Paper Group NANR 66
Stylometric Studies based on Tone and Word Length Motifs. Towards Replicability in Parsing. Quantifier Scoping and Semantic Preferences. Probabilistic Path Hamiltonian Monte Carlo. You’ll Never Tweet Alone: Building Sports Match Timelines from Microblog Posts. Metaphor Detection in a Poetry Corpus. DECCA Repurposed: Detecting transcription inconsis …
Stylometric Studies based on Tone and Word Length Motifs
| Title | Stylometric Studies based on Tone and Word Length Motifs |
| Authors | Renkui Hou, Chu-Ren Huang |
| Abstract | |
| Tasks | Text Classification |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/Y17-1011/ |
| https://www.aclweb.org/anthology/Y17-1011 | |
| PWC | https://paperswithcode.com/paper/stylometric-studies-based-on-tone-and-word |
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Towards Replicability in Parsing
| Title | Towards Replicability in Parsing |
| Authors | Daniel Dakota, S K{"u}bler, ra |
| Abstract | We investigate parsing replicability across 7 languages (and 8 treebanks), showing that choices concerning the use of grammatical functions in parsing or evaluation, the influence of the rare word threshold, as well as choices in test sentences and evaluation script options have considerable and often unexpected effects on parsing accuracies. All of those choices need to be carefully documented if we want to ensure replicability. |
| Tasks | |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/R17-1026/ |
| https://doi.org/10.26615/978-954-452-049-6_026 | |
| PWC | https://paperswithcode.com/paper/towards-replicability-in-parsing |
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Quantifier Scoping and Semantic Preferences
| Title | Quantifier Scoping and Semantic Preferences |
| Authors | Davide Catta, Mehdi Mirzapour |
| Abstract | |
| Tasks | Common Sense Reasoning, Natural Language Inference |
| Published | 2017-01-01 |
| URL | https://www.aclweb.org/anthology/W17-7202/ |
| https://www.aclweb.org/anthology/W17-7202 | |
| PWC | https://paperswithcode.com/paper/quantifier-scoping-and-semantic-preferences |
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Probabilistic Path Hamiltonian Monte Carlo
| Title | Probabilistic Path Hamiltonian Monte Carlo |
| Authors | Vu Dinh, Arman Bilge, Cheng Zhang, Frederick A. Matsen IV |
| Abstract | Hamiltonian Monte Carlo (HMC) is an efficient and effective means of sampling posterior distributions on Euclidean space, which has been extended to manifolds with boundary. However, some applications require an extension to more general spaces. For example, phylogenetic (evolutionary) trees are defined in terms of both a discrete graph and associated continuous parameters; although one can represent these aspects using a single connected space, this rather complex space is not suitable for existing HMC algorithms. In this paper, we develop Probabilistic Path HMC (PPHMC) as a first step to sampling distributions on spaces with intricate combinatorial structure. We define PPHMC on orthant complexes, show that the resulting Markov chain is ergodic, and provide a promising implementation for the case of phylogenetic trees in open-source software. We also show that a surrogate function to ease the transition across a boundary on which the log-posterior has discontinuous derivatives can greatly improve efficiency. |
| Tasks | |
| Published | 2017-08-01 |
| URL | https://icml.cc/Conferences/2017/Schedule?showEvent=615 |
| http://proceedings.mlr.press/v70/dinh17a/dinh17a.pdf | |
| PWC | https://paperswithcode.com/paper/probabilistic-path-hamiltonian-monte-carlo |
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You’ll Never Tweet Alone: Building Sports Match Timelines from Microblog Posts
| Title | You’ll Never Tweet Alone: Building Sports Match Timelines from Microblog Posts |
| Authors | Amosse Edouard, Elena Cabrio, Sara Tonelli, Nhan Le-Thanh |
| Abstract | In this paper, we propose an approach to build a timeline with actions in a sports game based on tweets. We combine information provided by external knowledge bases to enrich the content of the tweets, and apply graph theory to model relations between actions and participants in a game. We demonstrate the validity of our approach using tweets collected during the EURO 2016 Championship and evaluate the output against live summaries produced by sports channels. |
| Tasks | |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/R17-1030/ |
| https://doi.org/10.26615/978-954-452-049-6_030 | |
| PWC | https://paperswithcode.com/paper/youll-never-tweet-alone-building-sports-match |
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Metaphor Detection in a Poetry Corpus
| Title | Metaphor Detection in a Poetry Corpus |
| Authors | Vaibhav Kesarwani, Diana Inkpen, Stan Szpakowicz, Chris Tanasescu |
