

Benjamin Murauer, Michael Tschuggnall, Günther Specht and Julia Brandl: Algorithmic Segmentation of Job Ads Using Textual Analysis. In Computational Linguistics and Intelligent Text Processing, pages 287-300. Springer Nature Switzerland, 2023
@InProceedings{10.1007/978-3-031-23804-8_23, author="Murauer, Benjamin and Tschuggnall, Michael and Specht, G{\"u}nther and Brandl, Julia", editor="Gelbukh, Alexander", title="Algorithmic Segmentation of Job Ads Using Textual Analysis", booktitle="Computational Linguistics and Intelligent Text Processing", year="2023", publisher="Springer Nature Switzerland", address="Cham", pages="287--300", abstract="As job ads are getting more prevalent online, an automated analysis is becoming increasingly important, especially in the field of human resource management. In this paper, we propose an approach to automatically segment job ads by predefined categories like the description of a job or the offering company, which is needed to categorize and quantify different aspects of job ads. Using a manually annotated data set, textual features are extracted for each segment type in a first step and utilized to train state-of-the-art machine learning classification methods. Subsequently, these models are used by iterative algorithms to detect the individual segments. Using several optimization techniques like detecting typical segment start phrases, comprehensive evaluations show promising results.", isbn="978-3-031-23804-8" }
Benjamin Murauer, Michael Tschuggnall and Günther Specht: On the Influence of Machine Translation on Language Origin Obfuscation. In Computational Linguistics and Intelligent Text Processing, pages 320-330. Springer Nature Switzerland, 2023
@InProceedings{10.1007/978-3-031-23793-5_26, author="Murauer, Benjamin and Tschuggnall, Michael and Specht, G{\"u}nther", editor="Gelbukh, Alexander", title="On the Influence of Machine Translation on Language Origin Obfuscation", booktitle="Computational Linguistics and Intelligent Text Processing", year="2023", publisher="Springer Nature Switzerland", address="Cham", pages="320--330", abstract="In the last decade, machine translation has become a popular means to deal with multilingual digital content. By providing higher quality translations, obfuscating the source language of a text becomes more attractive. In this paper, we analyze the ability to detect the source language from the translated output of two widely used commercial machine translation systems by utilizing machine-learning algorithms with basic textual features like n-grams. Evaluations show that the source language can be reconstructed with high accuracy for documents that contain a sufficient amount of translated text. In addition, we analyze how the document size influences the performance of the prediction, as well as how limiting the set of possible source languages improves the classification accuracy.", isbn="978-3-031-23793-5" }
Benjamin Murauer: Universal Grammar Features for Cross-Language Authorship Attribution. PhD thesis, University of Innsbruck, Department of Computer Science, 2022.
@phdthesis{murauer2022dissertation, title={{Universal Grammar Features for Cross-Language Authorship Attribution}}, school = {University of Innsbruck, Department of Computer Science}, author={Benjamin Murauer}, year={2022}, }
Benjamin Murauer and Günther Specht: DT-grams: Structured Dependency Grammar Stylometry for Cross-Language Authorship Attribution. In Proceedings of the 32nd GI-Workshop Grundlagen von Datenbanksysteme (GvDB'21) . 2022
@InProceedings{murauer2022dtgrams, author = {Murauer, Benjamin and Specht, G\"{u}nther}, booktitle = {Proceedings of the 32nd GI-Workshop Grundlagen von Datenbanksysteme (GvDB'21) }, title = {{DT-grams: Structured Dependency Grammar Stylometry for Cross-Language Authorship Attribution}}, year = {2022}, }
Benjamin Murauer and Günther Specht: Developing a Benchmark for Reducing Data Bias in Authorship Attribution. In Proceedings of the Second Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP'21). 2021
@InProceedings{murauer2021authbench, author = {Murauer, Benjamin and Specht, G\"{u}nther}, booktitle = {Proceedings of the Second Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP'21)}, title = {{Developing a Benchmark for Reducing Data Bias in Authorship Attribution}}, year = {2021}, pages = {179--188} }
Benjamin Murauer and Günther Specht: Small-Scale Cross-Language Authorship Attribution on Social Media Comments. In Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021), pages 11-19. 2021
@inproceedings{murauer-specht-2021-small, title = "Small-Scale Cross-Language Authorship Attribution on Social Media Comments", author = "Murauer, Benjamin and Specht, G\"{u}nther", booktitle = "Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)", month = aug, year = "2021", url = "https://aclanthology.org/2021.mtsummit-LoResMT.2", pages = "11--19", year = {2021}, pages = {11--19}, }
Manfred Moosleitner, Benjamin Murauer and Günther Specht: Detecting Conspiracy Tweets using Support Vector Machines. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020.
