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Does my rebuttal matter? Insights from a major NLP conference

Does my rebuttal matter? Insights from a major NLP conferenc...

引用

2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019

作者： Gao, Yang Eger, Steffen Kuznetsov, Ilia Gurevych, Iryna Miyao, Yusuke Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Germany Department of Computer Science Graduate School of Information Science and Technology University of Tokyo Japan

ISBN: (纸本)9781950737130

Peer review is a core element of the scientific process, particularly in conference-centered fields such as ML and NLP. However, only few studies have evaluated its properties empirically. Aiming to fill this gap, we present a corpus that contains over 4k reviews and 1.2k author responses from ACL-2018. We quantitatively and qualitatively assess the corpus. This includes a pilot study on paper weaknesses given by reviewers and on quality of author responses. We then focus on the role of the rebuttal phase, and propose a novel task to predict after-rebuttal (i.e., final) scores from initial reviews and author responses. Although author responses do have a marginal (and statistically significant) influence on the final scores, especially for borderline papers, our results suggest that a reviewer's final score is largely determined by her initial score and the distance to the other reviewers' initial scores. In this context, we discuss the conformity bias inherent to peer reviewing, a bias that has largely been overlooked in previous research. We hope our analyses will help better assess the usefulness of the rebuttal phase in NLP conferences. © 2019 Association for Computational Linguistics

关键词： Natural language processing systems

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How text segmentation algorithms gain from topic models

How text segmentation algorithms gain from topic models

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2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2012

作者： Riedl, Martin Biemann, Chris Ubiquitous Knowledge Processing Lab Computer Science Department Technische Universität Darmstadt Hochschulstrasse 10 DarmstadtD-64289 Germany

ISBN: (纸本)1937284204

This paper introduces a general method to incorporate the LDA Topic Model into text segmentation algorithms. We show that semantic information added by Topic Models significantly improves the performance of two wordbased algorithms, namely TextTiling and C99. Additionally, we introduce the new TopicTiling algorithm that is designed to take better advantage of topic information. We show consistent improvements over word-based methods and achieve state-of-the art performance on a standard dataset. © 2012 Association for Computational Linguistics.

关键词： Semantics

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Using tag semantic network for keyphrase extraction in blogs

Using tag semantic network for keyphrase extraction in blogs

引用

17th ACM Conference on Information and knowledge Management, CIKM'08

作者： Qu, Lizhen Müller, Christof Gurevych, Iryna Ubiquitous Knowledge Processing Lab Computer Science Department Technische Universität Darmstadt HochschulstraBe 10 D-64289 Darmstadt Germany

ISBN: (纸本)9781595939913

Folksonomies provide a comfortable way to search and browse the blogosphere. As the tags in the blogosphere are sparse, ambiguous and too general, this paper proposes both a supervised and an unsupervised approach that extract tags from posts using a tag semantic network. We evaluate the two methods on a blog dataset and observe an improvement in F1-measure from 0.23 to 0.50 when compared to the base line system.

关键词： Blogs

来源：评论

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A reflective view on text similarity

A reflective view on text similarity

引用

8th International Conference on Recent Advances in Natural Language processing, RANLP 2011

作者： Bär, Daniel Zesch, Torsten Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstrasse 10 D-64289 Darmstadt Germany

While the concept of similarity is well grounded in psychology, text similarity is less well-defined. Thus, we analyze text similarity with respect to its definition and the datasets used for evaluation. We formalize text similarity based on the geometric model of conceptual spaces along three dimensions inherent to texts: structure, style, and content. We empirically ground these dimensions in a set of annotation studies, and categorize applications according to these dimensions. Furthermore, we analyze the characteristics of the existing evaluation datasets, and use those datasets to assess the performance of common text similarity measures.

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Wikipedia revision toolkit: Efficiently accessing Wikipedia's edit history

Wikipedia revision toolkit: Efficiently accessing Wikipedia'...

引用

49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL HLT 2011

作者： Ferschke, Oliver Zesch, Torsten Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstrasse 10 D-64289 Darmstadt Germany

ISBN: (纸本)9781932432909

We present an open-source toolkit which allows (i) to reconstruct past states of Wikipedia, and (ii) to efficiently access the edit history of Wikipedia articles. Reconstructing past states of Wikipedia is a prerequisite for reproducing previous experimental work based on Wikipedia. Beyond that, the edit history of Wikipedia articles has been shown to be a valuable knowledge source for NLP, but access is severely impeded by the lack of efficient tools for managing the huge amount of provided data. By using a dedicated storage format, our toolkit massively decreases the data volume to less than 2% of the original size, and at the same time provides an easy-to-use interface to access the revision data. The language-independent design allows to process any language represented in Wikipedia. We expect this work to consolidate NLP research using Wikipedia in general, and to foster research making use of the knowledge encoded in Wikipedia's edit history. © 2011 Association for Computational Linguistics.

