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Publications


Open list in Research Information System

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

@inproceedings{Potthast_Gienapp_Euchner_Heilenkötter_Weidmann_Wachsmuth_Stein_Hagen_2019, title={Argument Search: Assessing Argument Relevance}, DOI={10.1145/3331184.3331327}, booktitle={42nd International ACM Conference on Research and Development in Information Retrieval (SIGIR 2019)}, publisher={ACM}, author={Potthast, Martin and Gienapp, Lukas and Euchner, Florian and Heilenkötter, Nick and Weidmann, Nico and Wachsmuth, Henning and Stein, Benno and Hagen, Matthias}, year={2019} }


CL 2019. Book Review of ”Argumentation Mining"

H. Wachsmuth (2019)

@article{Wachsmuth_2019, title={CL 2019. Book Review of ”Argumentation Mining"}, author={Wachsmuth, Henning}, year={2019} }


KI 2019. Data Acquisition for Argument Search: The args.me Corpus.

H. Wachsmuth, Y. Ajjour, J. Kiesel, M. Potthast, M. Hagen, B. Stein, 2019

@inproceedings{Wachsmuth_Ajjour_ Kiesel_Potthast_Hagen_Stein_2019, title={KI 2019. Data Acquisition for Argument Search: The args.me Corpus.}, author={Wachsmuth, Henning and Ajjour, Yamen and Kiesel, Johannes and Potthast, Martin and Hagen, Matthias and Stein, Benno}, year={2019} }


Wikipedia Text Reuse: Within and Without

M. Alshomary, M. Völske, T. Licht, H. Wachsmuth, B. Stein, M. Hagen, M. Potthast, in: Lecture Notes in Computer Science, 2019

@inbook{Alshomary_Völske_Licht_Wachsmuth_Stein_Hagen_Potthast_2019, place={Cham}, title={Wikipedia Text Reuse: Within and Without}, DOI={10.1007/978-3-030-15712-8_49}, booktitle={Lecture Notes in Computer Science}, author={Alshomary, Milad and Völske, Michael and Licht, Tristan and Wachsmuth, Henning and Stein, Benno and Hagen, Matthias and Potthast, Martin}, year={2019} }


2018

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

@inproceedings{Wachsmuth_Stede_El Baff_Al Khatib_Skeppstedt_Stein_2018, title={Argumentation Synthesis following Rhetorical Strategies}, booktitle={Proceedings of the 27th International Conference on Computational Linguistics}, author={Wachsmuth, Henning and Stede, Manfred and El Baff, Roxanne and Al Khatib, Khalid and Skeppstedt, Maria and Stein, Benno}, year={2018}, pages={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

@inproceedings{Habernal_Wachsmuth_Gurevych_Stein_2018, title={Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies in Web Argumentation}, booktitle={Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)}, author={Habernal, Ivan and Wachsmuth, Henning and Gurevych, Iryna and Stein, Benno}, year={2018}, pages={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

@inproceedings{El Baff_Wachsmuth_Al Khatib_Stein_2018, title={Challenge or Empower: Revisiting Argumentation Quality in a News Editorial Corpus}, booktitle={Proceedings of the 22nd Conference on Computational Natural Language Learning}, publisher={Association for Computational Linguistics}, author={El Baff, Roxanne and Wachsmuth, Henning and Al Khatib, Khalid and Stein, Benno}, year={2018}, pages={454–464} }


Learning to Flip the Bias of News Headlines

W. 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

@inproceedings{Chen_Wachsmuth_Al Khatib_Stein_2018, title={Learning to Flip the Bias of News Headlines}, booktitle={Proceedings of the 11th International Conference on Natural Language Generation}, publisher={Association for Computational Linguistics}, author={Chen, Wei-Fan and Wachsmuth, Henning and Al Khatib, Khalid and Stein, Benno}, year={2018}, pages={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

