Publikationen

2020

Fine-Grained Argument Unit Recognition and Classification.
Trautmann D., Daxenberger J. Stab C., Schütze H., Gurevych I., In Proc. of the Thirty-Fourth AAAI Conf. on Artificial Intelligence (AAAI'20), 2020.

A Framework for Argument Retrieval - Ranking Argument Clusters by Frequency and Specificity.
Dumani, L., Neumann, P.J., Schenkel, R. In ECIR 2020: Advances in Information Retrieval - 42nd European Conf. on IR Research.

Predicting persuasive effectiveness for multimodal behavior adaptation using bipolar weighted argument graphs.
Weber, K., Janowski, K., Rach, N., Weitz, K., Minker, W., Ultes, S. and André, E. In Proc. of the 19th Intl. Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS '20). ACM, New York, USA. Nominated for the Best Paper Award.

Towards Demystifying Subliminal Persuasiveness: Using XAI-Techniques to Highlight Persuasive Markers of Public Speeches.
Weber, K., Tinnes, L., Huber, T., Heimerl, A., Pohlen, E., Reinecker, M-L. and André, E. In the 2nd Intl. Workshop on EXplainable, TRansparent Autonomous Agents and Multi-Agent Systems (EXTAAMAS '20). Springer. (In press).

Evaluation of Argument Search Approaches in the Context of Argumentative Dialogue Systems.
Rach, N., Matsuda, Y., Daxenberger, J., Ultes, S., Yasumoto, K. and Minker, W.
Accepted for Presentation at the 12th Intl. Conf. on Language Resources and Evaluation (LREC), Marseille, France, 2020.

Epistemic Graphs for Representing and Reasoning with Positive and Negative Influences of Arguments.
Hunter, A., Polberg, S. and Thimm, M. In Artificial intelligence 281:103236, 2020.

Touché: First Shared Task on Argument Retrieval.
Bondarenko, A., Hagen, M., Potthast, M., Wachsmuth, H., Beloucif, M., Biemann, Ch., Panchenko, A., Stein, B. In Advances in Information Retrieval. ECIR 2020. Lecture Notes in Computer Science, Vol. 12036. Springer.

Comparative Web Search Questions.
Bondarenko, A., Braslavski, P., Völske, M., Aly, R., Fröbe, M., Panchenko, A., Biemann, Ch., Stein, B. and Hagen, M. In Proc. of the 13th Intl. Conf. on Web Search and Data Mining (WSDM ’20). Association for Computing Machinery, New York, NY, USA, 52–60.

Independent argumentation schemes? Transferring argument queries from Brexit to environment tweets.
Dykes, N., Heinrich, P. and Blombach, A. Presentation at ICAME41, Heidelberg, Germany, 2020.

Leveraging Corpus Queries for Argumentation Mining.
Heinrich, P., Dykes, N. and Stefan E. Presentation at APCLC 2020, Seoul, Republic of Korea, 2020.

Implicit Knowledge in Argumentative Texts: An Annotated Corpus.
Becker, M., Korfhage, K., and Frank, A. In Proceedings of LREC. Marseille, France, 2020.

Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets.
Haunss, S., Kuhn, J., Padó, S., Blessing, A., Blokker, N., Dayanik, E. and Lapesa, G. In Politics and Governance, 8(2), 2020. (To appear).

Masking Actor Information Leads to Fairer Political Claims Detection.
Dayanik, E. and Padó, S. In Proc. of ACL. Seattle, WA, 2020. (To appear).

DEbateNet-mig15: Tracing the 2015 Immigration Debate in Germany Over Time.
Lapesa, G., Blessing, A., Blokker, N., Dayanik, E., Haunss, S., Kuhn, J. and Padó, S. In Proc. of LREC. Marseille, France, 2020. (To appear).

AMR Similarity Metrics from Principles.
Opitz, J., Parcalabescu, L. and Frank, A. (2020). In Transactions of the Association for Computational Linguistics.

Argumentative Relation Classification with Background Knowledge.
Paul, D., Opitz, J., Becker, M., Kobbe, J., Hirst, G. and Frank, A. In Proc. of the 8th Intl. Conf. on Computational Models of Argument (COMMA 2020) (To appear) .