| Abstract | Metaphor is indispensable in poetry. It showcases the poet{'}s creativity, and contributes to the overall emotional pertinence of the poem while honing its specific rhetorical impact. Previous work on metaphor detection relies on either rule-based or statistical models, none of them applied to poetry. Our method focuses on metaphor detection in a poetry corpus. It combines rule-based and statistical models (word embeddings) to develop a new classification system. Our system has achieved a precision of 0.759 and a recall of 0.804 in identifying one type of metaphor in poetry. |
| Tasks | Word Embeddings |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2201/ |
| https://www.aclweb.org/anthology/W17-2201 | |
| PWC | https://paperswithcode.com/paper/metaphor-detection-in-a-poetry-corpus |
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DECCA Repurposed: Detecting transcription inconsistencies without an orthographic standard
| Title | DECCA Repurposed: Detecting transcription inconsistencies without an orthographic standard |
| Authors | C. Anton Rytting, Julie Yelle |
| Abstract | |
| Tasks | Speech Recognition |
| Published | 2017-03-01 |
| URL | https://www.aclweb.org/anthology/W17-0116/ |
| https://www.aclweb.org/anthology/W17-0116 | |
| PWC | https://paperswithcode.com/paper/decca-repurposed-detecting-transcription |
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Corpus Creation and Initial SMT Experiments between Spanish and Shipibo-konibo
| Title | Corpus Creation and Initial SMT Experiments between Spanish and Shipibo-konibo |
| Authors | Ana-Paula Galarreta, Andr{'e}s Melgar, Arturo Oncevay |
| Abstract | In this paper, we present the first attempts to develop a machine translation (MT) system between Spanish and Shipibo-konibo (es-shp). There are very few digital texts written in Shipibo-konibo and even less bilingual texts that can be aligned, hence we had to create a parallel corpus using both bilingual and monolingual texts. We will describe how this corpus was made, as well as the process we followed to improve the quality of the sentences used to build a statistical MT model or SMT. The results obtained surpassed the baseline proposed (dictionary based) and made a promising result for further development considering the size of corpus used. Finally, it is expected that this MT system can be reinforced with the use of additional linguistic rules and automatic language processing functions that are being implemented. |
| Tasks | Machine Translation |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/R17-1033/ |
| https://doi.org/10.26615/978-954-452-049-6_033 | |
| PWC | https://paperswithcode.com/paper/corpus-creation-and-initial-smt-experiments |
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MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews
| Title | MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews |
| Authors | Wei Xue, Wubai Zhou, Tao Li, Qing Wang |
| Abstract | Online reviews are valuable resources not only for consumers to make decisions before purchase, but also for providers to get feedbacks for their services or commodities. In Aspect Based Sentiment Analysis (ABSA), it is critical to identify aspect categories and extract aspect terms from the sentences of user-generated reviews. However, the two tasks are often treated independently, even though they are closely related. Intuitively, the learned knowledge of one task should inform the other learning task. In this paper, we propose a multi-task learning model based on neural networks to solve them together. We demonstrate the improved performance of our multi-task learning model over the models trained separately on three public dataset released by SemEval workshops. |
| Tasks | Aspect-Based Sentiment Analysis, Extract Aspect, Multi-Task Learning, Opinion Mining, Sentiment Analysis, Text Classification |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/I17-2026/ |
| https://www.aclweb.org/anthology/I17-2026 | |
| PWC | https://paperswithcode.com/paper/mtna-a-neural-multi-task-model-for-aspect |
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Automatic Text Summarization Using Reinforcement Learning with Embedding Features
| Title | Automatic Text Summarization Using Reinforcement Learning with Embedding Features |
| Authors | Gyoung Ho Lee, Kong Joo Lee |
| Abstract | An automatic text summarization system can automatically generate a short and brief summary that contains a main concept of an original document. In this work, we explore the advantages of simple embedding features in Reinforcement leaning approach to automatic text summarization tasks. In addition, we propose a novel deep learning network for estimating Q-values used in Reinforcement learning. We evaluate our model by using ROUGE scores with DUC 2001, 2002, Wikipedia, ACL-ARC data. Evaluation results show that our model is competitive with the previous models. |
| Tasks | Information Retrieval, Text Summarization |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/I17-2033/ |
| https://www.aclweb.org/anthology/I17-2033 | |
| PWC | https://paperswithcode.com/paper/automatic-text-summarization-using |
