Paper Group NANR 20
Automatic Generation of Student Report Cards. Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records. Semantics-Driven Recognition of Collocations Using Word Embeddings. CICBUAPnlp at SemEval-2016 Task 4-A: Discovering Twitter Polarity using Enhanced Embeddings. Unsupervised Ranked Cross-Lingual Lexical Substitution for Lo …
Automatic Generation of Student Report Cards
| Title | Automatic Generation of Student Report Cards |
| Authors | Amy Isard, Jeremy Knox |
| Abstract | |
| Tasks | Sentiment Analysis, Text Generation, Time Series |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-6633/ |
| https://www.aclweb.org/anthology/W16-6633 | |
| PWC | https://paperswithcode.com/paper/automatic-generation-of-student-report-cards |
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Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records
| Title | Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records |
| Authors | Takanori Yamashita, Yoshifumi Wakata, Hidehisa Soejima, Naoki Nakashima, Sachio Hirokawa |
| Abstract | The number of unstructured medical records kept in hospital information systems is increasing. The conditions of patients are formulated as outcomes in clinical pathway. A variance of an outcome describes deviations from standards of care like a patient{'}s bad condition. The present paper applied text mining to extract feature words and phrases of the variance from admission records. We report the cases the variances of {}pain control{''} and {}no neuropathy worsening{''} in cerebral infarction. |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4212/ |
| https://www.aclweb.org/anthology/W16-4212 | |
| PWC | https://paperswithcode.com/paper/prediction-of-key-patient-outcome-from |
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Semantics-Driven Recognition of Collocations Using Word Embeddings
| Title | Semantics-Driven Recognition of Collocations Using Word Embeddings |
| Authors | Sara Rodr{'\i}guez-Fern{'a}ndez, Luis Espinosa-Anke, Roberto Carlini, Leo Wanner |
| Abstract | |
| Tasks | Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2081/ |
| https://www.aclweb.org/anthology/P16-2081 | |
| PWC | https://paperswithcode.com/paper/semantics-driven-recognition-of-collocations |
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CICBUAPnlp at SemEval-2016 Task 4-A: Discovering Twitter Polarity using Enhanced Embeddings
| Title | CICBUAPnlp at SemEval-2016 Task 4-A: Discovering Twitter Polarity using Enhanced Embeddings |
| Authors | Helena Gomez, Darnes Vilari{~n}o, Grigori Sidorov, David Pinto Avenda{~n}o |
| Abstract | |
| Tasks | Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1021/ |
| https://www.aclweb.org/anthology/S16-1021 | |
| PWC | https://paperswithcode.com/paper/cicbuapnlp-at-semeval-2016-task-4-a |
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Unsupervised Ranked Cross-Lingual Lexical Substitution for Low-Resource Languages
| Title | Unsupervised Ranked Cross-Lingual Lexical Substitution for Low-Resource Languages |
| Authors | Stefan Ecker, Andrea Horbach, Stefan Thater |
| Abstract | We propose an unsupervised system for a variant of cross-lingual lexical substitution (CLLS) to be used in a reading scenario in computer-assisted language learning (CALL), in which single-word translations provided by a dictionary are ranked according to their appropriateness in context. In contrast to most alternative systems, ours does not rely on either parallel corpora or machine translation systems, making it suitable for low-resource languages as the language to be learned. This is achieved by a graph-based scoring mechanism which can deal with ambiguous translations of context words provided by a dictionary. Due to this decoupling from the source language, we need monolingual corpus resources only for the target language, i.e. the language of the translation candidates. We evaluate our approach for the language pair Norwegian Nynorsk-English on an exploratory manually annotated gold standard and report promising results. When running our system on the original SemEval CLLS task, we rank 6th out of 18 (including 2 baselines and our 2 system variants) in the best evaluation. |
| Tasks | Machine Translation |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1270/ |
| https://www.aclweb.org/anthology/L16-1270 | |
| PWC | https://paperswithcode.com/paper/unsupervised-ranked-cross-lingual-lexical |
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Hand in Glove: Deep Feature Fusion Network Architectures for Answer Quality Prediction in Community Question Answering
| Title | Hand in Glove: Deep Feature Fusion Network Architectures for Answer Quality Prediction in Community Question Answering |
| Authors | Sai Praneeth Suggu, Kushwanth Naga Goutham, Manoj K. Chinnakotla, Manish Shrivastava |