@inproceedings{mediaeval2020conspiracy, author = {Moosleitner, Manfred and Murauer, Benjamin and Specht, Günther}, booktitle = {Working Notes Proceedings of the MediaEval 2020 Workshop}, month = {12}, publisher = {ceur-ws.org}, title = {Detecting Conspiracy Tweets using Support Vector Machines}, year = {2020} }
Michael Tschuggnall, Benjamin Murauer and Günther Specht: Reduce & Attribute: Two-Step Authorship Attribution for Large-Scale Problems. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 951-960. Association for Computational Linguistics, 2019
@inproceedings{tschuggnall-etal-2019-reduce, title = "Reduce {\textbackslash}{\&} Attribute: Two-Step Authorship Attribution for Large-Scale Problems", author = {Tschuggnall, Michael and Murauer, Benjamin and Specht, G{\"u}nther}, booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/K19-1089", doi = "10.18653/v1/K19-1089", pages = "951--960", }
Benjamin Murauer and Günther Specht: Generating Cross-Domain Text Classification Corpora from Social Media Comments. In 20th Conference and Labs of the Evaluation Forum (CLEF'2019), pages 114-125. Springer International Publishing, 2019
@InProceedings{10.1007/978-3-030-28577-7_7, author="Murauer, Benjamin and Specht, G{\"u}nther", editor="Crestani, Fabio and Braschler, Martin and Savoy, Jacques and Rauber, Andreas and M{\"u}ller, Henning and Losada, David E. and Heinatz B{\"u}rki, Gundula and Cappellato, Linda and Ferro, Nicola", title="Generating Cross-Domain Text Classification Corpora from Social Media Comments", booktitle="20th Conference and Labs of the Evaluation Forum (CLEF'2019)", year="2019", publisher="Springer International Publishing", address="Cham", pages="114--125", isbn="978-3-030-28577-7" }
Benjamin Murauer, Michael Tschuggnall and Günther Specht: Dynamic Parameter Search for Cross-Domain Authorship Attribution. In Working Notes of CLEF. 2018
@article{murauer2018dynamic, title={Dynamic Parameter Search for Cross-Domain Authorship Attribution}, author={Murauer, Benjamin and Tschuggnall, Michael and Specht, G{\"u}nther}, journal={Working Notes of CLEF}, year={2018} }
Benjamin Murauer and Günther Specht: Detecting Music Genre Using Extreme Gradient Boosting. In Companion of the The Web Conference 2018 on The Web Conference 2018, pages 1923-1927. International World Wide Web Conferences Steering Committee, 2018.
@inproceedings{Murauer:2018:DMG:3184558.3191822, author = {Murauer, Benjamin and Specht, G\"{u}nther}, title = {Detecting Music Genre Using Extreme Gradient Boosting}, booktitle = {Companion of the The Web Conference 2018 on The Web Conference 2018}, series = {WWW '18}, year = {2018}, isbn = {978-1-4503-5640-4}, location = {Lyon, France}, pages = {1923--1927}, numpages = {5}, url = {https://doi.org/10.1145/3184558.3191822}, doi = {10.1145/3184558.3191822}, acmid = {3191822}, publisher = {International World Wide Web Conferences Steering Committee}, address = {Republic and Canton of Geneva, Switzerland}, keywords = {gradient boosting, music classification, neural network}, }
Benjamin Murauer, Michael Tschuggnall and Günther Specht: On the Influence of Machine Translation on Language Origin Obfuscation. In Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2018). 2018 (to be published)
@inproceedings{Murauer2018Translation, title={{On the Influence of Machine Translation on Language Origin Obfuscation}}, author={Murauer, Benjamin and Tschuggnall, Michael and Specht, G\"unther}, year={2018}, location={Hanoi, Vietnam}, booktitle={Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing'2018)}, month=3, note={(to be published)} }
Benjamin Murauer, Maximilian Mayerl, Michael Tschuggnall, Eva Zangerle, Martin Pichl and Günther Specht: Hierarchical Multilabel Classification and Voting for Genre Classification. In CEURS Working Notes Proceedings of the MediaEval 2017 Workshop. CEUR-WS.org, 2017
@article{Murauer2017Genre, title={Hierarchical Multilabel Classification and Voting for Genre Classification}, author={Murauer, Benjamin and Mayerl, Maximilian and Tschuggnall, Michael and Zangerle, Eva and Pichl, Martin and Specht, G{\"u}nther}, booktitle={CEURS Working Notes Proceedings of the MediaEval 2017 Workshop}, publisher={CEUR-WS.org}, city={Dublin, Ireland}, year={2017}, url={http://ceur-ws.org/Vol-1984/Mediaeval_2017_paper_41.pdf}, }
Benjamin Murauer, Eva Zangerle, and Günther Specht: A Peer-Based Approach on Analyzing Hacked Twitter Accounts. In Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS 2017), Big Island, Hawaii, USA, January 4-7, 2017, pages 1841-1850. IEEE, 2017.
@inProceedings{hicss17, booktitle ={{50th Hawaii International Conference on System Sciences, {HICSS} 2017, Big Island, Hawaii, USA, January 4-7, 2017}}, title = {{A Peer-Based Approach on Analyzing Hacked Twitter Accounts}}, publisher = {IEEE}, year = {2017}, month = {January}, pages = {1841--1850}, author = {Murauer, Benjamin and Zangerle, Eva and and Specht, G\"unther}, }