Paper Group NANR 45
Parser Adaptation for Social Media by Integrating Normalization. Neural Morphological Disambiguation Using Surface and Contextual Morphological Awareness. The State of the Art in Semantic Representation. Multi-entity sentiment analysis using entity-level feature extraction and word embeddings approach. Detecting Anxiety through Reddit. ELiRF-UPV at …
Parser Adaptation for Social Media by Integrating Normalization
| Title | Parser Adaptation for Social Media by Integrating Normalization |
| Authors | Rob van der Goot, Gertjan van Noord |
| Abstract | This work explores different approaches of using normalization for parser adaptation. Traditionally, normalization is used as separate pre-processing step. We show that integrating the normalization model into the parsing algorithm is more beneficial. This way, multiple normalization candidates can be leveraged, which improves parsing performance on social media. We test this hypothesis by modifying the Berkeley parser; out-of-the-box it achieves an F1 score of 66.52. Our integrated approach reaches a significant improvement with an F1 score of 67.36, while using the best normalization sequence results in an F1 score of only 66.94. |
| Tasks | Domain Adaptation, Named Entity Recognition, Sentiment Analysis |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-2078/ |
| https://www.aclweb.org/anthology/P17-2078 | |
| PWC | https://paperswithcode.com/paper/parser-adaptation-for-social-media-by |
| Repo | |
| Framework | |
Neural Morphological Disambiguation Using Surface and Contextual Morphological Awareness
| Title | Neural Morphological Disambiguation Using Surface and Contextual Morphological Awareness |
| Authors | Akhilesh Sudhakar, Anil Kumar Singh |
| Abstract | |
| Tasks | |
| Published | 2017-12-01 |
| URL | https://www.aclweb.org/anthology/W17-7559/ |
| https://www.aclweb.org/anthology/W17-7559 | |
| PWC | https://paperswithcode.com/paper/neural-morphological-disambiguation-using |
| Repo | |
| Framework | |
The State of the Art in Semantic Representation
| Title | The State of the Art in Semantic Representation |
| Authors | Omri Abend, Ari Rappoport |
| Abstract | Semantic representation is receiving growing attention in NLP in the past few years, and many proposals for semantic schemes (e.g., AMR, UCCA, GMB, UDS) have been put forth. Yet, little has been done to assess the achievements and the shortcomings of these new contenders, compare them with syntactic schemes, and clarify the general goals of research on semantic representation. We address these gaps by critically surveying the state of the art in the field. |
| Tasks | |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-1008/ |
| https://www.aclweb.org/anthology/P17-1008 | |
| PWC | https://paperswithcode.com/paper/the-state-of-the-art-in-semantic |
| Repo | |
| Framework | |
Multi-entity sentiment analysis using entity-level feature extraction and word embeddings approach
| Title | Multi-entity sentiment analysis using entity-level feature extraction and word embeddings approach |
| Authors | Colm Sweeney, Deepak Padmanabhan |
| Abstract | The sentiment analysis task has been traditionally divided into lexicon or machine learning approaches, but recently the use of word embeddings methods have emerged, that provide powerful algorithms to allow semantic understanding without the task of creating large amounts of annotated test data. One problem with this type of binary classification, is that the sentiment output will be in the form of {}1{'} (positive) or {}0{'} (negative) for the string of text in the tweet, regardless if there are one or more entities referred to in the text. This paper plans to enhance the word embeddings approach with the deployment of a sentiment lexicon-based technique to appoint a total score that indicates the polarity of opinion in relation to a particular entity or entities. This type of sentiment classification is a way of associating a given entity with the adjectives, adverbs, and verbs describing it, and extracting the associated sentiment to try and infer if the text is positive or negative in relation to the entity or entities. |
| Tasks | Entity Extraction, Sentiment Analysis, Word Embeddings |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/R17-1094/ |
| https://doi.org/10.26615/978-954-452-049-6_094 | |
| PWC | https://paperswithcode.com/paper/multi-entity-sentiment-analysis-using-entity |
| Repo | |
| Framework | |
Detecting Anxiety through Reddit
| Title | Detecting Anxiety through Reddit |
| Authors | Judy Hanwen Shen, Frank Rudzicz |