| Abstract | Community Question Answering (cQA) forums have become a popular medium for soliciting direct answers to specific questions of users from experts or other experienced users on a given topic. However, for a given question, users sometimes have to sift through a large number of low-quality or irrelevant answers to find out the answer which satisfies their information need. To alleviate this, the problem of Answer Quality Prediction (AQP) aims to predict the quality of an answer posted in response to a forum question. Current AQP systems either learn models using - a) various hand-crafted features (HCF) or b) Deep Learning (DL) techniques which automatically learn the required feature representations. In this paper, we propose a novel approach for AQP known as - {``}Deep Feature Fusion Network (DFFN){''} which combines the advantages of both hand-crafted features and deep learning based systems. Given a question-answer pair along with its metadata, the DFFN architecture independently - a) learns features from the Deep Neural Network (DNN) and b) computes hand-crafted features using various external resources and then combines them using a fully connected neural network trained to predict the final answer quality. DFFN is end-end differentiable and trained as a single system. We propose two different DFFN architectures which vary mainly in the way they model the input question/answer pair - DFFN-CNN uses a Convolutional Neural Network (CNN) and DFFN-BLNA uses a Bi-directional LSTM with Neural Attention (BLNA). Both these proposed variants of DFFN (DFFN-CNN and DFFN-BLNA) achieve state-of-the-art performance on the standard SemEval-2015 and SemEval-2016 benchmark datasets and outperforms baseline approaches which individually employ either HCF or DL based techniques alone. | |
| Tasks | Community Question Answering, Question Answering |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1135/ |
| https://www.aclweb.org/anthology/C16-1135 | |
| PWC | https://paperswithcode.com/paper/hand-in-glove-deep-feature-fusion-network |
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Using Centroids of Word Embeddings and Word Mover’s Distance for Biomedical Document Retrieval in Question Answering
| Title | Using Centroids of Word Embeddings and Word Mover’s Distance for Biomedical Document Retrieval in Question Answering |
| Authors | Georgios-Ioannis Brokos, Prodromos Malakasiotis, Ion Androutsopoulos |
| Abstract | |
| Tasks | Document Classification, Question Answering, Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2915/ |
| https://www.aclweb.org/anthology/W16-2915 | |
| PWC | https://paperswithcode.com/paper/using-centroids-of-word-embeddings-and-word |
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Mirroring Facial Expressions and Emotions in Dyadic Conversations
| Title | Mirroring Facial Expressions and Emotions in Dyadic Conversations |
| Authors | Costanza Navarretta |
| Abstract | This paper presents an investigation of mirroring facial expressions and the emotions which they convey in dyadic naturally occurring first encounters. Mirroring facial expressions are a common phenomenon in face-to-face interactions, and they are due to the mirror neuron system which has been found in both animals and humans. Researchers have proposed that the mirror neuron system is an important component behind many cognitive processes such as action learning and understanding the emotions of others. Preceding studies of the first encounters have shown that overlapping speech and overlapping facial expressions are very frequent. In this study, we want to determine whether the overlapping facial expressions are mirrored or are otherwise correlated in the encounters, and to what extent mirroring facial expressions convey the same emotion. The results of our study show that the majority of smiles and laughs, and one fifth of the occurrences of raised eyebrows are mirrored in the data. Moreover some facial traits in co-occurring expressions co-occur more often than it would be expected by chance. Finally, amusement, and to a lesser extent friendliness, are often emotions shared by both participants, while other emotions indicating individual affective states such as uncertainty and hesitancy are never showed by both participants, but co-occur with complementary emotions such as friendliness and support. Whether these tendencies are specific to this type of conversations or are more common should be investigated further. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1075/ |
| https://www.aclweb.org/anthology/L16-1075 | |
| PWC | https://paperswithcode.com/paper/mirroring-facial-expressions-and-emotions-in |
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Building Language Resources for Exploring Autism Spectrum Disorders
| Title | Building Language Resources for Exploring Autism Spectrum Disorders |
| Authors | Julia Parish-Morris, Christopher Cieri, Mark Liberman, Leila Bateman, Emily Ferguson, Robert T. Schultz |
| Abstract | Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that would benefit from low-cost and reliable improvements to screening and diagnosis. Human language technologies (HLTs) provide one possible route to automating a series of subjective decisions that currently inform {``}Gold Standard{''} diagnosis based on clinical judgment. In this paper, we describe a new resource to support this goal, comprised of 100 20-minute semi-structured English language samples labeled with child age, sex, IQ, autism symptom severity, and diagnostic classification. We assess the feasibility of digitizing and processing sensitive clinical samples for data sharing, and identify areas of difficulty. Using the methods described here, we propose to join forces with researchers and clinicians throughout the world to establish an international repository of annotated language samples from individuals with ASD and related disorders. This project has the potential to improve the lives of individuals with ASD and their families by identifying linguistic features that could improve remote screening, inform personalized intervention, and promote advancements in clinically-oriented HLTs. | |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1333/ |
