Martin Franz


2020

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The TechQA Dataset
Vittorio Castelli | Rishav Chakravarti | Saswati Dana | Anthony Ferritto | Radu Florian | Martin Franz | Dinesh Garg | Dinesh Khandelwal | Scott McCarley | Michael McCawley | Mohamed Nasr | Lin Pan | Cezar Pendus | John Pitrelli | Saurabh Pujar | Salim Roukos | Andrzej Sakrajda | Avi Sil | Rosario Uceda-Sosa | Todd Ward | Rong Zhang
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

We introduce TECHQA, a domain-adaptation question answering dataset for the technical support domain. The TECHQA corpus highlights two real-world issues from the automated customer support domain. First, it contains actual questions posed by users on a technical forum, rather than questions generated specifically for a competition or a task. Second, it has a real-world size – 600 training, 310 dev, and 490 evaluation question/answer pairs – thus reflecting the cost of creating large labeled datasets with actual data. Hence, TECHQA is meant to stimulate research in domain adaptation rather than as a resource to build QA systems from scratch. TECHQA was obtained by crawling the IBMDeveloper and DeveloperWorks forums for questions with accepted answers provided in an IBM Technote—a technical document that addresses a specific technical issue. We also release a collection of the 801,998 Technotes available on the web as of April 4, 2019 as a companion resource that can be used to learn representations of the IT domain language.

2010

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Learning to Predict Readability using Diverse Linguistic Features
Rohit Kate | Xiaoqiang Luo | Siddharth Patwardhan | Martin Franz | Radu Florian | Raymond Mooney | Salim Roukos | Chris Welty
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)

2003

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TIPS: A Translingual Information Processing System
Yaser Al-Onaizan | Radu Florian | Martin Franz | Hany Hassan | Young-Suk Lee | J. Scott McCarley | Kishore Papineni | Salim Roukos | Jeffrey Sorensen | Christoph Tillmann | Todd Ward | Fei Xia
Companion Volume of the Proceedings of HLT-NAACL 2003 - Demonstrations

2001

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Question Answering Using Maximum-Entropy Components
Abraham Ittycheriah | Martin Franz | Wei-Jing Zhu | Adwait Ratnaparkhi
Second Meeting of the North American Chapter of the Association for Computational Linguistics