@inproceedings{Al Khatib_Wachsmuth_Lang_Herpel_Hagen_Stein_2018, title={Modeling Deliberative Argumentation Strategies on Wikipedia}, booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, author={Al Khatib, Khalid and Wachsmuth, Henning and Lang, Kevin and Herpel, Jakob and Hagen, Matthias and Stein, Benno}, year={2018}, pages={2545--2555} }


Reproducible Web Corpora

J. Kiesel, F. Kneist, M. Alshomary, B. Stein, M. Hagen, M. Potthast, Journal of Data and Information Quality (2018), pp. 1-25

@article{Kiesel_Kneist_Alshomary_Stein_Hagen_Potthast_2018, title={Reproducible Web Corpora}, DOI={10.1145/3239574}, journal={Journal of Data and Information Quality}, author={Kiesel, Johannes and Kneist, Florian and Alshomary, Milad and Stein, Benno and Hagen, Matthias and Potthast, Martin}, year={2018}, pages={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

@inproceedings{Wachsmuth_Syed_Stein_2018, title={Retrieval of the Best Counterargument without Prior Topic Knowledge}, booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, author={Wachsmuth, Henning and Syed, Shahbaz and Stein, Benno}, year={2018}, pages={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

@inproceedings{Habernal_Wachsmuth_Gurevych_Stein_2018, title={SemEval-2018 Task 12: The Argument Reasoning Comprehension Task}, booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation}, author={Habernal, Ivan and Wachsmuth, Henning and Gurevych, Iryna and Stein, Benno}, year={2018}, pages={763--772} }


Visualization of the Topic Space of Argument Search Results in args. me

Y. Ajjour, H. Wachsmuth, D. Kiesel, P. Riehmann, F. Fan, G. Castiglia, R. Adejoh, B. Fröhlich, B. Stein, in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2018, pp. 60-65

@inproceedings{Ajjour_Wachsmuth_Kiesel_Riehmann_Fan_Castiglia_Adejoh_Fröhlich_Stein_2018, title={Visualization of the Topic Space of Argument Search Results in args. me}, booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations}, author={Ajjour, Yamen and Wachsmuth, Henning and Kiesel, Dora and Riehmann, Patrick and Fan, Fan and Castiglia, Giuliano and Adejoh, Rosemary and Fröhlich, Bernd and Stein, Benno}, year={2018}, pages={60–65} }


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

@inproceedings{Wachsmuth_Stein_Ajjour_2017, title={“Page Rank’’’ for Argument Relevance”}, booktitle={Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers}, author={Wachsmuth, Henning and Stein, Benno and Ajjour, Yamen}, year={2017}, pages={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)(3), pp. 28:1--28:24

@article{Wachsmuth_Stein_2017, title={A Universal Model for Discourse-Level Argumentation Analysis}, DOI={http://doi.acm.org/10.1145/2957757}, number={3}, journal={Special Section of the ACM Transactions on Internet Technology: Argumentation in Social Media}, author={Wachsmuth, Henning and Stein, Benno}, year={2017}, pages={28:1--28:24} }


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

@inproceedings{Wachsmuth_Naderi_Habernal_Hou_Hirst_Gurevych_Stein_2017, title={Argumentation Quality Assessment: Theory vs. Practice}, DOI={10.18653/v1/P17-2039}, booktitle={Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)}, author={Wachsmuth, Henning and Naderi, Nona and Habernal, Ivan and Hou, Yufang and Hirst, Graeme and Gurevych, Iryna and Stein, Benno}, year={2017}, pages={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

@inproceedings{Wachsmuth_Potthast_Al-Khatib_Ajjour_Puschmann_Qu_Dorsch_Morari_Bevendorff_Stein_2017, title={Building an Argument Search Engine for the Web}, booktitle={Proceedings of the 4th Workshop on Argument Mining}, author={Wachsmuth, Henning and Potthast, Martin and Al-Khatib, Khalid and Ajjour, Yamen and Puschmann, Jana and Qu, Jiani and Dorsch, Jonas and Morari, Viorel and Bevendorff, Janek and Stein, Benno}, year={2017}, pages={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

