Alshomary, W.-F. Chen, T. Gurcke, H. Wachsmuth, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Association for Computational Linguistics, 2021, pp. 224–223.
Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models
M. Spliethöver, H. Wachsmuth, in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, 2021, pp. 552–559.
Computational Text Professionalization using Neural Sequence-to-Sequence Models
A. Mishra, Computational Text Professionalization Using Neural Sequence-to-Sequence Models, 2021.
Controlled Neural Sentence-Level Reframing of News Articles
W.-F. Chen, K. Al Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association for Computational Linguistics: EMNLP 2021, 2021, pp. 2683–2693.
Employing Argumentation Knowledge Graphs for Neural Argument Generation
K. Al-Khatib, L. Trautner, H. Wachsmuth, Y. Hou, B. Stein, in: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), 2021, pp. 4744–4754.
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems
K.J. Rohlfing, P. Cimiano, I. Scharlau, T. Matzner, H.M. Buhl, H. Buschmeier, E. Esposito, A. Grimminger, B. Hammer, R. Haeb-Umbach, I. Horwath, E. Hüllermeier, F. Kern, S. Kopp, K. Thommes, A.-C. Ngonga Ngomo, C. Schulte, H. Wachsmuth, P. Wagner, B. Wrede, IEEE Transactions on Cognitive and Developmental Systems 13 (2021) 717–728.
Generating Informative Conclusions for Argumentative Texts
S. Syed, K. Al-Khatib, M. Alshomary, H. Wachsmuth, M. Potthast, in: Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021): Findings, 2021, pp. 3482–3493.
iClarify - A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing
Z. Nouri, N. Prakash, U. Gadiraju, H. Wachsmuth, in: Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2021, 2021.
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
M. Alshomary, T. Gurcke, S. Syed, P. Heinisch, M. Spliethöver, P. Cimiano, M. Potthast, H. Wachsmuth, in: Proceedings of the 8th Workshop on Argument Mining, 2021, pp. 184–189.
Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale
G. Skitalinskaya, J. Klaff, H. Wachsmuth, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, 2021, pp. 1718–1729.
Overview of Touché 2021: Argument Retrieval
A. Bondarenko, L. Gienapp, M. Fröbe, M. Beloucif, Y. Ajjour, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: Proceedings of the 43rd Annual European Conference on Information Retrieval Research, 2021, pp. 384–395.
Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump
J. Bülling, Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump, 2021.
2020
Abstractive Snippet Generation
W.-F. Chen, S. Syed, B. Stein, M. Hagen, M. Potthast, in: Proceedings of the Web Conference 2020, 2020, pp. 1309–1319.
Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularity
W.-F. Chen, K. Al-Khatib, H. Wachsmuth, B. Stein, in: Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 2020, pp. 149–154.
Analyzing the Persuasive Effect of Style in News Editorial Argumentation
R. El Baff, H. Wachsmuth, K. Al-Khatib, B. Stein, in: J. Tsujii, J. Hajic (Eds.), Proceedings of 58th Annual Meeting of the Association for Computational Linguistics, 2020, pp. 553–564.
Argument from Old Man's View: Assessing Social Bias in Argumentation
M. Spliethöver, H. Wachsmuth, in: Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 76–87.
CauseNet: Towards a Causality Graph Extracted from the Web
S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030.
Detecting Media Bias in News Articles using Gaussian Bias Distributions
W.-F. Chen, K. Al-Khatib, B. Stein, H. Wachsmuth, in: Findings of the Association for Computational Linguistics: EMNLP 2020, 2020, pp. 4290–4300.
End-to-End Argumentation Knowledge Graph Construction
K. Al-Khatib, Y. Hou, H. Wachsmuth, C. Jochim, F. Bonin, B. Stein, in: Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 2020, pp. 7367–7374.