Explaining Arguments with Background Knowledge. Towards Knowledge-based Argumentation Analysis.
Becker, M., Hulpus, I., Paul, D., Opitz, J., Kobbe, J., Stuckenschmidt, H. and Frank, A. (2020). In Datenbank Spektrum 20:131–141, Special Issue: Argumentation Intelligence.

Unsupervised Stance Detection for Arguments from Consequences.
Kobbe, J., Hulpus, I. and Stuckenschmidt, H. (2020). In Proc. of the 2020 Conf. on Empirical Methods in Natural Language Processing (EMNLP)

2019

A Systematic Comparison of Methods for Finding Good Premises for Claims. 
Dumani, L.; Schenkel, R. In SIGIR 2019: Proc. of the 42nd Intl. ACM SIGIR Conf. on Research and Development in Information Retrieval.

Good Premises Retrieval via a Two-Stage Argument Retrieval Model. 
Dumani, L. In GvDB 2019: Proc. of the 31st GI-Workshop Grundlagen von Datenbanken, CEUR Workshop Proc. Vol. 2367.

Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections. 
El-Assday, M., Kehlbeck, R., Collins, CH., Keim, D.A., Deussen, O. (2019). IEEE Transactions on Visualization and Computer Graphics, 2019.

Aspectual Reasoning in LFG – A Computational Approach to Grammatical and Lexical Aspect. 
Zymla, M. and Butt, M. In Proc. of the LFG’19 Conf. 2019.

On the Syntax/Semantics Interface in Computational Glue Semantics: A Case Study. 
Zymla, M., Sigwarth, G., Butt, M. In Proc. of the LFG’19 Conf. 2019.

VIANA: Visual Interactive Annotation of Argumentation.
Sperrle, F., Sevastjanova, R., Kehlbeck, R., El-Assady, M. (2019) IEEE Conf. on Visual Analytics Science and Technology (VAST). 2019.

Human Trust Modeling for Bias Mitigation in Artificial Intelligence.
Sperrle, F., Schlegel, U., Keim, D.A., El-Assady. M. ACM CHI 2019 Workshop: Where is the Human? Bridging the Gap Between AI and HCI, 2019.

Visual Analytics for Topic Model Optimization based on User-Steerable Speculative Execution.
El-Assady, M., Sperrle, F., Deussen, O., Keim, D., Collins, Ch. (2019) IEEE Transactions on Visualization and Computer Graphics, 2019.

Abstract Graphs and Abstract Paths for Knowledge Graph Completion.
Nastase, V. and Kotnis, B. In Proc. of the 8th Joint Conf. on Lexical and Computational Semantics (* SEM 2019), Minneapolis, Minnesota, 2019.

Dissecting Content and Context in Argumentative Relation Analysis.
Opitz, J. and Frank, A. In Proc. of the 6th Workshop on Argument Mining, Florence, Italy, 2019.

Automatic Accuracy Prediction for AMR Parsing. 
Opitz, J. and Frank, A. In Proc. of 8th Joint Conf. on Lexical and Computational Semantics (*SEM), Minneapolis, Minnesota, 2019.

Argumentative Relation Classification as Plausibility Ranking. 
Opitz, J. In Proc. of the 15th Conf. on Natural Language Processing (KONVENS), 2019.

A Spreading Activation Framework for Tracking Conceptual Complexity of Texts.
Hulpus, I., Stajner, S. and Stuckenschmidt, H. In Proc. of the 57th Conf. of the Association for Computational Linguistics (ACL 2019), pp. 3878-3887. 2019.

Anytime bottom-up rule learning for knowledge graph completion.
Meilicke, C., Chekol, M.W., Ruffinelli, D. and Stuckenschmidt, H. In Proc. of the 28h Intl. Joint Conf. on Artificial Intelligence (IJCAI-2019).

Towards Explaining Natural Language Arguments with Background Knowledge.
Hulpus, I., Kobbe, J., Meilicke, C., Stuckenschmidt, H., Hirst, G., Becker, M., Opitz, J., Nastase, V. and Frank, A. In the Workshop on Semantic Explainability (SemEx 2019) in the 18th Intl. Semantic Web Conf. (ISWC 2019), Christchurch, New Zealand, 2019.

Clustering of Argument Graphs Using Semantic Similarity Measures.
Block, K., Trumm, S., Sahitaj, P., Ollinger, S. and Bergmann, R. In KI 2019: Advances in Artificial Intelligence: 42nd German Conf. on AI, Kassel, Germany, September 23–26, 2019, Proceedings, 2019.Springer.

Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs.
Lenz, M.; Ollinger, S.; Sahitaj, P.; and Bergmann, R. In Proceedings of the 27th Intl. Conf. on Case-Based Reasoning Research and Development (ICCBR 2019), pp. 219–234, Otzenhausen, Germany, 2019.

CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors.
Baris, I.,Schmelzeisen, L. and Staab, S. In the 3th Intl. Workshop on Semantic Evaluation, Minneapolis, USA, 2019.

Categorizing Comparative Sentences.
Panchenko, A., Bondarenko, A., Franzek, M., Hagen, M. and Biemann, Ch. In Proc. of the the 6th Workshop on Argument Mining (ArgMining'2019) in the ACL 2019, Florence, Italy, 2019.

Annotating and analyzing the interactions between meaning relations.
Gold, D., Kovatchev, V., and Zesch, T. In Proceedings of the 13th Linguistic Annotation Workshop in the ACL 2019 (pp. 26--6), Florence, Italy, 2019.

An Environment for Relational Annotation of Political Debates.
Blessing, A., Blokker, N., Haunss, S., Kuhn, J., Lapesa, G. and Padó, S. In Proc. of the 57th Annual Meeting of the ACL: System Demonstrations (pp. 105-110),  Florence, Italy, 2019.

Who Sides with Whom? Towards Computational Construction of Discourse Networks for Political Debates.
Padó, S., Blessing, A., Blokker, N., Dayanik, E., Haunss, S. and Kuhn, J. In Proc. of the 57th Annual Meeting of the ACL (pp. 2841-2847), Florence, Italy, 2019.

Assessing the Difficulty of Classifying ConceptNet Relations in a Multi-Label Classification Setting.
Becker, M., Staniek, M., Nastase, V., Frank, A. In RELATIONS - Workshop on meaning relations between phrases and sentences (co-located with IWCS), Gothenburg, Sweden, 2019.

Using Topic Specific Features for Argument Stance Recognition.
Eljasik-Swoboda, T., Engel, F. and Hemmje, M. In Proc. of the 8th Intl. Conf. on Data Science, Technology and Applications (DATA), pp. 13-22, Prague, Czech Republic, 2019.

TARGER: NeuralArgument Mining at Your Fingertips.
Chernodub, A., Oliynyk, O., Heidenreich, P., Bondarenko, A., Hagen, M., Biemann, C.and Panchenko, A. In Proc. of the 57th Annual Meeting of the ACL: System Demonstrations (pp. 195-200), Florence, Italy, 2019.

Answering Comparative Questions: Better than Ten-Blue-Links?
Schildwächter, M.,Bondarenko, A., Zenker, J., Hagen, M., Biemann, C. and Panchenko, A. (2019). In Proc. of the 2019 Conf. on Human Information Interaction and Retrieval CHIIR '19, (pp. 361-365). Glasgow, Scotland, UK.

Classification and Clustering of Arguments with Contextualized Word Embeddings.
Reimers, N., Schiller, B., Beck, T., Daxenberger, J., Stab, Ch.  and Gurevych, I. In Proc. of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 567-578. Florence, Italy, July, 2019.

Exploiting Background Knowledge for Argumentative Relation Classification.
Kobbe, J., Opitz, J., Becker, M.,Hulpus, I., Stuckenschmidt, H. and Frank, A. In the 2nd Biennial Conf. on Language, Data and Knowledge LDK 2019, Dagstuhl, Germany, 2019. (Best Student Paper Award).

Similarity Measures for Case-Based Retrieval of Natural Language Argument Graphs in Argumentation Machines.
Bergmann, R., Lenz, M., Ollinger, S., Pfister, M. In Proc. of the 32nd Intl. Conf. of The Florida Artificial Intelligence Research Society (FLAIRS 2019), Sarasota, Florida, USA, 2019.

C-TrO: an Ontology for Summarization and Aggregation of the Level of Evidence in Clinical Trials.
Sanchez-Graillet, O., Cimiano, P., Witte, C and Ell, B. In the Proc. of the Workshop Ontologies and Data in Life Sciences (ODLS 2019) in the Joint Ontology Workshops' (JOWO 2019), Graz, Austria.