@inproceedings{Wachsmuth_Naderi_Hou_Bilu_Prabhakaran_Thijm_Hirst_Stein_2017, title={Computational Argumentation Quality Assessment in Natural Language}, booktitle={Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers}, author={Wachsmuth, Henning and Naderi, Nona and Hou, Yufang and Bilu, Yonatan and Prabhakaran, Vinodkumar and Thijm, Tim Alberdingk and Hirst, Graeme and Stein, Benno}, year={2017}, pages={176--187} }


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

@inproceedings{Al Khatib_Wachsmuth_Hagen_Stein_2017, title={Patterns of Argumentation Strategies across Topics}, booktitle={Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing}, author={Al Khatib, Khalid and Wachsmuth, Henning and Hagen, Matthias and Stein, Benno}, year={2017}, pages={1362--1368} }


The Impact of Modeling Overall Argumentation with Tree Kernels

H. Wachsmuth, G. Da San Martino, D. Kiesel, B. Stein, in: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017, pp. 2369--2379

@inproceedings{Wachsmuth_Da San Martino_Kiesel_Stein_2017, title={The Impact of Modeling Overall Argumentation with Tree Kernels}, booktitle={Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing}, author={Wachsmuth, Henning and Da San Martino, Giovanni and Kiesel, Dora and Stein, Benno}, year={2017}, pages={2369--2379} }


Unit Segmentation of Argumentative Texts

Y. Ajjour, W. Chen, J. Kiesel, H. Wachsmuth, B. Stein, in: Proceedings of the 4th Workshop on Argument Mining, 2017, pp. 118--128

@inproceedings{Ajjour_Chen_Kiesel_Wachsmuth_Stein_2017, title={Unit Segmentation of Argumentative Texts}, booktitle={Proceedings of the 4th Workshop on Argument Mining}, author={Ajjour, Yamen and Chen, Wei-Fan and Kiesel, Johannes and Wachsmuth, Henning and Stein, Benno}, year={2017}, pages={118--128} }


WAT-SL: A Customizable Web Annotation Tool for Segment Labeling

J. Kiesel, H. Wachsmuth, K. Al Khatib, B. Stein, in: Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017, pp. 13--16

@inproceedings{Kiesel_Wachsmuth_Al Khatib_Stein_2017, title={WAT-SL: A Customizable Web Annotation Tool for Segment Labeling}, booktitle={Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics}, author={Kiesel, Johannes and Wachsmuth, Henning and Al Khatib, Khalid and Stein, Benno}, year={2017}, pages={13--16} }


Webis at the CLEF 2017 Dynamic Search Lab

M. Hagen, J. Kiesel, M. Alshomary, B. Stein, in: CLEF, 2017

@inproceedings{Hagen_Kiesel_Alshomary_Stein_2017, title={Webis at the CLEF 2017 Dynamic Search Lab}, booktitle={CLEF}, author={Hagen, Matthias and Kiesel, Johannes and Alshomary, Milad and Stein, Benno}, year={2017} }


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

@inproceedings{Al Khatib_Wachsmuth_Kiesel_Hagen_Stein_2016, title={A News Editorial Corpus for Mining Argumentation Strategies}, booktitle={Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers}, author={Al Khatib, Khalid and Wachsmuth, Henning and Kiesel, Johannes and Hagen, Matthias and Stein, Benno}, year={2016}, pages={3433--3443} }


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

@inproceedings{Al-Khatib_Wachsmuth_Hagen_Köhler_Stein_2016, title={Cross-Domain Mining of Argumentative Text through Distant Supervision}, DOI={10.18653/v1/N16-1165}, booktitle={Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies}, author={Al-Khatib, Khalid and Wachsmuth, Henning and Hagen, Matthias and Köhler, Jonas and Stein, Benno}, year={2016}, pages={1395--1404} }


Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse

H. Wachsmuth, in: Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329-338

@inproceedings{Wachsmuth_2016, title={Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse}, booktitle={Ausgezeichnete Informatikdissertationen 2015}, author={Wachsmuth, Henning}, year={2016}, pages={329–338} }


