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Lecture Notes in Computer Science, 2015. <a href=\"http://dx.doi.org/10.1007/978-3-319-25741-9\">http://dx.doi.org/10.1007/978-3-319-25741-9</a>.","mla":"Wachsmuth, Henning. <i>Text Analysis Pipelines - Towards Ad-Hoc Large-Scale Text Mining</i>. 2015, doi:<a href=\"http://dx.doi.org/10.1007/978-3-319-25741-9\">http://dx.doi.org/10.1007/978-3-319-25741-9</a>.","bibtex":"@book{Wachsmuth_2015, series={Lecture Notes in Computer Science}, title={Text Analysis Pipelines - Towards Ad-hoc Large-scale Text Mining}, DOI={<a href=\"http://dx.doi.org/10.1007/978-3-319-25741-9\">http://dx.doi.org/10.1007/978-3-319-25741-9</a>}, author={Wachsmuth, Henning}, year={2015}, collection={Lecture Notes in Computer Science} }","ama":"Wachsmuth H. <i>Text Analysis Pipelines - Towards Ad-Hoc Large-Scale Text Mining</i>.; 2015. doi:<a href=\"http://dx.doi.org/10.1007/978-3-319-25741-9\">http://dx.doi.org/10.1007/978-3-319-25741-9</a>"}},{"citation":{"chicago":"Wachsmuth, Henning. <i>Pipelines for Ad-Hoc Large-Scale Text Mining</i>, 2015.","short":"H. Wachsmuth, Pipelines for Ad-Hoc Large-Scale Text Mining, 2015.","apa":"Wachsmuth, H. (2015). <i>Pipelines for Ad-hoc Large-scale Text Mining</i>.","ieee":"H. Wachsmuth, <i>Pipelines for Ad-hoc Large-scale Text Mining</i>. 2015.","ama":"Wachsmuth H. <i>Pipelines for Ad-Hoc Large-Scale Text Mining</i>.; 2015.","bibtex":"@book{Wachsmuth_2015, title={Pipelines for Ad-hoc Large-scale Text Mining}, author={Wachsmuth, Henning}, year={2015} }","mla":"Wachsmuth, Henning. <i>Pipelines for Ad-Hoc Large-Scale Text Mining</i>. 2015."},"related_material":{"link":[{"url":"https://webis.de/downloads/publications/papers/wachsmuth_2013.pdf","relation":"confirmation"}]},"abstract":[{"text":"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.","lang":"eng"}],"date_created":"2019-02-06T14:14:29Z","department":[{"_id":"66"},{"_id":"600"}],"type":"dissertation","author":[{"last_name":"Wachsmuth","first_name":"Henning","full_name":"Wachsmuth, Henning","id":"3900"}],"title":"Pipelines for Ad-hoc Large-scale Text Mining","year":"2015","status":"public","date_updated":"2022-01-06T07:03:39Z","_id":"7568","language":[{"iso":"eng"}],"user_id":"82920"},{"publication":"Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications","citation":{"chicago":"Chen, Wei-Fan, MeiHua Chen, and Lun-Wei Ku. “Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording.” In <i>Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications</i>, 144–53, 2015.","ama":"Chen W-F, Chen M, Ku L-W. Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording. In: <i>Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications</i>. ; 2015:144-153.","short":"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.","bibtex":"@inproceedings{Chen_Chen_Ku_2015, title={Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording}, booktitle={Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications}, author={Chen, Wei-Fan and Chen, MeiHua and Ku, Lun-Wei}, year={2015}, pages={144–153} }","mla":"Chen, Wei-Fan, et al. “Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording.” <i>Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications</i>, 2015, pp. 144–53.","apa":"Chen, W.-F., Chen, M., &#38; Ku, L.-W. (2015). Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording. In <i>Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications</i> (pp. 144–153).","ieee":"W.-F. Chen, M. Chen, and L.