---
_id: '3880'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: 'Wachsmuth H. Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse. In:
Ausgezeichnete Informatikdissertationen 2015. ; 2016:329-338.'
apa: Wachsmuth, H. (2016). Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse.
In Ausgezeichnete Informatikdissertationen 2015 (pp. 329–338).
bibtex: '@inproceedings{Wachsmuth_2016, title={Pipelines Für Effiziente und Robuste
Ad-hoc Textanalyse}, booktitle={Ausgezeichnete Informatikdissertationen 2015},
author={Wachsmuth, Henning}, year={2016}, pages={329–338} }'
chicago: Wachsmuth, Henning. “Pipelines Für Effiziente Und Robuste Ad-Hoc Textanalyse.”
In Ausgezeichnete Informatikdissertationen 2015, 329–38, 2016.
ieee: H. Wachsmuth, “Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse,” in
Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329–338.
mla: Wachsmuth, Henning. “Pipelines Für Effiziente Und Robuste Ad-Hoc Textanalyse.”
Ausgezeichnete Informatikdissertationen 2015, 2016, pp. 329–38.
short: 'H. Wachsmuth, in: Ausgezeichnete Informatikdissertationen 2015, 2016, pp.
329–338.'
date_created: 2018-08-11T16:16:00Z
date_updated: 2022-01-06T06:59:47Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://dl.gi.de/bitstream/handle/20.500.12116/4595/329.pdf?sequence=1
page: 329-338
publication: Ausgezeichnete Informatikdissertationen 2015
publication_identifier:
isbn:
- 978-3-88579-975-7
status: public
title: Pipelines Für Effiziente und Robuste Ad-hoc Textanalyse
type: conference
user_id: '82920'
year: '2016'
...
---
_id: '14881'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: 'Chen W-F, Ku L-W. UTCNN: a Deep Learning Model of Stance Classification on
Social Media Text. In: Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics. ; 2016:1635-1645.'
apa: 'Chen, W.-F., & Ku, L.-W. (2016). UTCNN: a Deep Learning Model of Stance
Classification on Social Media Text. In Proceedings of COLING 2016, the 26th
International Conference on Computational Linguistics (pp. 1635–1645).'
bibtex: '@inproceedings{Chen_Ku_2016, title={UTCNN: a Deep Learning Model of Stance
Classification on Social Media Text}, booktitle={Proceedings of COLING 2016, the
26th International Conference on Computational Linguistics}, author={Chen, Wei-Fan
and Ku, Lun-Wei}, year={2016}, pages={1635–1645} }'
chicago: 'Chen, Wei-Fan, and Lun-Wei Ku. “UTCNN: A Deep Learning Model of Stance
Classification on Social Media Text.” In Proceedings of COLING 2016, the 26th
International Conference on Computational Linguistics, 1635–45, 2016.'
ieee: 'W.-F. Chen and L.-W. Ku, “UTCNN: a Deep Learning Model of Stance Classification
on Social Media Text,” in Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics, 2016, pp. 1635–1645.'
mla: 'Chen, Wei-Fan, and Lun-Wei Ku. “UTCNN: A Deep Learning Model of Stance Classification
on Social Media Text.” Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics, 2016, pp. 1635–45.'
short: 'W.-F. Chen, L.-W. Ku, in: Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics, 2016, pp. 1635–1645.'
date_created: 2019-11-11T12:28:24Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
extern: '1'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/C16-1154.pdf
page: 1635-1645
publication: Proceedings of COLING 2016, the 26th International Conference on Computational
Linguistics
status: public
title: 'UTCNN: a Deep Learning Model of Stance Classification on Social Media Text'
type: conference
user_id: '82920'
year: '2016'
...
---
_id: '14882'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Fang-Yu
full_name: Lin, Fang-Yu
last_name: Lin
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: 'Chen W-F, Lin F-Y, Ku L-W. WordForce: Visualizing Controversial Words in Debates.
In: Proceedings of COLING 2016, the 26th International Conference on Computational
Linguistics: System Demonstrations. ; 2016:273-277.'
apa: 'Chen, W.-F., Lin, F.-Y., & Ku, L.-W. (2016). WordForce: Visualizing Controversial
Words in Debates. In Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: System Demonstrations (pp. 273–277).'
bibtex: '@inproceedings{Chen_Lin_Ku_2016, title={WordForce: Visualizing Controversial
Words in Debates}, booktitle={Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics: System Demonstrations}, author={Chen,
Wei-Fan and Lin, Fang-Yu and Ku, Lun-Wei}, year={2016}, pages={273–277} }'
chicago: 'Chen, Wei-Fan, Fang-Yu Lin, and Lun-Wei Ku. “WordForce: Visualizing Controversial
Words in Debates.” In Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: System Demonstrations, 273–77, 2016.'
ieee: 'W.-F. Chen, F.-Y. Lin, and L.-W. Ku, “WordForce: Visualizing Controversial
Words in Debates,” in Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: System Demonstrations, 2016, pp. 273–277.'
mla: 'Chen, Wei-Fan, et al. “WordForce: Visualizing Controversial Words in Debates.”