Using Argument Mining to Assess the Argumentation Quality of Essays

H. Wachsmuth, K. Al Khatib, B. Stein, in: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 1680--1691

@inproceedings{Wachsmuth_Al Khatib_Stein_2016, title={Using Argument Mining to Assess the Argumentation Quality of Essays}, booktitle={Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers}, author={Wachsmuth, Henning and Al Khatib, Khalid and Stein, Benno}, year={2016}, pages={1680--1691} }


2015

Pipelines for Ad-hoc Large-scale Text Mining

H. Wachsmuth, 2015

Today's web search and big data analytics applications aim to address information needs~(typically given in the form of search queries) ad-hoc on large numbers of texts. In order to directly return relevant information instead of only returning potentially relevant texts, these applications have begun to employ text mining. The term text mining covers tasks that deal with the inference of structured high-quality information from collections and streams of unstructured input texts. Text mining requires task-specific text analysis processes that may consist of several interdependent steps. These processes are realized with sequences of algorithms from information extraction, text classification, and natural language processing. However, the use of such text analysis pipelines is still restricted to addressing a few predefined information needs. We argue that the reasons behind are three-fold: First, text analysis pipelines are usually made manually in respect of the given information need and input texts, because their design requires expert knowledge about the algorithms to be employed. When information needs have to be addressed that are unknown beforehand, text mining hence cannot be performed ad-hoc. Second, text analysis pipelines tend to be inefficient in terms of run-time, because their execution often includes analyzing texts with computationally expensive algorithms. When information needs have to be addressed ad-hoc, text mining hence cannot be performed in the large. And third, text analysis pipelines tend not to robustly achieve high effectiveness on all texts, because their results are often inferred by algorithms that rely on domain-dependent features of texts. Hence, text mining currently cannot guarantee to infer high-quality information. In this thesis, we contribute to the question of how to address information needs from text mining ad-hoc in an efficient and domain-robust manner. We observe that knowledge about a text analysis process and information obtained within the process help to improve the design, the execution, and the results of the pipeline that realizes the process. To this end, we apply different techniques from classical and statistical artificial intelligence. In particular, we first develop knowledge-based approaches for an ad-hoc pipeline construction and for an optimal execution of a pipeline on its input. Then, we show theoretically and practically how to optimize and adapt the schedule of the algorithms in a pipeline based on information in the analyzed input texts in order to maximize execution efficiency. Finally, we learn patterns in the argumentation structures of texts statistically that remain strongly invariant across domains and that, thereby, allow for more robust analysis results in a restricted set of tasks. We formally analyze all developed approaches and we implement them as open-source software applications. Based on these applications, we evaluate the approaches on established and on newly created collections of texts for scientifically and industrially important text analysis tasks, such as financial event extraction and fine-grained sentiment analysis. Our findings show that text analysis pipelines can be designed automatically, which process only portions of text that are relevant for the information need at hand. Through scheduling, the run-time efficiency of pipelines can be improved by up to more than one order of magnitude while maintaining effectiveness. Moreover, we provide evidence that a pipeline's domain robustness substantially benefits from focusing on argumentation structure in tasks like sentiment analysis. We conclude that our approaches denote essential building blocks of enabling ad-hoc large-scale text mining in web search and big data analytics applications.

@book{Wachsmuth_2015, title={Pipelines for Ad-hoc Large-scale Text Mining}, author={Wachsmuth, Henning}, year={2015} }


Sentiment Flow - A General Model of Web Review Argumentation

H. Wachsmuth, J. Kiesel, B. Stein, in: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015, pp. 601--611

@inproceedings{Wachsmuth_Kiesel_Stein_2015, series={Lecture Notes in Computer Science}, title={Sentiment Flow - A General Model of Web Review Argumentation}, DOI={10.18653/v1/D15-1072}, booktitle={Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing}, author={Wachsmuth, Henning and Kiesel, Johannes and Stein, Benno}, editor={Tsujii, Junichi and Hajic, JanEditors}, year={2015}, pages={601--611}, collection={Lecture Notes in Computer Science} }