Argumentation Schemes for Clinical Interventions. Towards an Evidence-aggregation System for Medical Recommendations.
Sanchez-Graillet, O., Cimiano, P., Witte, C and Ell, B. In The 4th Internt. Conf. HEALTHINFO 2019, November 24-28, Valencia, Spain, 2019.

Emotion recognition based preference modelling in argumentative dialogue systems.
Rach, N., Weber, K., Aicher, A., Lingenfelser, F., André, E. and Minker, W.. In the IEEE Intl. Conf. on Pervasive Computing and Communications Workshops (PerCom Workshops), Kyoto, Japan, 2019.

Opinion Building based on the Argumentative Dialogue System BEA.
Aicher, A., Rach, N., Minker, W. and Ultes, S. In Proc. of the 10th Intl. Workshop on Spoken Dialog Systems Technology (IWSDS 2019), Siracusa, Italy, 2019.

Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study.
Kuhlmann, I. and Thimm, M.  In Proc. of the 13th Intl. Conf. on Scalable Uncertainty Management (SUM'19). December 2019.

Ranked Programming.
Rienstra, T. In Proc. of the 28th Intl. Joint Conf. on Artificial Intelligence (IJCAI'19), August 2019.

A General Approach to Reasoning with Probabilities.
Cerutti, F. and Thimm, M. In Intl. Journal of Approximate Reasoning, 111:35-50. August 2019.

Automatic Bayesian Density Analysis.
Vergari, A. Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I. In Proc. of the Thirty-Third AAAI Conf. on Artificial Intelligence (AAAI'19), 2019.

Explanatory Interactive Machine Learning.
Teso, S., Kersting, K. In Proc. of the 2nd AAAI/ACM Conf. on AI, Ethics, and Society (AIES). 2019.

Webis at TREC 2019: Decision Track.
Bondarenko, A., Fröbe, M., Kasturia, V., Völske, M., Stein, B. and Hagen, M. In the Proc. of the 28th Text REtrieval Conference (TREC 2019).

Emerging Named Entity Recognition on Retrieval Features in an Affective Computing Corpus.
Nawroth, C., Engel, F., Mc Kevitt, P. and Hemmje, M. L. In Proc. of the IEEE Intl. Conf. on Bioinformatics and Biomedicine (BIBM 2019), pp. 2860-2868, San Diego, CA, USA, 2019.

Reconstructing Twitter arguments with corpus linguistics.
Dykes, N., Heinrich, P. and Evert, S. Presentation at ICAME40: Language in Time, Time in Language. Neuchâtel, Switzerland, 2019.

Arguing Brexit on Twitter. A corpus linguistic study.
Dykes, N., Heinrich, P. and Evert, S. Presentation at the European Conference on Argumentation 2019, Groningen, Netherlands, 2019.

Classifying Semantic Clause Types with Recurrent Neural Networks: Analysis of Attention, Context and Genre Characteristics.
Becker, M., Staniek, M., Nastase, V., Palmer, A., and Frank, A. In TAL Journal (Traitement Automatique des Langues / Natural Language Processing): Special issue Deep Learning for Natural Language Processing (2019).

2018

Augmenting Public Deliberations through Stream Argument Analytics and Visualisations.
Plüss, B., Sperrle, F., Gold, V., El-Assady, M., Hautli, A., Budzynska, K., Reed, Ch. In  The Leipzig Symposium on Visualization in Applications, 2018.

Speculative Execution for Guided Visual Analytics.
Sperrle, F., Bernard, J., Sedlmair, M., Keim, D., El-Assady. M. In The Workshop on Machine Learning from User Interaction for Visualization and Analytics as part of the IEEE VIS,2018.

Utilizing Argument Mining Techniques for Argumentative Dialogue Systems.
Rach, N., Langhammer, S., Minker, W. and Ultes, S. In Proc. of the 9th Intl. Workshop On Spoken Dialogue Systems (IWSDS), Singapore, 2018.

Handling Unknown User Arguments in Argumentative Dialogue Systems.
Rach, N., Minker, W. and Ultes, S. Presented at the 32nd British Human Computer Interaction Conf. (HCI), Belfast Markov, 2018.

Games for Persuasive Dialogue.
Rach, N., Minker, W. and Ultes, S. Accepted for presentation at the 7th Intl. Conf. on Computational Models of Argument (COMMA), Warsaw, 2018.

EVA: A Multimodal Argumentative Dialogue System.
Rach, N., Weber, K., Pragst, L.,André, E., Minker, W. and Ultes, S. Accepted for presentation at the 20th ACM Intl. Conf. on Multimodal Interaction, Boulder, Colorado, October, 2018.