Proceedings of COLING 2016, the 26th International Conference on Computational
Linguistics: System Demonstrations, 2016, pp. 273–77.'
short: 'W.-F. Chen, F.-Y. Lin, L.-W. Ku, in: Proceedings of COLING 2016, the 26th
International Conference on Computational Linguistics: System Demonstrations,
2016, pp. 273–277.'
date_created: 2019-11-11T12:29:14Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
extern: '1'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/C16-2057.pdf
page: 273-277
publication: 'Proceedings of COLING 2016, the 26th International Conference on Computational
Linguistics: System Demonstrations'
status: public
title: 'WordForce: Visualizing Controversial Words in Debates'
type: conference
user_id: '82920'
year: '2016'
...
---
_id: '14883'
author:
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
citation:
ama: 'Ku L-W, Chen W-F. Chinese Textual Sentiment Analysis: Datasets, Resources
and Tools. In: Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: Tutorial Abstracts. ; 2016:5-8.'
apa: 'Ku, L.-W., & Chen, W.-F. (2016). Chinese Textual Sentiment Analysis: Datasets,
Resources and Tools. In Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics: Tutorial Abstracts (pp. 5–8).'
bibtex: '@inproceedings{Ku_Chen_2016, title={Chinese Textual Sentiment Analysis:
Datasets, Resources and Tools}, booktitle={Proceedings of COLING 2016, the 26th
International Conference on Computational Linguistics: Tutorial Abstracts}, author={Ku,
Lun-Wei and Chen, Wei-Fan}, year={2016}, pages={5–8} }'
chicago: 'Ku, Lun-Wei, and Wei-Fan Chen. “Chinese Textual Sentiment Analysis: Datasets,
Resources and Tools.” In Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics: Tutorial Abstracts, 5–8, 2016.'
ieee: 'L.-W. Ku and W.-F. Chen, “Chinese Textual Sentiment Analysis: Datasets, Resources
and Tools,” in Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.'
mla: 'Ku, Lun-Wei, and Wei-Fan Chen. “Chinese Textual Sentiment Analysis: Datasets,
Resources and Tools.” Proceedings of COLING 2016, the 26th International Conference
on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.'
short: 'L.-W. Ku, W.-F. Chen, in: Proceedings of COLING 2016, the 26th International
Conference on Computational Linguistics: Tutorial Abstracts, 2016, pp. 5–8.'
date_created: 2019-11-11T12:30:04Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
extern: '1'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/C16-3002.pdf
page: 5-8
publication: 'Proceedings of COLING 2016, the 26th International Conference on Computational
Linguistics: Tutorial Abstracts'
status: public
title: 'Chinese Textual Sentiment Analysis: Datasets, Resources and Tools'
type: conference_abstract
user_id: '82920'
year: '2016'
...
---
_id: '3815'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Johannes
full_name: Kiesel, Johannes
last_name: Kiesel
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
citation:
ama: 'Wachsmuth H, Kiesel J, Stein B. Sentiment Flow - A General Model of Web Review
Argumentation. In: Tsujii J, Hajic J, eds. Proceedings of the 2015 Conference
on Empirical Methods in Natural Language Processing. Lecture Notes in Computer
Science. ; 2015:601-611. doi:10.18653/v1/D15-1072'
apa: Wachsmuth, H., Kiesel, J., & Stein, B. (2015). Sentiment Flow - A General
Model of Web Review Argumentation. In J. Tsujii & J. Hajic (Eds.), Proceedings
of the 2015 Conference on Empirical Methods in Natural Language Processing
(pp. 601–611). https://doi.org/10.18653/v1/D15-1072
bibtex: '@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} }'
chicago: Wachsmuth, Henning, Johannes Kiesel, and Benno Stein. “Sentiment Flow -
A General Model of Web Review Argumentation.” In Proceedings of the 2015 Conference
on Empirical Methods in Natural Language Processing, edited by Junichi Tsujii
and Jan Hajic, 601–11. Lecture Notes in Computer Science, 2015. https://doi.org/10.18653/v1/D15-1072.
ieee: H. Wachsmuth, J. Kiesel, and B. Stein, “Sentiment Flow - A General Model of
Web Review Argumentation,” in Proceedings of the 2015 Conference on Empirical
Methods in Natural Language Processing, 2015, pp. 601–611.
mla: Wachsmuth, Henning, et al. “Sentiment Flow - A General Model of Web Review
Argumentation.” Proceedings of the 2015 Conference on Empirical Methods in
Natural Language Processing, edited by Junichi Tsujii and Jan Hajic, 2015,
pp. 601–11, doi:10.18653/v1/D15-1072.
short: '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.'
date_created: 2018-08-02T13:38:41Z
date_updated: 2022-01-06T06:59:37Z
department:
- _id: '600'
doi: 10.18653/v1/D15-1072
editor:
- first_name: Junichi
full_name: Tsujii, Junichi
last_name: Tsujii
- first_name: Jan
full_name: Hajic, Jan
last_name: Hajic
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/D15-1072.pdf
page: 601-611
publication: Proceedings of the 2015 Conference on Empirical Methods in Natural Language
Processing
publication_identifier:
isbn:
- 978-3-319-25740-2
series_title: Lecture Notes in Computer Science
status: public
title: Sentiment Flow - A General Model of Web Review Argumentation
type: conference
user_id: '82920'
year: '2015'
...