Text Analysis Pipelines - Towards Ad-hoc Large-scale Text Mining

H. Wachsmuth, 2015

@book{Wachsmuth_2015, series={Lecture Notes in Computer Science}, title={Text Analysis Pipelines - Towards Ad-hoc Large-scale Text Mining}, DOI={http://dx.doi.org/10.1007/978-3-319-25741-9}, author={Wachsmuth, Henning}, year={2015}, collection={Lecture Notes in Computer Science} }


2014

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), pp. 169-175

@article{Abu Quba Rana_Hassas_Usama_Alshomary_Gertosio_2014, title={iSoNTRE: The Social Network Transformer into Recommendation Engine}, journal={2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA)}, author={Abu Quba Rana, Chamsi and Hassas, Salima and Usama, Fayyad and Alshomary, Milad and Gertosio, Christine}, year={2014}, pages={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

@inproceedings{Wachsmuth_Trenkmann_Stein_Engels_2014, title={Modeling Review Argumentation for Robust Sentiment Analysis}, booktitle={Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers}, author={Wachsmuth, Henning and Trenkmann, Martin and Stein, Benno and Engels, Gregor}, year={2014}, pages={553--564} }


Modeling Review Argumentation for Robust Sentiment Analysis

H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, in: 25th International Conference on Computational Linguistics, 2014, pp. 553-564

@inproceedings{Wachsmuth_Trenkmann_Stein_Engels_2014, title={Modeling Review Argumentation for Robust Sentiment Analysis}, booktitle={25th International Conference on Computational Linguistics}, author={Wachsmuth, Henning and Trenkmann, Martin and Stein, Benno and Engels, Gregor}, editor={Tsujii, Junichi and Hajic, JanEditors}, year={2014}, pages={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

@inproceedings{Brüseke_Wachsmuth_Engels_Becker_2014, title={PBlaman: performance blame analysis based on Palladio contracts}, number={12}, booktitle={Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment}, author={Brüseke, Frank and Wachsmuth, Henning and Engels, Gregor and Becker, Steffen}, year={2014}, pages={1975--2004} }


2013

Automatic Pipeline Construction for Real-Time Annotation

H. Wachsmuth, M. Rose, G. Engels, in: 14th International Conference on Intelligent Text Processing and Computational Linguistics, 2013, pp. 38--49

@inproceedings{Wachsmuth_Rose_Engels_2013, series={Lecture Notes in Computer Science}, title={Automatic Pipeline Construction for Real-Time Annotation}, DOI={http://dx.doi.org//10.1007/978-3-642-37247-6_4}, booktitle={14th International Conference on Intelligent Text Processing and Computational Linguistics}, author={Wachsmuth, Henning and Rose, Mirko and Engels, Gregor}, editor={Gelbukh, AlexanderEditor}, year={2013}, pages={38--49}, collection={Lecture Notes in Computer Science} }


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

@inproceedings{Wachsmuth_Stein_Engels_2013, title={Information Extraction as a Filtering Task}, booktitle={Proceedings of the 22nd ACM International Conference on Conference on Information \& Knowledge Management}, author={Wachsmuth, Henning and Stein, Benno and Engels, Gregor}, year={2013}, pages={2049--2058} }


Learning Efficient Information Extraction on Heterogeneous Texts

H. Wachsmuth, B. Stein, G. Engels, in: Proceedings of the Sixth International Joint Conference on Natural Language Processing, 2013, pp. 534--542

@inproceedings{Wachsmuth_Stein_Engels_2013, series={Lecture Notes in Computer Science}, title={Learning Efficient Information Extraction on Heterogeneous Texts}, DOI={http://dx.doi.org//10.1007/978-3-642-37247-6_4}, booktitle={Proceedings of the Sixth International Joint Conference on Natural Language Processing}, author={Wachsmuth, Henning and Stein, Benno and Engels, Gregor}, editor={Gelbukh, AlexanderEditor}, year={2013}, pages={534--542}, collection={Lecture Notes in Computer Science} }