Extractive Snippet Generation for Arguments
M. Alshomary, N. Düsterhus, H. Wachsmuth, in: Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020, pp. 1969–1972.
Intrinsic Quality Assessment of Arguments
H. Wachsmuth, T. Werner, in: Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, 2020, pp. 6739–6745.
Investigating Expectations for Voice-based and Conversational Argument Search on the Web
J. Kiesel, K. Lang, H. Wachsmuth, E. Hornecker, B. Stein, in: Proceedings of the 2020 ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR 2020), 2020, pp. 53–62.
Mining Crowdsourcing Problems from Discussion Forums of Workers
Z. Nouri, H. Wachsmuth, G. Engels, in: Proceedings of COLING 2020, the 28th International Conference on Computational Linguistics, n.d., pp. 6264–6276.
Overview of Touché 2020: Argument Retrieval
A. Bondarenko, M. Fröbe, M. Beloucif, L. Gienapp, Y. Ajjour, A. Panchenko, C. Biemann, B. Stein, H. Wachsmuth, M. Potthast, M. Hagen, in: CEUR Workshop Proceedings, 2020, pp. 384–395.
Persuasiveness of News Editorials depending on Ideology and Personality
R. El Baff, K. Al-Khatib, B. Stein, H. Wachsmuth, in: Third Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES 2020), 2020, pp. 29–40.
Playful User-Generated Treatment: A Novel Game Design Approach for VR Exposure Therapy
D. Alexandrovsky, G. Volkmar, M. Spliethöver, S. Finke, M. Herrlich, T. Döring, J.D. Smeddinck, R. Malaka, in: Proceedings of the Annual Symposium on Computer-Human Interaction in Play, Association for Computing Machinery, New York, NY, USA, 2020, pp. 32–45.
Semi-Supervised Cleansing of Web Argument Corpora
J. Dorsch, H. Wachsmuth, in: Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020), 2020, pp. 19–29.
2019
Argument Search: Assessing Argument Relevance
M. Potthast, L. Gienapp, F. Euchner, N. Heilenkötter, N. Weidmann, H. Wachsmuth, B. Stein, M. Hagen, in: 42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019), ACM, 2019, pp. 1117–1120.
CLEF ProtestNews Lab 2019: Contextualized Word Embeddings for Event Sentence Detection and Event Extraction
G. Skitalinskaya, J. Klaff, M. Spliethöver, CLEF ProtestNews Lab 2019: Contextualized Word Embeddings for Event Sentence Detection and Event Extraction, Lugano, Switzerland, 2019.
Computational Argumentation Synthesis as a Language Modeling Task
R. El Baff, H. Wachsmuth, K. Al-Khatib, M. Stede, B. Stein, in: Proceedings of the 12th International Conference on Natural Language Generation, Association for Computational Linguistics, 2019, pp. 54–64.
Data Acquisition for Argument Search: The args.me Corpus
Y. Ajjour, H. Wachsmuth, J. Kiesel, M. Potthast, M. Hagen, B. Stein, in: Proceedings of the 42nd Edition of the German Conference on Artificial Intelligence, 2019, pp. 48–59.
Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation
M. Spliethöver, J. Klaff, H. Heuer, in: Proceedings of the 6th Workshop on Argument Mining, Association for Computational Linguistics, Florence, Italy, 2019, pp. 74–82.
Modeling Frames in Argumentation
Y. Ajjour, M. Alshomary, H. Wachsmuth, B. Stein, in: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, 2019, pp. 2915–2925.
Proceedings of the 6th Workshop on Argument Mining
B. Stein, H. Wachsmuth, eds., Proceedings of the 6th Workshop on Argument Mining, Association for Computational Linguistics, Florence, Italy, 2019.
2018
A Plan for Ancillary Copyright: Original Snippets.
M. Potthast, W.-F. Chen, M. Hagen, B. Stein, in: Proceedings of the Second International Workshop on Recent Trends in News Information Retrieval, 2018, pp. 3–5.
A User Study on Snippet Generation: Text Reuse vs. Paraphrases
W.-F. Chen, M. Hagen, B. Stein, M. Potthast, in: Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018, pp. 1033–1036.