Probabilistic Abstract Argumentation based on SCC Decomposability.
Rienstra, T., Thimm, M., Liao, B., van der Torre, L. In Proceedings of the 16th Intl. Conf. on Principles of Knowledge Representation and Reasoning (KR'18), October, 2018.

A General Approach to Reasoning with Probabilities (Extended Abstract).
Cerutti, F., Thimm, M. In Proc. of the 16th Intl. Conf. on Principles of Knowledge Representation and Reasoning (KR'18), October, 2018.

Towards Enabling Emerging Named Entity Recognition as a Clinical Information and Argumentation Support.
Nawroth, C., Engel, F.C., Eljasik-Swoboda, T. and Hemmje, M. In Proc. of the 7th Intl. Conf. on Data Science, Technology and Applications (DATA), pp. 47-55, Porto, Portugal, 2018.

Epistemic Attack Semantics.
Thimm, M. Polberg, S., Hunter, A. In Proc. of the Seventh Intl. Conf. on Computational Models of Argumentation (COMMA'18), September, 2018.

Probabilistic Graded Semantics.
Thimm, M., Cerutti, F., Rienstra, T. In Proc. of the Seventh Intl. Conf. on Computational Models of Argumentation (COMMA'18), September, 2018.

Ranking Functions over Labellings.
Rienstra, T. and Thimm, M. In Proc. of the Seventh Intl. Conf. on Computational Models of Argumentation (COMMA'18), September, 2018.

Stochastic Local Search Algorithms for Abstract Argumentation under Stable Semantics.
Thimm, M. In Proc. of the Seventh Intl. Conf. on Computational Models of Argumentation (COMMA'18), September, 2018.

Argumentation as Exogenous Coordination.
van der Torre, L., Rienstra, T., Gabbay, D. In It's All About Coordination. Springer Intl. Publishing, 2018.

Building a Web-Scale Dependency-Parsed Corpus from Common Crawl.
Panchenko, A., Ruppert, E., Faralli, S., Ponzetto, S.P., Biemann, C. In Proc. of LREC 2018, Myazaki, Japan, 2018.

Unsupervised Semantic Frame Induction using Triclustering.
Ustalov D., Panchenko A., Kutuzov A., Biemann C., Ponzetto S. P. In Proc. of the ACL’2018. Melbourne, Australia, 2018.

Unsupervised Sense-Aware Hypernymy Extraction.
Ustalov D., Panchenko A., Biemann C., Ponzetto S.-P. In Proc. of KONVENS’2018. Vienna, Austria. p. 192-201, 2018

Corpus of Aspect-based Sentiment in Political Debates.
Gold, D., Bexte, M. Zesch, T. In Proc. of KONVENS’2018. Vienna, Austria. p. 89-99, 2018.

ReCAP - Information Retrieval and Case-Based Reasoning for Robust Deliberation and Synthesis of Arguments in the Political Discourse.
Bergmann, R., Schenkel, R., Dumani, L., Ollinger, S.In Proc. of the Conf. "Lernen, Wissen, Daten, Analysen", LWDA 2018.

Webis at TREC 2018: Common Core Track.
Bondarenko, A., Völske, M., Panchenko, A., Biemann, Ch., Stein, B., Hagen, M. In the 27th Intl. Text Retrieval Conf. (TREC 2018), November 2018. National Inst. of Standards and Technology (NIST).

Probabilistic Augmentations for Knowledge Representation Formalisms.
Cerutti, F. and Thimm, M. In Proc. of the 2018 Workshop on Hybrid Reasoning and Learning (HRL'18). October 2018.

Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs.
Kotnis, B. and Nastase, V. In KBCOM 2018, Los Angeles, California (2018). 

Using Patterns in Knowledge Graphs for Targeted Information Extraction.
Zhou, M. and Nastase, V. In KBCOM 2018. 

Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs.
Kotnis, B. and Nastase, V. In KBCOM 2018, Los Angeles, California. 

2017

Towards Argumentation-based Classification.
Thimm, M. and Kersting, K. In Logical Foundations of Uncertainty and Machine Learning, Workshop at IJCAI'17. August, 2017.

Kontakt

Prof Dr. Philipp Cimiano
Tel: 0521 106-12249
E-Mail