Paper Group NANR 131
Linguistic Style Accommodation in Disagreements. SlangNet: A WordNet like resource for English Slang. ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages. Improving Neural Translation Models with Linguistic Factors. Solving the AL Chicken-and-Egg Corpus and Model Problem: Model-free Active Learning f …
Linguistic Style Accommodation in Disagreements
| Title | Linguistic Style Accommodation in Disagreements |
| Authors | Elise van der Pol, Sharon Gieske, Raquel Fern{'a}ndez |
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| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/S16-2015/ |
| https://www.aclweb.org/anthology/S16-2015 | |
| PWC | https://paperswithcode.com/paper/linguistic-style-accommodation-in |
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SlangNet: A WordNet like resource for English Slang
| Title | SlangNet: A WordNet like resource for English Slang |
| Authors | Shehzaad Dhuliawala, Diptesh Kanojia, Pushpak Bhattacharyya |
| Abstract | We present a WordNet like structured resource for slang words and neologisms on the internet. The dynamism of language is often an indication that current language technology tools trained on today{'}s data, may not be able to process the language in the future. Our resource could be (1) used to augment the WordNet, (2) used in several Natural Language Processing (NLP) applications which make use of noisy data on the internet like Information Retrieval and Web Mining. Such a resource can also be used to distinguish slang word senses from conventional word senses. To stimulate similar innovations widely in the NLP community, we test the efficacy of our resource for detecting slang using standard bag of words Word Sense Disambiguation (WSD) algorithms (Lesk and Extended Lesk) for English data on the internet. |
| Tasks | Information Retrieval, Word Sense Disambiguation |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1686/ |
| https://www.aclweb.org/anthology/L16-1686 | |
| PWC | https://paperswithcode.com/paper/slangnet-a-wordnet-like-resource-for-english |
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ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages
| Title | ANEW+: Automatic Expansion and Validation of Affective Norms of Words Lexicons in Multiple Languages |
| Authors | Samira Shaikh, Kit Cho, Tomek Strzalkowski, Laurie Feldman, John Lien, Ting Liu, George Aaron Broadwell |
| Abstract | In this article we describe our method of automatically expanding an existing lexicon of words with affective valence scores. The automatic expansion process was done in English. In addition, we describe our procedure for automatically creating lexicons in languages where such resources may not previously exist. The foreign languages we discuss in this paper are Spanish, Russian and Farsi. We also describe the procedures to systematically validate our newly created resources. The main contributions of this work are: 1) A general method for expansion and creation of lexicons with scores of words on psychological constructs such as valence, arousal or dominance; and 2) a procedure for ensuring validity of the newly constructed resources. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1180/ |
| https://www.aclweb.org/anthology/L16-1180 | |
| PWC | https://paperswithcode.com/paper/anew-automatic-expansion-and-validation-of |
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Improving Neural Translation Models with Linguistic Factors
| Title | Improving Neural Translation Models with Linguistic Factors |
| Authors | Cong Duy Vu Hoang, Reza Haffari, Trevor Cohn |
| Abstract | |
| Tasks | Constituency Parsing, Dependency Parsing, Feature Engineering, Lemmatization, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/U16-1001/ |
| https://www.aclweb.org/anthology/U16-1001 | |
| PWC | https://paperswithcode.com/paper/improving-neural-translation-models-with |
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Solving the AL Chicken-and-Egg Corpus and Model Problem: Model-free Active Learning for Phenomena-driven Corpus Construction
| Title | Solving the AL Chicken-and-Egg Corpus and Model Problem: Model-free Active Learning for Phenomena-driven Corpus Construction |
| Authors | Dain Kaplan, Neil Rubens, Simone Teufel, Takenobu Tokunaga |
| Abstract | Active learning (AL) is often used in corpus construction (CC) for selecting {``}informative{''} documents for annotation. This is ideal for focusing annotation efforts when all documents cannot be annotated, but has the limitation that it is carried out in a closed-loop, selecting points that will improve an existing model. For phenomena-driven and exploratory CC, the lack of existing-models and specific task(s) for using it make traditional AL inapplicable. In this paper we propose a novel method for model-free AL utilising characteristics of phenomena for applying AL to select documents for annotation. The method can also supplement traditional closed-loop AL-based CC to extend the utility of the corpus created beyond a single task. We introduce our tool, MOVE, and show its potential with a real world case-study. | |
| Tasks | Active Learning |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1697/ |
| https://www.aclweb.org/anthology/L16-1697 | |
| PWC | https://paperswithcode.com/paper/solving-the-al-chicken-and-egg-corpus-and |
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Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making
| Title | Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making |
| Authors | Himabindu Lakkaraju, Jure Leskovec |
| Abstract | We propose Confusions over Time (CoT), a novel generative framework which facilitates a multi-granular analysis of the decision making process. The CoT not only models the confusions or error properties of individual decision makers and their evolution over time, but also allows us to obtain diagnostic insights into the collective decision making process in an interpretable manner. To this end, the CoT models the confusions of the decision makers and their evolution over time via time-dependent confusion matrices. Interpretable insights are obtained by grouping similar decision makers (and items being judged) into clusters and representing each such cluster with an appropriate prototype and identifying the most important features characterizing the cluster via a subspace feature indicator vector. Experimentation with real world data on bail decisions, asthma treatments, and insurance policy approval decisions demonstrates that CoT can accurately model and explain the confusions of decision makers and their evolution over time. |