-W. Ku, “Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording,” in <i>Proceedings of the Tenth Workshop on Innovative Use of NLP for Building Educational Applications</i>, 2015, pp. 144–153."},"date_created":"2019-11-11T12:21:53Z","type":"conference","department":[{"_id":"600"}],"year":"2015","title":"Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate Wording","status":"public","author":[{"id":"82920","full_name":"Chen, Wei-Fan","last_name":"Chen","first_name":"Wei-Fan"},{"full_name":"Chen, MeiHua","last_name":"Chen","first_name":"MeiHua"},{"full_name":"Ku, Lun-Wei","first_name":"Lun-Wei","last_name":"Ku"}],"date_updated":"2022-01-06T06:52:09Z","main_file_link":[{"url":"https://www.aclweb.org/anthology/W15-0617.pdf"}],"page":"144-153","language":[{"iso":"eng"}],"_id":"14875","user_id":"82920"},{"date_updated":"2022-01-06T06:52:09Z","title":"Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example","status":"public","year":"2015","author":[{"id":"82920","last_name":"Chen","first_name":"Wei-Fan","full_name":"Chen, Wei-Fan"},{"last_name":"Ku","first_name":"Lun-Wei","full_name":"Ku, Lun-Wei"},{"first_name":"Yann-Hui","last_name":"Lee","full_name":"Lee, Yann-Hui"}],"user_id":"82920","main_file_link":[{"url":"https://www.aaai.org/ocs/index.php/SSS/SSS15/paper/viewFile/10270/10093"}],"language":[{"iso":"eng"}],"_id":"14877","extern":"1","publication":"2015 AAAI Spring Symposium Series","citation":{"apa":"Chen, W.-F., Ku, L.-W., &#38; Lee, Y.-H. (2015). Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example. In <i>2015 AAAI Spring Symposium Series</i>.","mla":"Chen, Wei-Fan, et al. “Mining Supportive and Unsupportive Evidence from Facebook Using Anti-Reconstruction of the Nuclear Power Plant as an Example.” <i>2015 AAAI Spring Symposium Series</i>, 2015.","ieee":"W.-F. Chen, L.-W. Ku, and Y.-H. Lee, “Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example,” in <i>2015 AAAI Spring Symposium Series</i>, 2015.","chicago":"Chen, Wei-Fan, Lun-Wei Ku, and Yann-Hui Lee. “Mining Supportive and Unsupportive Evidence from Facebook Using Anti-Reconstruction of the Nuclear Power Plant as an Example.” In <i>2015 AAAI Spring Symposium Series</i>, 2015.","short":"W.-F. Chen, L.-W. Ku, Y.-H. Lee, in: 2015 AAAI Spring Symposium Series, 2015.","ama":"Chen W-F, Ku L-W, Lee Y-H. Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example. In: <i>2015 AAAI Spring Symposium Series</i>. ; 2015.","bibtex":"@inproceedings{Chen_Ku_Lee_2015, title={Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as an Example}, booktitle={2015 AAAI Spring Symposium Series}, author={Chen, Wei-Fan and Ku, Lun-Wei and Lee, Yann-Hui}, year={2015} }"},"type":"conference","department":[{"_id":"600"}],"date_created":"2019-11-11T12:24:50Z"},{"type":"conference","department":[{"_id":"600"}],"date_created":"2019-11-11T12:25:52Z","publication":"International Conference on HCI in Business","citation":{"ieee":"W.-F. Chen, Y.-H. Lee, and L.-W. Ku, “Topic-based Stance Mining for Social Media Texts,” in <i>International Conference on HCI in Business</i>, 2015, pp. 22–33.","apa":"Chen, W.-F., Lee, Y.-H., &#38; Ku, L.-W. (2015). Topic-based Stance Mining for Social Media Texts. In <i>International Conference on HCI in Business</i> (pp. 22–33).","chicago":"Chen, Wei-Fan, Yann-Hui Lee, and Lun-Wei Ku. “Topic-Based Stance Mining for Social Media Texts.” In <i>International Conference on HCI in Business</i>, 22–33, 2015.","short":"W.-F. Chen, Y.-H. Lee, L.