---
_id: '3879'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: Wachsmuth H. Text Analysis Pipelines - Towards Ad-Hoc Large-Scale Text Mining.;
2015. doi:http://dx.doi.org/10.1007/978-3-319-25741-9
apa: Wachsmuth, H. (2015). Text Analysis Pipelines - Towards Ad-hoc Large-scale
Text Mining. http://dx.doi.org/10.1007/978-3-319-25741-9
bibtex: '@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} }'
chicago: Wachsmuth, Henning. Text Analysis Pipelines - Towards Ad-Hoc Large-Scale
Text Mining. Lecture Notes in Computer Science, 2015. http://dx.doi.org/10.1007/978-3-319-25741-9.
ieee: H. Wachsmuth, Text Analysis Pipelines - Towards Ad-hoc Large-scale Text
Mining. 2015.
mla: Wachsmuth, Henning. Text Analysis Pipelines - Towards Ad-Hoc Large-Scale
Text Mining. 2015, doi:http://dx.doi.org/10.1007/978-3-319-25741-9.
short: H. Wachsmuth, Text Analysis Pipelines - Towards Ad-Hoc Large-Scale Text Mining,
2015.
date_created: 2018-08-11T16:15:08Z
date_updated: 2022-01-06T06:59:47Z
department:
- _id: '600'
doi: http://dx.doi.org/10.1007/978-3-319-25741-9
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-319-25740-2
series_title: Lecture Notes in Computer Science
status: public
title: Text Analysis Pipelines - Towards Ad-hoc Large-scale Text Mining
type: book
user_id: '82920'
year: '2015'
...
---
_id: '7568'
abstract:
- lang: eng
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.'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
citation:
ama: Wachsmuth H. Pipelines for Ad-Hoc Large-Scale Text Mining.; 2015.
apa: Wachsmuth, H. (2015). Pipelines for Ad-hoc Large-scale Text Mining.
bibtex: '@book{Wachsmuth_2015, title={Pipelines for Ad-hoc Large-scale Text Mining},
author={Wachsmuth, Henning}, year={2015} }'
chicago: Wachsmuth, Henning. Pipelines for Ad-Hoc Large-Scale Text Mining,
2015.
ieee: H. Wachsmuth, Pipelines for Ad-hoc Large-scale Text Mining. 2015.
mla: Wachsmuth, Henning. Pipelines for Ad-Hoc Large-Scale Text Mining. 2015.
short: H. Wachsmuth, Pipelines for Ad-Hoc Large-Scale Text Mining, 2015.
date_created: 2019-02-06T14:14:29Z
date_updated: 2022-01-06T07:03:39Z
department:
- _id: '66'
- _id: '600'
language:
- iso: eng
related_material:
link:
- relation: confirmation
url: https://webis.de/downloads/publications/papers/wachsmuth_2013.pdf
status: public
title: Pipelines for Ad-hoc Large-scale Text Mining
type: dissertation
user_id: '82920'
year: '2015'
...
---
_id: '14875'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: MeiHua
full_name: Chen, MeiHua
last_name: Chen
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: 'Chen W-F, Chen M, Ku L-W. Embarrassed or Awkward? Ranking Emotion Synonyms
for ESL Learners’ Appropriate Wording. In: Proceedings of the Tenth Workshop
on Innovative Use of NLP for Building Educational Applications. ; 2015:144-153.'
apa: Chen, W.-F., Chen, M., & Ku, L.-W. (2015). Embarrassed or Awkward? Ranking
Emotion Synonyms for ESL Learners’ Appropriate Wording. In Proceedings of the
Tenth Workshop on Innovative Use of NLP for Building Educational Applications
(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}
}'
chicago: Chen, Wei-Fan, MeiHua Chen, and Lun-Wei Ku. “Embarrassed or Awkward? Ranking
Emotion Synonyms for ESL Learners’ Appropriate Wording.” In Proceedings of
the Tenth Workshop on Innovative Use of NLP for Building Educational Applications,
144–53, 2015.
ieee: W.-F. Chen, M. Chen, and L.-W. Ku, “Embarrassed or Awkward? Ranking Emotion
Synonyms for ESL Learners’ Appropriate Wording,” in Proceedings of the Tenth
Workshop on Innovative Use of NLP for Building Educational Applications, 2015,
pp. 144–153.
mla: Chen, Wei-Fan, et al. “Embarrassed or Awkward? Ranking Emotion Synonyms for
ESL Learners’ Appropriate Wording.” Proceedings of the Tenth Workshop on Innovative
Use of NLP for Building Educational Applications, 2015, pp. 144–53.