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Technology Solutions to Combat Online Harassment
| Title | Technology Solutions to Combat Online Harassment |
| Authors | George Kennedy, Andrew McCollough, Edward Dixon, Alexei Bastidas, John Ryan, Chris Loo, Saurav Sahay |
| Abstract | This work is part of a new initiative to use machine learning to identify online harassment in social media and comment streams. Online harassment goes under-reported due to the reliance on humans to identify and report harassment, reporting that is further slowed by requirements to fill out forms providing context. In addition, the time for moderators to respond and apply human judgment can take days, but response times in terms of minutes are needed in the online context. Though some of the major social media companies have been doing proprietary work in automating the detection of harassment, there are few tools available for use by the public. In addition, the amount of labeled online harassment data and availability of cross-platform online harassment datasets is limited. We present the methodology used to create a harassment dataset and classifier and the dataset used to help the system learn what harassment looks like. |
| Tasks | |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-3011/ |
| https://www.aclweb.org/anthology/W17-3011 | |
| PWC | https://paperswithcode.com/paper/technology-solutions-to-combat-online |
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Normalizador de Texto para Lingua Portuguesa baseado em Modelo de Linguagem (A Normalizer based on Language Model for Texts in Portuguese)[In Portuguese]
| Title | Normalizador de Texto para Lingua Portuguesa baseado em Modelo de Linguagem (A Normalizer based on Language Model for Texts in Portuguese)[In Portuguese] |
| Authors | Patrick Bard, Renan Lopes Luis, Silvia Moraes |
| Abstract | |
| Tasks | Language Modelling, Machine Translation |
| Published | 2017-10-01 |
| URL | https://www.aclweb.org/anthology/W17-6617/ |
| https://www.aclweb.org/anthology/W17-6617 | |
| PWC | https://paperswithcode.com/paper/normalizador-de-texto-para-lingua-portuguesa |
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Finite-State Morphological Analysis for Marathi
| Title | Finite-State Morphological Analysis for Marathi |
| Authors | Vinit Ravishankar, Francis M. Tyers |
| Abstract | |
| Tasks | Machine Translation, Morphological Analysis |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-4006/ |
| https://www.aclweb.org/anthology/W17-4006 | |
| PWC | https://paperswithcode.com/paper/finite-state-morphological-analysis-for-1 |
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Between Reading Time and Syntactic/Semantic Categories
| Title | Between Reading Time and Syntactic/Semantic Categories |
| Authors | Masayuki Asahara, Sachi Kato |
| Abstract | This article presents a contrastive analysis between reading time and syntactic/semantic categories in Japanese. We overlaid the reading time annotation of BCCWJ-EyeTrack and a syntactic/semantic category information annotation on the {`}Balanced Corpus of Contemporary Written Japanese{'}. Statistical analysis based on a mixed linear model showed that verbal phrases tend to have shorter reading times than adjectives, adverbial phrases, or nominal phrases. The results suggest that the preceding phrases associated with the presenting phrases promote the reading process to shorten the gazing time. | |
| Tasks | |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/I17-1041/ |
| https://www.aclweb.org/anthology/I17-1041 | |
| PWC | https://paperswithcode.com/paper/between-reading-time-and-syntacticsemantic |
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bunji at SemEval-2017 Task 3: Combination of Neural Similarity Features and Comment Plausibility Features
| Title | bunji at SemEval-2017 Task 3: Combination of Neural Similarity Features and Comment Plausibility Features |
| Authors | Yuta Koreeda, Takuya Hashito, Yoshiki Niwa, Misa Sato, Toshihiko Yanase, Kenzo Kurotsuchi, Kohsuke Yanai |
| Abstract | This paper describes a text-ranking system developed by bunji team in SemEval-2017 Task 3: Community Question Answering, Subtask A and C. The goal of the task is to re-rank the comments in a question-and-answer forum such that useful comments for answering the question are ranked high. We proposed a method that combines neural similarity features and hand-crafted comment plausibility features, and we modeled inter-comments relationship using conditional random field. Our approach obtained the fifth place in the Subtask A and the second place in the Subtask C. |
| Tasks | Community Question Answering, Question Answering, Question Similarity |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/S17-2058/ |
| https://www.aclweb.org/anthology/S17-2058 | |
| PWC | https://paperswithcode.com/paper/bunji-at-semeval-2017-task-3-combination-of |
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