-W. Ku, in: International Conference on HCI in Business, 2015, pp. 22–33.","mla":"Chen, Wei-Fan, et al. “Topic-Based Stance Mining for Social Media Texts.” <i>International Conference on HCI in Business</i>, 2015, pp. 22–33.","bibtex":"@inproceedings{Chen_Lee_Ku_2015, title={Topic-based Stance Mining for Social Media Texts}, booktitle={International Conference on HCI in Business}, author={Chen, Wei-Fan and Lee, Yann-Hui and Ku, Lun-Wei}, year={2015}, pages={22–33} }","ama":"Chen W-F, Lee Y-H, Ku L-W. Topic-based Stance Mining for Social Media Texts. In: <i>International Conference on HCI in Business</i>. ; 2015:22-33."},"user_id":"82920","page":"22-33","main_file_link":[{"url":"http://www.iis.sinica.edu.tw/papers/lwku/18917-F.pdf"}],"_id":"14878","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:52:09Z","year":"2015","title":"Topic-based Stance Mining for Social Media Texts","status":"public","author":[{"full_name":"Chen, Wei-Fan","first_name":"Wei-Fan","last_name":"Chen","id":"82920"},{"first_name":"Yann-Hui","last_name":"Lee","full_name":"Lee, Yann-Hui"},{"full_name":"Ku, Lun-Wei","last_name":"Ku","first_name":"Lun-Wei"}]},{"author":[{"id":"82920","full_name":"Chen, Wei-Fan","first_name":"Wei-Fan","last_name":"Chen"},{"full_name":"Chen, Mei-Hua","last_name":"Chen","first_name":"Mei-Hua"},{"full_name":"Chen, Ming-Lung","last_name":"Chen","first_name":"Ming-Lung"},{"last_name":"Ku","first_name":"Lun-Wei","full_name":"Ku, Lun-Wei"}],"title":"A Computer-assistance Learning System for Emotional Wording","status":"public","year":"2015","intvolume":"        28","date_updated":"2022-01-06T06:52:09Z","_id":"14879","language":[{"iso":"eng"}],"publisher":"IEEE","page":"1093-1104","main_file_link":[{"url":"https://ieeexplore.ieee.org/iel7/69/4358933/07355346.pdf"}],"volume":28,"user_id":"82920","citation":{"mla":"Chen, Wei-Fan, et al. “A Computer-Assistance Learning System for Emotional Wording.” <i>IEEE Transactions on Knowledge and Data Engineering</i>, vol. 28, no. 5, IEEE, 2015, pp. 1093–104.","ama":"Chen W-F, Chen M-H, Chen M-L, Ku L-W. A Computer-assistance Learning System for Emotional Wording. <i>IEEE Transactions on Knowledge and Data Engineering</i>. 2015;28(5):1093-1104.","bibtex":"@article{Chen_Chen_Chen_Ku_2015, title={A Computer-assistance Learning System for Emotional Wording}, volume={28}, number={5}, journal={IEEE Transactions on Knowledge and Data Engineering}, publisher={IEEE}, author={Chen, Wei-Fan and Chen, Mei-Hua and Chen, Ming-Lung and Ku, Lun-Wei}, year={2015}, pages={1093–1104} }","apa":"Chen, W.-F., Chen, M.-H., Chen, M.-L., &#38; Ku, L.-W. (2015). A Computer-assistance Learning System for Emotional Wording. <i>IEEE Transactions on Knowledge and Data Engineering</i>, <i>28</i>(5), 1093–1104.","ieee":"W.-F. Chen, M.-H. Chen, M.-L. Chen, and L.-W. Ku, “A Computer-assistance Learning System for Emotional Wording,” <i>IEEE Transactions on Knowledge and Data Engineering</i>, vol. 28, no. 5, pp. 1093–1104, 2015.","chicago":"Chen, Wei-Fan, Mei-Hua Chen, Ming-Lung Chen, and Lun-Wei Ku. “A Computer-Assistance Learning System for Emotional Wording.” <i>IEEE Transactions on Knowledge and Data Engineering</i> 28, no. 5 (2015): 1093–1104.","short":"W.-F. Chen, M.-H. Chen, M.-L. Chen, L.-W. Ku, IEEE Transactions on Knowledge and Data Engineering 28 (2015) 1093–1104."