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.'
date_created: 2019-11-11T12:21:53Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/W15-0617.pdf
page: 144-153
publication: Proceedings of the Tenth Workshop on Innovative Use of NLP for Building
Educational Applications
status: public
title: Embarrassed or Awkward? Ranking Emotion Synonyms for ESL Learners’ Appropriate
Wording
type: conference
user_id: '82920'
year: '2015'
...
---
_id: '14877'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
- first_name: Yann-Hui
full_name: Lee, Yann-Hui
last_name: Lee
citation:
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:
2015 AAAI Spring Symposium Series. ; 2015.'
apa: Chen, W.-F., Ku, L.-W., & Lee, Y.-H. (2015). Mining Supportive and Unsupportive
Evidence from Facebook Using Anti-reconstruction of the Nuclear Power Plant as
an Example. In 2015 AAAI Spring Symposium Series.
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} }'
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 2015 AAAI Spring Symposium Series, 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 2015 AAAI Spring Symposium Series, 2015.
mla: Chen, Wei-Fan, et al. “Mining Supportive and Unsupportive Evidence from Facebook
Using Anti-Reconstruction of the Nuclear Power Plant as an Example.” 2015 AAAI
Spring Symposium Series, 2015.
short: 'W.-F. Chen, L.-W. Ku, Y.-H. Lee, in: 2015 AAAI Spring Symposium Series,
2015.'
date_created: 2019-11-11T12:24:50Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
extern: '1'
language:
- iso: eng
main_file_link:
- url: https://www.aaai.org/ocs/index.php/SSS/SSS15/paper/viewFile/10270/10093
publication: 2015 AAAI Spring Symposium Series
status: public
title: Mining Supportive and Unsupportive Evidence from Facebook Using Anti-reconstruction
of the Nuclear Power Plant as an Example
type: conference
user_id: '82920'
year: '2015'
...
---
_id: '14878'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Yann-Hui
full_name: Lee, Yann-Hui
last_name: Lee
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: 'Chen W-F, Lee Y-H, Ku L-W. Topic-based Stance Mining for Social Media Texts.
In: International Conference on HCI in Business. ; 2015:22-33.'
apa: Chen, W.-F., Lee, Y.-H., & Ku, L.-W. (2015). Topic-based Stance Mining
for Social Media Texts. In International Conference on HCI in Business
(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} }'
chicago: Chen, Wei-Fan, Yann-Hui Lee, and Lun-Wei Ku. “Topic-Based Stance Mining
for Social Media Texts.” In International Conference on HCI in Business,
22–33, 2015.
ieee: W.-F. Chen, Y.-H. Lee, and L.-W. Ku, “Topic-based Stance Mining for Social
Media Texts,” 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.” International
Conference on HCI in Business, 2015, pp. 22–33.
short: 'W.-F. Chen, Y.-H. Lee, L.-W. Ku, in: International Conference on HCI in
Business, 2015, pp. 22–33.'
date_created: 2019-11-11T12:25:52Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: http://www.iis.sinica.edu.tw/papers/lwku/18917-F.pdf
page: 22-33
publication: International Conference on HCI in Business
status: public
title: Topic-based Stance Mining for Social Media Texts
type: conference
user_id: '82920'
year: '2015'
...
---
_id: '14879'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Ming-Lung
full_name: Chen, Ming-Lung
last_name: Chen
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: Chen W-F, Chen M-H, Chen M-L, Ku L-W. A Computer-assistance Learning System
for Emotional Wording. IEEE Transactions on Knowledge and Data Engineering.
2015;28(5):1093-1104.
apa: Chen, W.-F., Chen, M.-H., Chen, M.-L., & Ku, L.-W. (2015). A Computer-assistance
Learning System for Emotional Wording. IEEE Transactions on Knowledge and Data
Engineering, 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}
}'
chicago: 'Chen, Wei-Fan, Mei-Hua Chen, Ming-Lung Chen, and Lun-Wei Ku. “A Computer-Assistance
Learning System for Emotional Wording.” IEEE Transactions on Knowledge and
Data Engineering 28, no. 5 (2015): 1093–1104.'
ieee: W.-F. Chen, M.-H. Chen, M.-L. Chen, and L.-W. Ku, “A Computer-assistance Learning
System for Emotional Wording,” IEEE Transactions on Knowledge and Data Engineering,
vol. 28, no. 5, pp. 1093–1104, 2015.
mla: Chen, Wei-Fan, et al. “A Computer-Assistance Learning System for Emotional
Wording.” IEEE Transactions on Knowledge and Data Engineering, vol. 28,
no. 5, IEEE, 2015, pp. 1093–104.
short: W.-F. Chen, M.-H. Chen, M.-L. Chen, L.-W. Ku, IEEE Transactions on Knowledge
and Data Engineering 28 (2015) 1093–1104.
date_created: 2019-11-11T12:27:00Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
intvolume: ' 28'
issue: '5'
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/iel7/69/4358933/07355346.pdf
page: 1093-1104
publication: IEEE Transactions on Knowledge and Data Engineering
publisher: IEEE
status: public
title: A Computer-assistance Learning System for Emotional Wording
type: journal_article
user_id: '82920'
volume: 28
year: '2015'
...