关键词： Natural language processing systems

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Wikulu: An extensible architecture for integrating natural language processing techniques with wikis

Wikulu: An extensible architecture for integrating natural l...

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49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL HLT 2011

作者： Bär, Daniel Erbs, Nicolai Zesch, Torsten Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstrasse 10 D-64289 Darmstadt Germany

ISBN: (纸本)9781932432893

We present Wikulu1, a system focusing on supporting wiki users with their everyday tasks by means of an intelligent interface. Wikulu is implemented as an extensible architecture which transparently integrates natural language processing (NLP) techniques with wikis. It is designed to be deployed with any wiki platform, and the current prototype integrates a wide range of NLP algorithms such as keyphrase extraction, link discovery, text segmentation, summarization, or text similarity. Additionally, we show how Wikulu can be applied for visually analyzing the results of NLP algorithms, educational purposes, and enabling semantic wikis. © 2011 Association for Computational Linguistics.

关键词： Semantics

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An architecture to support intelligent user interfaces for wikis by means of natural language processing 09

An architecture to support intelligent user interfaces for w...

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5th International Symposium on Wikis and Open Collaboration, WiKiSym 2009

作者： Hoffart, Johannes Zesch, Torsten Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstraße 10 D-64289 Darmstadt Germany

ISBN: (纸本)9781605587301

We present an architecture for integrating a set of Natural Language processing (NLP) techniques with a wiki platform. This entails support for adding, organizing, and finding content in the wiki. We perform a comprehensive analysis of how NLP techniques can support the user interaction with the wiki, using an intelligent interface to provide suggestions. The architecture is designed to be deployed with any existing wiki platform, especially those used in corporate environments. We implemented a prototype integrating the NLP techniques keyphrase extraction and text segmentation, as well as an improved search engine. The prototype is integrated with two widely used wiki platforms: Media-Wiki and TWiki. Copyright © 2009 ACM.

关键词： Search engines

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Using wiktionary for computing semantic relatedness

Using wiktionary for computing semantic relatedness

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23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08

作者： Zesch, Torsten Müller, Christof Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstraße 10 D-64289 Darmstadt Germany

ISBN: (纸本)9781577353683

We introduce Wiktionary as an emerging lexical semantic resource that can be used as a substitute for expert-made resources in AI applications. We evaluate Wiktionary on the pervasive task of computing semantic relatedness for English and German by means of correlation with human rankings and solving word choice problems. For the first time, we apply a concept vector based measure to a set of different concept representations like Wiktionary pseudo glosses, the first paragraph of Wikipedia articles, English WordNet glosses, and GermaNet pseudo glosses. We show that: (i) Wiktionary is the best lexical semantic resource in the ranking task and performs comparably to other resources in the word choice task, and (ii) the concept vector based approach yields the best results on all datasets in both evaluations. Copyright © 2008, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Semantics

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Graph-theoretic analysis of collaborative knowledge bases in Natural Language processing

Graph-theoretic analysis of collaborative knowledge bases in...

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7th International Semantic Web Conference, ISWC 2008

作者： Garoufi, Konstantina Zesch, Torsten Gurevych, Iryna Ubiquitous Knowledge Processing Lab. Computer Science Department Technische Universität Darmstadt Hochschulstr. 10 D-64289 Darmstadt Germany

We present a graph-theoretic analysis of the topological structures underlying the collaborative knowledge bases Wikipedia and Wiktionary, which are promising uprising resources in Natural Language processing. We contrastively compare them to a conventional linguistic knowledge base, and address the issue of how these Social Web knowledge repositories can be best exploited within the Social-Semantic Web.

关键词： knowledge based systems

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Assessing SRL frameworks with automatic training data expansion 11

Assessing SRL frameworks with automatic training data expans...

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11th Linguistic Annotation Workshop, LAW 2017

作者： Hartmann, Silvana Mújdricza-Maydt, E. Éva Kuznetsov, Ilia Gurevych, Iryna Frank, Anette Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Germany Research Training School AIPHES Department of Computational Linguistics Heidelberg University Germany

ISBN: (纸本)9781945626395

We present the first experiment-based study that explicitly contrasts the three major semantic role labeling frameworks. As a prerequisite, we create a dataset labeled with parallel FrameNet-, PropBank-, and VerbNet-style labels for German. We train a state-of-the-art SRL tool for German for the different annotation styles and provide a comparative analysis across frameworks. We further explore the behavior of the frameworks with automatic training data generation. VerbNet provides larger semantic expressivity than PropBank, and we find that its generalization capacity approaches PropBank in SRL training, but it benefits less from training data expansion than the sparse-data affected FrameNet. © 2017 Association for Computational Linguistics.

关键词： Semantics

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