},"issue":"5","publication":"IEEE Transactions on Knowledge and Data Engineering","date_created":"2019-11-11T12:27:00Z","department":[{"_id":"600"}],"type":"journal_article"},{"date_created":"2019-11-11T12:23:45Z","department":[{"_id":"600"}],"type":"conference","citation":{"chicago":"Chen, Mei-Hua, Wei-Fan Chen, and Lun-Wei Ku. “Technology Enhanced Emotion Expression Learning.” In <i>Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI)</i>, 2015.","short":"M.-H. Chen, W.-F. Chen, L.-W. Ku, in: Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI), 2015.","apa":"Chen, M.-H., Chen, W.-F., &#38; Ku, L.-W. (2015). Technology Enhanced Emotion Expression Learning. <i>Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI)</i>.","ieee":"M.-H. Chen, W.-F. Chen, and L.-W. Ku, “Technology Enhanced Emotion Expression Learning,” 2015.","ama":"Chen M-H, Chen W-F, Ku L-W. Technology Enhanced Emotion Expression Learning. In: <i>Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI)</i>. ; 2015.","bibtex":"@inproceedings{Chen_Chen_Ku_2015, title={Technology Enhanced Emotion Expression Learning}, booktitle={Proceedings of the sixth joint Foreign Language Education and Technology Conference (FLEAT VI)}, author={Chen, Mei-Hua and Chen, Wei-Fan and Ku, Lun-Wei}, year={2015} }","mla":"Chen, Mei-Hua, et al. “Technology Enhanced Emotion Expression Learning.” <i>Proceedings of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT VI)</i>, 2015."},"publication":"Proceedings of the sixth joint Foreign Language Education and Technology Conference (FLEAT VI)","extern":"1","language":[{"iso":"eng"}],"_id":"14876","user_id":"82920","author":[{"last_name":"Chen","first_name":"Mei-Hua","full_name":"Chen, Mei-Hua"},{"full_name":"Chen, Wei-Fan","last_name":"Chen","first_name":"Wei-Fan","id":"82920"},{"first_name":"Lun-Wei","last_name":"Ku","full_name":"Ku, Lun-Wei"}],"year":"2015","status":"public","title":"Technology Enhanced Emotion Expression Learning","date_updated":"2022-11-10T09:17:00Z"},{"publication":"Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics","citation":{"ieee":"H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, and T. Palakarska, “A Review Corpus for Argumentation Analysis,” in <i>Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics</i>, 2014, pp. 115–127.","mla":"Wachsmuth, Henning, et al. “A Review Corpus for Argumentation Analysis.” <i>Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics</i>, 2014, pp. 115–127.","apa":"Wachsmuth, H., Trenkmann, M., Stein, B., Engels, G., &#38; Palakarska, T. (2014). A Review Corpus for Argumentation Analysis. In <i>Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics</i> (pp. 115–127).","bibtex":"@inproceedings{Wachsmuth_Trenkmann_Stein_Engels_Palakarska_2014, title={A Review Corpus for Argumentation Analysis}, booktitle={Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics}, author={Wachsmuth, Henning and Trenkmann, Martin and Stein, Benno and Engels, Gregor and Palakarska, Tsvetomira}, year={2014}, pages={115–127} }","chicago":"Wachsmuth, Henning, Martin Trenkmann, Benno Stein, Gregor Engels, and Tsvetomira Palakarska. “A Review Corpus for Argumentation Analysis.” In <i>Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics</i>, 115–127, 2014.","short":"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.","ama":"Wachsmuth H, Trenkmann M, Stein B, Engels G, Palakarska T. A Review Corpus for Argumentation Analysis. In: <i>Proceedings of the 15th International Conference on Intelligent Text Processing and Computational Linguistics</i>. ; 2014:115–127."