---
_id: '14876'
author:
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Lun-Wei
full_name: Ku, Lun-Wei
last_name: Ku
citation:
ama: 'Chen M-H, Chen W-F, Ku L-W. Technology Enhanced Emotion Expression Learning.
In: Proceedings of the Sixth Joint Foreign Language Education and Technology
Conference (FLEAT VI). ; 2015.'
apa: Chen, M.-H., Chen, W.-F., & Ku, L.-W. (2015). Technology Enhanced Emotion
Expression Learning. Proceedings of the Sixth Joint Foreign Language Education
and Technology Conference (FLEAT VI).
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} }'
chicago: Chen, Mei-Hua, Wei-Fan Chen, and Lun-Wei Ku. “Technology Enhanced Emotion
Expression Learning.” In Proceedings of the Sixth Joint Foreign Language Education
and Technology Conference (FLEAT VI), 2015.
ieee: M.-H. Chen, W.-F. Chen, and L.-W. Ku, “Technology Enhanced Emotion Expression
Learning,” 2015.
mla: Chen, Mei-Hua, et al. “Technology Enhanced Emotion Expression Learning.” Proceedings
of the Sixth Joint Foreign Language Education and Technology Conference (FLEAT
VI), 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.'
date_created: 2019-11-11T12:23:45Z
date_updated: 2022-11-10T09:17:00Z
department:
- _id: '600'
extern: '1'
language:
- iso: eng
publication: Proceedings of the sixth joint Foreign Language Education and Technology
Conference (FLEAT VI)
status: public
title: Technology Enhanced Emotion Expression Learning
type: conference
user_id: '82920'
year: '2015'
...
---
_id: '20142'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Martin
full_name: Trenkmann, Martin
last_name: Trenkmann
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
id: '107'
last_name: Engels
- first_name: Tsvetomira
full_name: Palakarska, Tsvetomira
last_name: Palakarska
citation:
ama: 'Wachsmuth H, Trenkmann M, Stein B, Engels G, Palakarska T. A Review Corpus
for Argumentation Analysis. In: Proceedings of the 15th International Conference
on Intelligent Text Processing and Computational Linguistics. ; 2014:115–127.'
apa: Wachsmuth, H., Trenkmann, M., Stein, B., Engels, G., & Palakarska, T. (2014).
A Review Corpus for Argumentation Analysis. In Proceedings of the 15th International
Conference on Intelligent Text Processing and Computational Linguistics (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 Proceedings of
the 15th International Conference on Intelligent Text Processing and Computational
Linguistics, 115–127, 2014.
ieee: H. Wachsmuth, M. Trenkmann, B. Stein, G. Engels, and T. Palakarska, “A Review
Corpus for Argumentation Analysis,” in Proceedings of the 15th International
Conference on Intelligent Text Processing and Computational Linguistics, 2014,
pp. 115–127.
mla: Wachsmuth, Henning, et al. “A Review Corpus for Argumentation Analysis.” Proceedings
of the 15th International Conference on Intelligent Text Processing and Computational
Linguistics, 2014, pp. 115–127.
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.'
date_created: 2020-10-20T13:47:30Z
date_updated: 2022-01-06T06:54:20Z
department:
- _id: '600'
language:
- iso: eng
page: 115–127
publication: Proceedings of the 15th International Conference on Intelligent Text
Processing and Computational Linguistics
status: public
title: A Review Corpus for Argumentation Analysis
type: conference
user_id: '82920'
year: '2014'
...
---
_id: '3805'
author:
- first_name: Frank
full_name: Brüseke, Frank
last_name: Brüseke
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Gregor
full_name: Engels, Gregor
last_name: Engels
- first_name: Steffen
full_name: Becker, Steffen
last_name: Becker
citation:
ama: 'Brüseke F, Wachsmuth H, Engels G, Becker S. PBlaman: performance blame analysis
based on Palladio contracts. In: Proceedings of the 4th International Symposium
on Autonomous Minirobots for Research and Edutainment. ; 2014:1975-2004.'
apa: 'Brüseke, F., Wachsmuth, H., Engels, G., & Becker, S. (2014). PBlaman:
performance blame analysis based on Palladio contracts. In Proceedings of the
4th International Symposium on Autonomous Minirobots for Research and Edutainment
(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} }'
chicago: 'Brüseke, Frank, Henning Wachsmuth, Gregor Engels, and Steffen Becker.