| Tasks | Decision Making |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6234-confusions-over-time-an-interpretable-bayesian-model-to-characterize-trends-in-decision-making |
| http://papers.nips.cc/paper/6234-confusions-over-time-an-interpretable-bayesian-model-to-characterize-trends-in-decision-making.pdf | |
| PWC | https://paperswithcode.com/paper/confusions-over-time-an-interpretable |
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Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction
| Title | Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction |
| Authors | Behrang QasemiZadeh, Laura Kallmeyer |
| Abstract | |
| Tasks | Dimensionality Reduction, Semantic Textual Similarity, Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/S16-2024/ |
| https://www.aclweb.org/anthology/S16-2024 | |
| PWC | https://paperswithcode.com/paper/random-positive-only-projections-ppmi-enabled |
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Morphological reinflection with convolutional neural networks
| Title | Morphological reinflection with convolutional neural networks |
| Authors | Robert {"O}stling |
| Abstract | |
| Tasks | Machine Translation, Morphological Analysis |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2003/ |
| https://www.aclweb.org/anthology/W16-2003 | |
| PWC | https://paperswithcode.com/paper/morphological-reinflection-with-convolutional |
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Commonsense Knowledge Base Completion
| Title | Commonsense Knowledge Base Completion |
| Authors | Xiang Li, Aynaz Taheri, Lifu Tu, Kevin Gimpel |
| Abstract | |
| Tasks | Knowledge Base Completion |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1137/ |
| https://www.aclweb.org/anthology/P16-1137 | |
| PWC | https://paperswithcode.com/paper/commonsense-knowledge-base-completion |
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Universal dependencies for Uyghur
| Title | Universal dependencies for Uyghur |
| Authors | Marhaba Eli, Weinila Mushajiang, Tuergen Yibulayin, Kahaerjiang Abiderexiti, Yan Liu |
| Abstract | The Universal Dependencies (UD) Project seeks to build a cross-lingual studies of treebanks, linguistic structures and parsing. Its goal is to create a set of multilingual harmonized treebanks that are designed according to a universal annotation scheme. In this paper, we report on the conversion of the Uyghur dependency treebank to a UD version of the treebank which we term the Uyghur Universal Dependency Treebank (UyDT). We present the mapping of the Uyghur dependency treebank{'}s labelling scheme to the UD scheme, along with a clear description of the structural changes required in this conversion. |
| Tasks | Cross-Lingual Transfer |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-5206/ |
| https://www.aclweb.org/anthology/W16-5206 | |
| PWC | https://paperswithcode.com/paper/universal-dependencies-for-uyghur |
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The Power of Optimization from Samples
| Title | The Power of Optimization from Samples |
| Authors | Eric Balkanski, Aviad Rubinstein, Yaron Singer |
| Abstract | We consider the problem of optimization from samples of monotone submodular functions with bounded curvature. In numerous applications, the function optimized is not known a priori, but instead learned from data. What are the guarantees we have when optimizing functions from sampled data? In this paper we show that for any monotone submodular function with curvature c there is a (1 - c)/(1 + c - c^2) approximation algorithm for maximization under cardinality constraints when polynomially-many samples are drawn from the uniform distribution over feasible sets. Moreover, we show that this algorithm is optimal. That is, for any c < 1, there exists a submodular function with curvature c for which no algorithm can achieve a better approximation. The curvature assumption is crucial as for general monotone submodular functions no algorithm can obtain a constant-factor approximation for maximization under a cardinality constraint when observing polynomially-many samples drawn from any distribution over feasible sets, even when the function is statistically learnable. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6447-the-power-of-optimization-from-samples |
| http://papers.nips.cc/paper/6447-the-power-of-optimization-from-samples.pdf | |
| PWC | https://paperswithcode.com/paper/the-power-of-optimization-from-samples |
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Socially-Aware Animated Intelligent Personal Assistant Agent
| Title | Socially-Aware Animated Intelligent Personal Assistant Agent |
| Authors | Yoichi Matsuyama, Arjun Bhardwaj, Ran Zhao, Oscar Romeo, Sushma Akoju, Justine Cassell |
| Abstract | |
| Tasks | Speech Recognition |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3628/ |
| https://www.aclweb.org/anthology/W16-3628 | |
| PWC | https://paperswithcode.com/paper/socially-aware-animated-intelligent-personal |
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Proceedings of the 28th Conference on Computational Linguistics and Speech Processing (ROCLING 2016)
| Title | Proceedings of the 28th Conference on Computational Linguistics and Speech Processing (ROCLING 2016) |
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| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/O16-1000/ |
| https://www.aclweb.org/anthology/O16-1000 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-28th-conference-on |
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基於詞語分布均勻度的核心詞彙選擇之研究(A Study on Dispersion Measures for Core Vocabulary Compilation )[In Chinese]
| Title | 基於詞語分布均勻度的核心詞彙選擇之研究(A Study on Dispersion Measures for Core Vocabulary Compilation )[In Chinese] |
| Authors | Ming-Hong Bai, Jian-Cheng Wu, Ying-Ni Chien, Shu-Ling Huang, Ching-Lung Lin |
| Abstract | |
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| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/O16-1007/ |
| https://www.aclweb.org/anthology/O16-1007 | |
| PWC | https://paperswithcode.com/paper/ao14eeaaa-aaaoc-aea12e-a1c-ca-study-on |
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Crowdsourcing Experiment Designs for Chinese Word Sense Annotation
| Title | Crowdsourcing Experiment Designs for Chinese Word Sense Annotation |
| Authors | Tzu-Yun Huang, Hsiao-Han Wu, Chia-Chen Lee, Shao-Man Lee, Guan-Wei Li, Shu-Kai Hsieh |
| Abstract | |
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| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/O16-1009/ |
| https://www.aclweb.org/anthology/O16-1009 | |
| PWC | https://paperswithcode.com/paper/crowdsourcing-experiment-designs-for-chinese |
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