| https://www.aclweb.org/anthology/L16-1333 | |
| PWC | https://paperswithcode.com/paper/building-language-resources-for-exploring |
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A Report on the Automatic Evaluation of Scientific Writing Shared Task
| Title | A Report on the Automatic Evaluation of Scientific Writing Shared Task |
| Authors | Vidas Daudaravicius, Rafael E. Banchs, Elena Volodina, Courtney Napoles |
| Abstract | |
| Tasks | Grammatical Error Correction, Grammatical Error Detection |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0506/ |
| https://www.aclweb.org/anthology/W16-0506 | |
| PWC | https://paperswithcode.com/paper/a-report-on-the-automatic-evaluation-of |
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Causal meets Submodular: Subset Selection with Directed Information
| Title | Causal meets Submodular: Subset Selection with Directed Information |
| Authors | Yuxun Zhou, Costas J. Spanos |
| Abstract | We study causal subset selection with Directed Information as the measure of prediction causality. Two typical tasks, causal sensor placement and covariate selection, are correspondingly formulated into cardinality constrained directed information maximizations. To attack the NP-hard problems, we show that the first problem is submodular while not necessarily monotonic. And the second one is ``nearly’’ submodular. To substantiate the idea of approximate submodularity, we introduce a novel quantity, namely submodularity index (SmI), for general set functions. Moreover, we show that based on SmI, greedy algorithm has performance guarantee for the maximization of possibly non-monotonic and non-submodular functions, justifying its usage for a much broader class of problems. We evaluate the theoretical results with several case studies, and also illustrate the application of the subset selection to causal structure learning. | |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6384-causal-meets-submodular-subset-selection-with-directed-information |
| http://papers.nips.cc/paper/6384-causal-meets-submodular-subset-selection-with-directed-information.pdf | |
| PWC | https://paperswithcode.com/paper/causal-meets-submodular-subset-selection-with |
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Proceedings of the Sixth Workshop on Hybrid Approaches to Translation (HyTra6)
| Title | Proceedings of the Sixth Workshop on Hybrid Approaches to Translation (HyTra6) |
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| Abstract | |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4500/ |
| https://www.aclweb.org/anthology/W16-4500 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-sixth-workshop-on-hybrid |
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A Correlation Analysis of English Particle Placement of Three East Asian EFL Learners Writings
| Title | A Correlation Analysis of English Particle Placement of Three East Asian EFL Learners Writings |
| Authors | Ha-Eung Kim, Gyu-Hyeong Lee, Yong-hun Lee |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-3005/ |
| https://www.aclweb.org/anthology/Y16-3005 | |
| PWC | https://paperswithcode.com/paper/a-correlation-analysis-of-english-particle |
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DialPort: A General Framework for Aggregating Dialog Systems
| Title | DialPort: A General Framework for Aggregating Dialog Systems |
| Authors | Tiancheng Zhao, Kyusong Lee, Maxine Eskenazi |
| Abstract | |
| Tasks | Representation Learning |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/W16-6007/ |
| https://www.aclweb.org/anthology/W16-6007 | |
| PWC | https://paperswithcode.com/paper/dialport-a-general-framework-for-aggregating |
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Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation
| Title | Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation |
| Authors | Akiko Eriguchi, Kazuma Hashimoto, Yoshimasa Tsuruoka |
| Abstract | This paper reports our systems (UT-AKY) submitted in the 3rd Workshop of Asian Translation 2016 (WAT{'}16) and their results in the English-to-Japanese translation task. Our model is based on the tree-to-sequence Attention-based NMT (ANMT) model proposed by Eriguchi et al. (2016). We submitted two ANMT systems: one with a word-based decoder and the other with a character-based decoder. Experimenting on the English-to-Japanese translation task, we have confirmed that the character-based decoder can cover almost the full vocabulary in the target language and generate translations much faster than the word-based model. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4617/ |
| https://www.aclweb.org/anthology/W16-4617 | |
| PWC | https://paperswithcode.com/paper/character-based-decoding-in-tree-to-sequence |
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