“PBlaman: Performance Blame Analysis Based on Palladio Contracts.” In Proceedings
of the 4th International Symposium on Autonomous Minirobots for Research and Edutainment,
1975–2004, 2014.'
ieee: 'F. Brüseke, H. Wachsmuth, G. Engels, and S. Becker, “PBlaman: performance
blame analysis based on Palladio contracts,” in Proceedings of the 4th International
Symposium on Autonomous Minirobots for Research and Edutainment, 2014, no.
12, pp. 1975–2004.'
mla: 'Brüseke, Frank, et al. “PBlaman: Performance Blame Analysis Based on Palladio
Contracts.” Proceedings of the 4th International Symposium on Autonomous Minirobots
for Research and Edutainment, no. 12, 2014, pp. 1975–2004.'
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
date_updated: 2022-01-06T06:59:36Z
department:
- _id: '600'
issue: '12'
language:
- iso: eng
page: 1975-2004
publication: Proceedings of the 4th International Symposium on Autonomous Minirobots
for Research and Edutainment
status: public
title: 'PBlaman: performance blame analysis based on Palladio contracts'
type: conference
user_id: '82920'
year: '2014'
...
---
_id: '3877'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Martin
full_name: Trenkmann, Martin
last_name: Trenkmann
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
last_name: Engels
citation:
ama: 'Wachsmuth H, Trenkmann M, Stein B, Engels G. Modeling Review Argumentation
for Robust Sentiment Analysis. In: Proceedings of COLING 2014, the 25th International
Conference on Computational Linguistics: Technical Papers. ; 2014:553-564.'
apa: 'Wachsmuth, H., Trenkmann, M., Stein, B., & Engels, G. (2014). Modeling
Review Argumentation for Robust Sentiment Analysis. In Proceedings of COLING
2014, the 25th International Conference on Computational Linguistics: Technical
Papers (pp. 553–564).'
bibtex: '@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} }'
chicago: 'Wachsmuth, Henning, Martin Trenkmann, Benno Stein, and Gregor Engels.
“Modeling Review Argumentation for Robust Sentiment Analysis.” In Proceedings
of COLING 2014, the 25th International Conference on Computational Linguistics:
Technical Papers, 553–64, 2014.'
ieee: 'H. Wachsmuth, M. Trenkmann, B. Stein, and G. Engels, “Modeling Review Argumentation
for Robust Sentiment Analysis,” in Proceedings of COLING 2014, the 25th International
Conference on Computational Linguistics: Technical Papers, 2014, pp. 553–564.'
mla: 'Wachsmuth, Henning, et al. “Modeling Review Argumentation for Robust Sentiment
Analysis.” Proceedings of COLING 2014, the 25th International Conference on
Computational Linguistics: Technical Papers, 2014, pp. 553–64.'
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.'
date_created: 2018-08-11T16:13:24Z
date_updated: 2022-01-06T06:59:47Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/C14-1053.pdf
page: 553-564
publication: 'Proceedings of COLING 2014, the 25th International Conference on Computational
Linguistics: Technical Papers'
status: public
title: Modeling Review Argumentation for Robust Sentiment Analysis
type: conference
user_id: '82920'
year: '2014'
...
---
_id: '3905'
author:
- first_name: Chamsi
full_name: Abu Quba Rana, Chamsi
last_name: Abu Quba Rana
- first_name: Salima
full_name: Hassas, Salima
last_name: Hassas
- first_name: Fayyad
full_name: Usama, Fayyad
last_name: Usama
- first_name: Milad
full_name: Alshomary, Milad
id: '73059'
last_name: Alshomary
- first_name: Christine
full_name: Gertosio, Christine
last_name: Gertosio
citation:
ama: 'Abu Quba Rana C, Hassas S, Usama F, Alshomary M, Gertosio C. iSoNTRE: The
Social Network Transformer into Recommendation Engine. 2014 IEEE/ACS 11th International
Conference on Computer Systems and Applications (AICCSA). 2014:169-175.'
apa: 'Abu Quba Rana, C., Hassas, S., Usama, F., Alshomary, M., & Gertosio, C.
(2014). iSoNTRE: The Social Network Transformer into Recommendation Engine. 2014
IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA),
169–175.'
bibtex: '@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} }'
chicago: 'Abu Quba Rana, Chamsi, Salima Hassas, Fayyad Usama, Milad Alshomary, and
Christine Gertosio. “ISoNTRE: The Social Network Transformer into Recommendation
Engine.” 2014 IEEE/ACS 11th International Conference on Computer Systems and
Applications (AICCSA), 2014, 169–75.'
ieee: 'C. Abu Quba Rana, S. Hassas, F. Usama, M. Alshomary, and C. Gertosio, “iSoNTRE:
The Social Network Transformer into Recommendation Engine,” 2014 IEEE/ACS 11th
International Conference on Computer Systems and Applications (AICCSA), pp.