| Abstract | Previous investigations into detecting mental illnesses through social media have predominately focused on detecting depression through Twitter corpora. In this paper, we study anxiety disorders through personal narratives collected through the popular social media website, Reddit. We build a substantial data set of typical and anxiety-related posts, and we apply N-gram language modeling, vector embeddings, topic analysis, and emotional norms to generate features that accurately classify posts related to binary levels of anxiety. We achieve an accuracy of 91{%} with vector-space word embeddings, and an accuracy of 98{%} when combined with lexicon-based features. |
| Tasks | Language Modelling, Word Embeddings |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-3107/ |
| https://www.aclweb.org/anthology/W17-3107 | |
| PWC | https://paperswithcode.com/paper/detecting-anxiety-through-reddit |
| Repo | |
| Framework | |
ELiRF-UPV at SemEval-2017 Task 7: Pun Detection and Interpretation
| Title | ELiRF-UPV at SemEval-2017 Task 7: Pun Detection and Interpretation |
| Authors | Llu{'\i}s-F. Hurtado, Encarna Segarra, Ferran Pla, Pascual Carrasco, Jos{'e}-{'A}ngel Gonz{'a}lez |
| Abstract | This paper describes the participation of ELiRF-UPV team at task 7 (subtask 2: homographic pun detection and subtask 3: homographic pun interpretation) of SemEval2017. Our approach is based on the use of word embeddings to find related words in a sentence and a version of the Lesk algorithm to establish relationships between synsets. The results obtained are in line with those obtained by the other participants and they encourage us to continue working on this problem. |
| Tasks | Word Embeddings, Word Sense Disambiguation |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/S17-2075/ |
| https://www.aclweb.org/anthology/S17-2075 | |
| PWC | https://paperswithcode.com/paper/elirf-upv-at-semeval-2017-task-7-pun |
| Repo | |
| Framework | |
The Universal Dependencies Treebank for Slovenian
| Title | The Universal Dependencies Treebank for Slovenian |
| Authors | Kaja Dobrovoljc, Toma{\v{z}} Erjavec, Simon Krek |
| Abstract | This paper introduces the Universal Dependencies Treebank for Slovenian. We overview the existing dependency treebanks for Slovenian and then detail the conversion of the ssj200k treebank to the framework of Universal Dependencies version 2. We explain the mapping of part-of-speech categories, morphosyntactic features, and the dependency relations, focusing on the more problematic language-specific issues. We conclude with a quantitative overview of the treebank and directions for further work. |
| Tasks | |
| Published | 2017-04-01 |
| URL | https://www.aclweb.org/anthology/W17-1406/ |
| https://www.aclweb.org/anthology/W17-1406 | |
| PWC | https://paperswithcode.com/paper/the-universal-dependencies-treebank-for |
| Repo | |
| Framework | |
Neural Modeling of Multi-Predicate Interactions for Japanese Predicate Argument Structure Analysis
| Title | Neural Modeling of Multi-Predicate Interactions for Japanese Predicate Argument Structure Analysis |
| Authors | Hiroki Ouchi, Hiroyuki Shindo, Yuji Matsumoto |
| Abstract | The performance of Japanese predicate argument structure (PAS) analysis has improved in recent years thanks to the joint modeling of interactions between multiple predicates. However, this approach relies heavily on syntactic information predicted by parsers, and suffers from errorpropagation. To remedy this problem, we introduce a model that uses grid-type recurrent neural networks. The proposed model automatically induces features sensitive to multi-predicate interactions from the word sequence information of a sentence. Experiments on the NAIST Text Corpus demonstrate that without syntactic information, our model outperforms previous syntax-dependent models. |
| Tasks | |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-1146/ |
| https://www.aclweb.org/anthology/P17-1146 | |
| PWC | https://paperswithcode.com/paper/neural-modeling-of-multi-predicate |
| Repo | |
| Framework | |
Gera\cc~ao de perguntas e respostas para a base de conhecimento de um chatterbot educacional (Application to generate questions and answers for an educational chatterbot)[In Portuguese]
| Title | Gera\cc~ao de perguntas e respostas para a base de conhecimento de um chatterbot educacional (Application to generate questions and answers for an educational chatterbot)[In Portuguese] |
| Authors | Joyce Martins, Camila Martins |
| Abstract | |
| Tasks | |
| Published | 2017-10-01 |
| URL | https://www.aclweb.org/anthology/W17-6603/ |
| https://www.aclweb.org/anthology/W17-6603 | |
| PWC | https://paperswithcode.com/paper/geraaao-de-perguntas-e-respostas-para-a-base |
| Repo | |
| Framework | |