},"date_created":"2020-10-20T13:47:30Z","type":"conference","department":[{"_id":"600"}],"title":"A Review Corpus for Argumentation Analysis","year":"2014","status":"public","author":[{"full_name":"Wachsmuth, Henning","first_name":"Henning","last_name":"Wachsmuth","id":"3900"},{"full_name":"Trenkmann, Martin","first_name":"Martin","last_name":"Trenkmann"},{"full_name":"Stein, Benno","last_name":"Stein","first_name":"Benno"},{"full_name":"Engels, Gregor","last_name":"Engels","first_name":"Gregor","id":"107"},{"full_name":"Palakarska, Tsvetomira","first_name":"Tsvetomira","last_name":"Palakarska"}],"date_updated":"2022-01-06T06:54:20Z","page":"115–127","language":[{"iso":"eng"}],"_id":"20142","user_id":"82920"},{"issue":"12","publication":"Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment","citation":{"mla":"Brüseke, Frank, et al. “PBlaman: Performance Blame Analysis Based on Palladio Contracts.” <i>Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment</i>, no. 12, 2014, pp. 1975–2004.","bibtex":"@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} }","ama":"Brüseke F, Wachsmuth H, Engels G, Becker S. PBlaman: performance blame analysis based on Palladio contracts. In: <i>Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment</i>. ; 2014:1975-2004.","ieee":"F. Brüseke, H. Wachsmuth, G. Engels, and S. Becker, “PBlaman: performance blame analysis based on Palladio contracts,” in <i>Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment</i>, 2014, no. 12, pp. 1975–2004.","apa":"Brüseke, F., Wachsmuth, H., Engels, G., &#38; Becker, S. (2014). PBlaman: performance blame analysis based on Palladio contracts. In <i>Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment</i> (pp. 1975–2004).","chicago":"Brüseke, Frank, Henning Wachsmuth, Gregor Engels, and Steffen Becker. “PBlaman: Performance Blame Analysis Based on Palladio Contracts.” In <i>Proceedings of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment</i>, 1975–2004, 2014.","short":"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."},"date_created":"2018-08-02T13:38:28Z","type":"conference","department":[{"_id":"600"}],"year":"2014","status":"public","title":"PBlaman: performance blame analysis based on Palladio contracts","author":[{"full_name":"Brüseke, Frank","first_name":"Frank","last_name":"Brüseke"},{"id":"3900","last_name":"Wachsmuth","first_name":"Henning","full_name":"Wachsmuth, Henning"},{"last_name":"Engels","first_name":"Gregor","full_name":"Engels, Gregor"},{"full_name":"Becker, Steffen","last_name":"Becker","first_name":"Steffen"}],"date_updated":"2022-01-06T06:59:36Z","page":"1975-2004","language":[{"iso":"eng"}],"_id":"3805","user_id":"82920"},{"department":[{"_id":"600"}],"type":"conference","date_created":"2018-08-11T16:13:24Z","citation":{"chicago":"Wachsmuth, Henning, Martin Trenkmann, Benno Stein, and Gregor Engels. “Modeling Review Argumentation for Robust Sentiment Analysis.” In <i>Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers</i>, 553–64, 2014.","short":"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.","apa":"Wachsmuth, H., Trenkmann, M., Stein, B., &#38; Engels, G. (2014). Modeling Review Argumentation for Robust Sentiment Analysis. In <i>Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers</i> (pp. 553–564).","ieee":"H. Wachsmuth, M. Trenkmann, B. Stein, and G. Engels, “Modeling Review Argumentation for Robust Sentiment Analysis,” in <i>Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers</i>, 2014, pp. 553–564.","ama":"Wachsmuth H, Trenkmann M, Stein B, Engels G. Modeling Review Argumentation for Robust Sentiment Analysis. 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