169–175, 2014.'
mla: 'Abu Quba Rana, Chamsi, et al. “ISoNTRE: The Social Network Transformer into
Recommendation Engine.” 2014 IEEE/ACS 11th International Conference on Computer
Systems and Applications (AICCSA), 2014, pp. 169–75.'
short: 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.
date_created: 2018-08-14T13:35:39Z
date_updated: 2022-01-06T06:59:54Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/document/7073195
page: 169-175
publication: 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications
(AICCSA)
status: public
title: 'iSoNTRE: The Social Network Transformer into Recommendation Engine'
type: journal_article
user_id: '73059'
year: '2014'
...
---
_id: '14874'
author:
- first_name: Mei-Hua
full_name: Chen, Mei-Hua
last_name: Chen
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Lun-Wei
full_name: ' Ku, Lun-Wei'
last_name: ' Ku'
citation:
ama: 'Chen M-H, Chen W-F, Ku L-W. RESOLVE: An Emotion Word Suggestion System Facilitates
Language Learners’ Emotional Expressions. In: Proceedings of the AsiaCALL 2014.
; 2014.'
apa: 'Chen, M.-H., Chen, W.-F., & Ku, L.-W. (2014). RESOLVE: An Emotion Word
Suggestion System Facilitates Language Learners’ Emotional Expressions. In Proceedings
of the AsiaCALL 2014.'
bibtex: '@inproceedings{Chen_Chen_ Ku_2014, title={RESOLVE: An Emotion Word Suggestion
System Facilitates Language Learners’ Emotional Expressions}, booktitle={Proceedings
of the AsiaCALL 2014}, author={Chen, Mei-Hua and Chen, Wei-Fan and Ku, Lun-Wei},
year={2014} }'
chicago: 'Chen, Mei-Hua, Wei-Fan Chen, and Lun-Wei Ku. “RESOLVE: An Emotion Word
Suggestion System Facilitates Language Learners’ Emotional Expressions.” In Proceedings
of the AsiaCALL 2014, 2014.'
ieee: 'M.-H. Chen, W.-F. Chen, and L.-W. Ku, “RESOLVE: An Emotion Word Suggestion
System Facilitates Language Learners’ Emotional Expressions,” in Proceedings
of the AsiaCALL 2014, 2014.'
mla: 'Chen, Mei-Hua, et al. “RESOLVE: An Emotion Word Suggestion System Facilitates
Language Learners’ Emotional Expressions.” Proceedings of the AsiaCALL 2014,
2014.'
short: 'M.-H. Chen, W.-F. Chen, L.-W. Ku, in: Proceedings of the AsiaCALL 2014,
2014.'
date_created: 2019-11-11T12:21:14Z
date_updated: 2022-01-06T06:52:09Z
department:
- _id: '600'
language:
- iso: eng
publication: Proceedings of the AsiaCALL 2014
status: public
title: 'RESOLVE: An Emotion Word Suggestion System Facilitates Language Learners’
Emotional Expressions'
type: conference
user_id: '82920'
year: '2014'
...
---
_id: '3813'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
last_name: Engels
citation:
ama: 'Wachsmuth H, Stein B, Engels G. Learning Efficient Information Extraction
on Heterogeneous Texts. In: Gelbukh A, ed. Proceedings of the Sixth International
Joint Conference on Natural Language Processing. Lecture Notes in Computer
Science. ; 2013:534-542.'
apa: Wachsmuth, H., Stein, B., & Engels, G. (2013). Learning Efficient Information
Extraction on Heterogeneous Texts. In A. Gelbukh (Ed.), Proceedings of the
Sixth International Joint Conference on Natural Language Processing (pp. 534–542).
bibtex: '@inproceedings{Wachsmuth_Stein_Engels_2013, series={Lecture Notes in Computer
Science}, title={Learning Efficient Information Extraction on Heterogeneous Texts},
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} }'
chicago: Wachsmuth, Henning, Benno Stein, and Gregor Engels. “Learning Efficient
Information Extraction on Heterogeneous Texts.” In Proceedings of the Sixth
International Joint Conference on Natural Language Processing, edited by Alexander
Gelbukh, 534–42. Lecture Notes in Computer Science, 2013.
ieee: H. Wachsmuth, B. Stein, and G. Engels, “Learning Efficient Information Extraction
on Heterogeneous Texts,” in Proceedings of the Sixth International Joint Conference
on Natural Language Processing, 2013, pp. 534–542.
mla: Wachsmuth, Henning, et al. “Learning Efficient Information Extraction on Heterogeneous
Texts.” Proceedings of the Sixth International Joint Conference on Natural
Language Processing, edited by Alexander Gelbukh, 2013, pp. 534–42.
short: '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.'
date_created: 2018-08-02T13:38:39Z
date_updated: 2022-01-06T06:59:37Z
department:
- _id: '600'
editor:
- first_name: Alexander
full_name: Gelbukh, Alexander
last_name: Gelbukh
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/I13-1061.pdf
page: 534-542
publication: Proceedings of the Sixth International Joint Conference on Natural Language
Processing
series_title: Lecture Notes in Computer Science
status: public
title: Learning Efficient Information Extraction on Heterogeneous Texts
type: conference
user_id: '82920'
year: '2013'
...