Application of Sentiment Analysis to Language Learning
M.-H. Chen, W.-F. Chen, L.-W. Ku, IEEE Access 6 (2018) 24433–24442.
Argumentation Synthesis following Rhetorical Strategies
H. Wachsmuth, M. Stede, R. El Baff, K. Al Khatib, M. Skeppstedt, B. Stein, in: Proceedings of the 27th International Conference on Computational Linguistics, 2018, pp. 3753–3765.
Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation
I. Habernal, H. Wachsmuth, I. Gurevych, B. Stein, in: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018, pp. 386–396.
Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus
R. El Baff, H. Wachsmuth, K. Al Khatib, B. Stein, in: Proceedings of the 22nd Conference on Computational Natural Language Learning, Association for Computational Linguistics, 2018, pp. 454–464.
If You Ask Nicely: A Digital Assistant Rebuking Impolite Voice Commands
M. Bonfert, M. Spliethöver, R. Arzaroli, M. Lange, M. Hanci, R. Porzel, in: Proceedings of the 20th ACM International Conference on Multimodal Interaction, 2018.
Learning to Flip the Bias of News Headlines
W.-F. Chen, H. Wachsmuth, K. Al Khatib, B. Stein, in: Proceedings of the 11th International Conference on Natural Language Generation, Association for Computational Linguistics, 2018, pp. 79–88.
Modeling Deliberative Argumentation Strategies on Wikipedia
K. Al Khatib, H. Wachsmuth, K. Lang, J. Herpel, M. Hagen, B. Stein, in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 2545–2555.
Reproducible Web Corpora
J. Kiesel, F. Kneist, M. Alshomary, B. Stein, M. Hagen, M. Potthast, Journal of Data and Information Quality (2018) 1–25.
Retrieval of the Best Counterargument without Prior Topic Knowledge
H. Wachsmuth, S. Syed, B. Stein, in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018, pp. 241–251.
SemEval-2018 Task 12: The Argument Reasoning Comprehension Task
I. Habernal, H. Wachsmuth, I. Gurevych, B. Stein, in: Proceedings of The 12th International Workshop on Semantic Evaluation, 2018, pp. 763–772.
2017
"Page Rank'' for Argument Relevance
H. Wachsmuth, B. Stein, Y. Ajjour, in: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 1117–1127.
A Universal Model for Discourse-Level Argumentation Analysis
H. Wachsmuth, B. Stein, Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media (2017) 1–24.
Argumentation Quality Assessment: Theory vs. Practice
H. Wachsmuth, N. Naderi, I. Habernal, Y. Hou, G. Hirst, I. Gurevych, B. Stein, in: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2017, pp. 250–255.
Building an Argument Search Engine for the Web
H. Wachsmuth, M. Potthast, K. Al-Khatib, Y. Ajjour, J. Puschmann, J. Qu, J. Dorsch, V. Morari, J. Bevendorff, B. Stein, in: Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 49–59.
Computational Argumentation Quality Assessment in Natural Language
H. Wachsmuth, N. Naderi, Y. Hou, Y. Bilu, V. Prabhakaran, T.A. Thijm, G. Hirst, B. Stein, in: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 2017, pp. 176–187.
How to Get Endorsements? Predicting Facebook Likes Using Post Content and User Engagement
W.-F. Chen, Y.-P. Chen, L.-W. Ku, in: International Conference on HCI in Business, Government, and Organizations, 2017, pp. 190–202.
Patterns of Argumentation Strategies across Topics
K. Al Khatib, H. Wachsmuth, M. Hagen, B. Stein, in: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 1362–1368.
2016
A News Editorial Corpus for Mining Argumentation Strategies
K. Al Khatib, H. Wachsmuth, J. Kiesel, M. Hagen, B. Stein, in: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 3433–3443.
Chinese Textual Sentiment Analysis: Datasets, Resources and Tools
L.-W. Ku, W.-F. Chen, in: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.