2012

Optimal Scheduling of Information Extraction Algorithms

H. Wachsmuth, B. Stein, in: Proceedings of COLING 2012: Posters, 2012, pp. 1281--1290

@inproceedings{Wachsmuth_Stein_2012, title={Optimal Scheduling of Information Extraction Algorithms}, booktitle={Proceedings of COLING 2012: Posters}, author={Wachsmuth, Henning and Stein, Benno}, year={2012}, pages={1281--1290} }


2011

Back to the Roots of Genres: Text Classification by Language Function

H. Wachsmuth, K. Bujna, in: Proceedings of 5th International Joint Conference on Natural Language Processing, 2011, pp. 632--640

@inproceedings{Wachsmuth_Bujna_2011, title={Back to the Roots of Genres: Text Classification by Language Function}, DOI={http://doi.acm.org/10.1145/2063576.2063935}, booktitle={Proceedings of 5th International Joint Conference on Natural Language Processing}, author={Wachsmuth, Henning and Bujna, Kathrin}, editor={Berendt, Bettina and de Vries, Arjen and Fan, Wenfei and Macdonald, Craig and Ounis, Iadh and Ruthven, IanEditors}, year={2011}, pages={632--640} }


Constructing Efficient Information Extraction Pipelines

H. Wachsmuth, B. Stein, G. Engels, in: 20th ACM International Conference on Information and Knowledge Management, 2011, pp. 2237-2240

@inproceedings{Wachsmuth_Stein_Engels_2011, title={Constructing Efficient Information Extraction Pipelines}, DOI={http://doi.acm.org/10.1145/2063576.2063935}, booktitle={20th ACM International Conference on Information and Knowledge Management}, author={Wachsmuth, Henning and Stein, Benno and Engels, Gregor}, editor={Berendt, Bettina and de Vries, Arjen and Fan, Wenfei and Macdonald, Craig and Ounis, Iadh and Ruthven, IanEditors}, year={2011}, pages={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

@inproceedings{Wachsmuth_Prettenhofer_Stein_2010, title={Efficient Statement Identification for Automatic Market Forecasting}, booktitle={Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)}, author={Wachsmuth, Henning and Prettenhofer, Peter and Stein, Benno}, year={2010}, pages={1128--1136} }


2007

Smart Teams: Simulating Large Robotic Swarms in Vast Environments

S. Arens, A. Buss, H. Deck, M. Dynia, M. Fischer, H. Hagedorn, P. Isaak, J. Kutylowski, F. Meyer auf der Heide, V. Nesterow, A. Ogiermann, B. Stobbe, T. Storm, H. Wachsmuth, in: Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment, Heinz Nixdorf Institut, University of Paderborn, 2007, pp. 215-222

We consider the problem of exploring an unknown environment using a swarm of autonomous robots with collective behavior emerging from their local rules. Each robot has only a very restricted view on the environment which makes cooperation difficult. We introduce a software system which is capable of simulating a large number of such robots (e.g. 1000) on highly complex terrains with millions of obstacles. Its main purpose is to easily integrate and evaluate any kind of algorithm for controlling the robot behavior. The simulation may be observed in real-time via a visualization that displays both the individual and the collective progress of the robots. We present the system design, its main features and underlying concepts.

@inproceedings{Arens_Buss_Deck_Dynia_Fischer_Hagedorn_Isaak_Kutylowski_Meyer auf der Heide_Nesterow_et al._2007, place={Buenos Aires, Argentina}, title={Smart Teams: Simulating Large Robotic Swarms in Vast Environments}, booktitle={Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment}, publisher={Heinz Nixdorf Institut, University of Paderborn}, author={Arens, Stephan and Buss, Alexander and Deck, Helena and Dynia, Miroslaw and Fischer, Matthias and Hagedorn, Holger and Isaak, Peter and Kutylowski, Jaroslaw and Meyer auf der Heide, Friedhelm and Nesterow, Viktor and et al.}, year={2007}, pages={215–222} }


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