---
_id: '3814'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
- first_name: Gregor
full_name: Engels, Gregor
last_name: Engels
citation:
ama: 'Wachsmuth H, Stein B, Engels G. Information Extraction as a Filtering Task.
In: Proceedings of the 22nd ACM International Conference on Conference on Information
& Knowledge Management. ; 2013:2049-2058.'
apa: Wachsmuth, H., Stein, B., & Engels, G. (2013). Information Extraction as
a Filtering Task. In Proceedings of the 22nd ACM International Conference on
Conference on Information & Knowledge Management (pp. 2049–2058).
bibtex: '@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} }'
chicago: Wachsmuth, Henning, Benno Stein, and Gregor Engels. “Information Extraction
as a Filtering Task.” In Proceedings of the 22nd ACM International Conference
on Conference on Information & Knowledge Management, 2049–58, 2013.
ieee: H. Wachsmuth, B. Stein, and G. Engels, “Information Extraction as a Filtering
Task,” in Proceedings of the 22nd ACM International Conference on Conference
on Information & Knowledge Management, 2013, pp. 2049–2058.
mla: Wachsmuth, Henning, et al. “Information Extraction as a Filtering Task.” Proceedings
of the 22nd ACM International Conference on Conference on Information & Knowledge
Management, 2013, pp. 2049–58.
short: 'H. Wachsmuth, B. Stein, G. Engels, in: Proceedings of the 22nd ACM International
Conference on Conference on Information & Knowledge Management, 2013, pp.
2049–2058.'
date_created: 2018-08-02T13:38:40Z
date_updated: 2022-01-06T06:59:37Z
department:
- _id: '600'
language:
- iso: eng
main_file_link:
- url: https://dl.acm.org/doi/pdf/10.1145/2505515.2505557
page: 2049-2058
publication: Proceedings of the 22nd ACM International Conference on Conference on
Information & Knowledge Management
publication_identifier:
isbn:
- 978-1-4503-2263-8
status: public
title: Information Extraction as a Filtering Task
type: conference
user_id: '82920'
year: '2013'
...
---
_id: '3876'
author:
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Mirko
full_name: Rose, Mirko
last_name: Rose
- first_name: Gregor
full_name: Engels, Gregor
last_name: Engels
citation:
ama: 'Wachsmuth H, Rose M, Engels G. Automatic Pipeline Construction for Real-Time
Annotation. In: Gelbukh A, ed. 14th International Conference on Intelligent
Text Processing and Computational Linguistics. Lecture Notes in Computer Science.
; 2013:38-49.'
apa: Wachsmuth, H., Rose, M., & Engels, G. (2013). Automatic Pipeline Construction
for Real-Time Annotation. In A. Gelbukh (Ed.), 14th International Conference
on Intelligent Text Processing and Computational Linguistics (pp. 38–49).
bibtex: '@inproceedings{Wachsmuth_Rose_Engels_2013, series={Lecture Notes in Computer
Science}, title={Automatic Pipeline Construction for Real-Time Annotation}, 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} }'
chicago: Wachsmuth, Henning, Mirko Rose, and Gregor Engels. “Automatic Pipeline
Construction for Real-Time Annotation.” In 14th International Conference on
Intelligent Text Processing and Computational Linguistics, edited by Alexander
Gelbukh, 38–49. Lecture Notes in Computer Science, 2013.
ieee: H. Wachsmuth, M. Rose, and G. Engels, “Automatic Pipeline Construction for
Real-Time Annotation,” in 14th International Conference on Intelligent Text
Processing and Computational Linguistics, 2013, pp. 38–49.
mla: Wachsmuth, Henning, et al. “Automatic Pipeline Construction for Real-Time Annotation.”
14th International Conference on Intelligent Text Processing and Computational
Linguistics, edited by Alexander Gelbukh, 2013, pp. 38–49.
short: 'H. Wachsmuth, M. Rose, G. Engels, in: A. Gelbukh (Ed.), 14th International
Conference on Intelligent Text Processing and Computational Linguistics, 2013,
pp. 38–49.'
date_created: 2018-08-11T16:12:29Z
date_updated: 2022-01-06T06:59:47Z
department:
- _id: '600'
editor:
- first_name: Alexander
full_name: Gelbukh, Alexander
last_name: Gelbukh
language:
- iso: eng
main_file_link:
- url: https://webis.de/downloads/publications/papers/wachsmuth_2013.pdf
page: 38-49
publication: 14th International Conference on Intelligent Text Processing and Computational
Linguistics
series_title: Lecture Notes in Computer Science
status: public
title: Automatic Pipeline Construction for Real-Time Annotation
type: conference
user_id: '82920'
year: '2013'
...