Cross-Domain Mining of Argumentative Text through Distant Supervision
K. Al-Khatib, H. Wachsmuth, M. Hagen, J. Köhler, B. Stein, in: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2016, pp. 1395–1404.
Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse
H. Wachsmuth, in: Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329–338.
2015
A Computer-assistance Learning System for Emotional Wording
W.-F. Chen, M.-H. Chen, M.-L. Chen, L.-W. Ku, IEEE Transactions on Knowledge and Data Engineering 28 (2015) 1093–1104.
Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording
W.-F. Chen, M. Chen, L.-W. Ku, in: Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications, 2015, pp. 144–153.
Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example
W.-F. Chen, L.-W. Ku, Y.-H. Lee, in: 2015 AAAI Spring Symposium Series, 2015.
Pipelines for Ad-hoc Large-scale Text Mining
H. Wachsmuth, Pipelines for Ad-Hoc Large-Scale Text Mining, 2015.
Sentiment Flow - A General Model of Web Review Argumentation
H. Wachsmuth, J. Kiesel, B. Stein, in: J. Tsujii, J. Hajic (Eds.), Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015, pp. 601–611.
2014
A Review Corpus for Argumentation Analysis
H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, T. Palakarska, in: Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics, 2014, pp. 115–127.
iSoNTRE: The Social Network Transformer into Recommendation Engine
C. Abu Quba Rana, S. Hassas, F. Usama, M. Alshomary, C. Gertosio, 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA) (2014) 169–175.
Modeling Review Argumentation for Robust Sentiment Analysis
H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, in: Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, 2014, pp. 553–564.
PBlaman: performance blame analysis based on Palladio contracts
F. Brüseke, H. Wachsmuth, G. Engels, S. Becker, in: Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment, 2014, pp. 1975–2004.
RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’ Emotional Expressions
M.-H. Chen, W.-F. Chen, L.-W. Ku, in: Proceedings of the AsiaCALL 2014, 2014.
2013
Automatic Pipeline Construction for Real-Time Annotation
H. Wachsmuth, M. Rose, G. Engels, in: A. Gelbukh (Ed.), 14th International Conference on Intelligent Text Processing and Computational Linguistics, 2013, pp. 38–49.
Information Extraction as a Filtering Task
H. Wachsmuth, B. Stein, G. Engels, in: Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management, 2013, pp. 2049–2058.
Learning Efficient Information Extraction on Heterogeneous Texts
H. Wachsmuth, B. Stein, G. Engels, in: A. Gelbukh (Ed.), Proceedings of the Sixth International Joint Conference on Natural Language Processing, 2013, pp. 534–542.
2012
A Syllable-based Prosody Modeling for L1 and L2 English Speeches
W.-F. Chen, C.-K. Kuo, Y.-R. Wang, S.-H. Chen, in: Proceedings of the 8th International Symposium on Chinese Spoken Language Processing, IEEE, 2012, pp. 281–285.
Optimal Scheduling of Information Extraction Algorithms
H. Wachsmuth, B. Stein, in: Proceedings of COLING 2012: Posters, 2012, pp. 1281–1290.
2011
Back to the Roots of Genres: Text Classification by Language Function
H. Wachsmuth, K. Bujna, in: B. Berendt, A. de Vries, W. Fan, C. Macdonald, I. Ounis, I. Ruthven (Eds.), Proceedings of 5th International Joint Conference on Natural Language Processing, 2011, pp. 632–640.
Constructing Efficient Information Extraction Pipelines
H. Wachsmuth, B. Stein, G. Engels, in: B. Berendt, A. de Vries, W. Fan, C. Macdonald, I. Ounis, I. Ruthven (Eds.), 20th ACM International Conference on Information and Knowledge Management, 2011, pp. 2237–2240.
2010
Efficient Statement Identification for Automatic Market Forecasting
H. Wachsmuth, P. Prettenhofer, B. Stein, in: Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), 2010, pp. 1128–1136.
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