Cross-lingual and cross-domain discourse segmentation of entire documents
| Title | Cross-lingual and cross-domain discourse segmentation of entire documents |
| Authors | Chlo{'e} Braud, Oph{'e}lie Lacroix, Anders S{\o}gaard |
| Abstract | Discourse segmentation is a crucial step in building end-to-end discourse parsers. However, discourse segmenters only exist for a few languages and domains. Typically they only detect intra-sentential segment boundaries, assuming gold standard sentence and token segmentation, and relying on high-quality syntactic parses and rich heuristics that are not generally available across languages and domains. In this paper, we propose statistical discourse segmenters for five languages and three domains that do not rely on gold pre-annotations. We also consider the problem of learning discourse segmenters when no labeled data is available for a language. Our fully supervised system obtains 89.5{%} F1 for English newswire, with slight drops in performance on other domains, and we report supervised and unsupervised (cross-lingual) results for five languages in total. |
| Tasks | |
| Published | 2017-07-01 |
| URL | https://www.aclweb.org/anthology/P17-2037/ |
| https://www.aclweb.org/anthology/P17-2037 | |
| PWC | https://paperswithcode.com/paper/cross-lingual-and-cross-domain-discourse |
| Repo | |
| Framework | |
Factoring Ambiguity out of the Prediction of Compositionality for German Multi-Word Expressions
| Title | Factoring Ambiguity out of the Prediction of Compositionality for German Multi-Word Expressions |
| Authors | Stefan Bott, Sabine Schulte im Walde |
| Abstract | Ambiguity represents an obstacle for distributional semantic models(DSMs), which typically subsume the contexts of all word senses within one vector. While individual vector space approaches have been concerned with sense discrimination (e.g., Sch{"u}tze 1998, Erk 2009, Erk and Pado 2010), such discrimination has rarely been integrated into DSMs across semantic tasks. This paper presents a soft-clustering approach to sense discrimination that filters sense-irrelevant features when predicting the degrees of compositionality for German noun-noun compounds and German particle verbs. |
| Tasks | Machine Translation |
| Published | 2017-04-01 |
| URL | https://www.aclweb.org/anthology/W17-1708/ |
| https://www.aclweb.org/anthology/W17-1708 | |
| PWC | https://paperswithcode.com/paper/factoring-ambiguity-out-of-the-prediction-of |
| Repo | |
| Framework | |
Non-Projectivity in Serbian: Analysis of Formal and Linguistic Properties
| Title | Non-Projectivity in Serbian: Analysis of Formal and Linguistic Properties |
| Authors | Aleks Miletic, ra, Assaf Urieli |
| Abstract | |
| Tasks | |
| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-6517/ |
| https://www.aclweb.org/anthology/W17-6517 | |
| PWC | https://paperswithcode.com/paper/non-projectivity-in-serbian-analysis-of |
| Repo | |
| Framework | |
Integrating Subject, Type, and Property Identification for Simple Question Answering over Knowledge Base
| Title | Integrating Subject, Type, and Property Identification for Simple Question Answering over Knowledge Base |
| Authors | Wei-Chuan Hsiao, Hen-Hsen Huang, Hsin-Hsi Chen |
| Abstract | This paper presents an approach to identify subject, type and property from knowledge base (KB) for answering simple questions. We propose new features to rank entity candidates in KB. Besides, we split a relation in KB into type and property. Each of them is modeled by a bi-directional LSTM. Experimental results show that our model achieves the state-of-the-art performance on the SimpleQuestions dataset. The hard questions in the experiments are also analyzed in detail. |
| Tasks | Question Answering |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/I17-1098/ |
| https://www.aclweb.org/anthology/I17-1098 | |
| PWC | https://paperswithcode.com/paper/integrating-subject-type-and-property |
| Repo | |
| Framework | |
A Meta-Learning Perspective on Cold-Start Recommendations for Items
| Title | A Meta-Learning Perspective on Cold-Start Recommendations for Items |
| Authors | Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman, Hugo Larochelle |
| Abstract | Matrix factorization (MF) is one of the most popular techniques for product recommendation, but is known to suffer from serious cold-start problems. Item cold-start problems are particularly acute in settings such as Tweet recommendation where new items arrive continuously. In this paper, we present a meta-learning strategy to address item cold-start when new items arrive continuously. We propose two deep neural network architectures that implement our meta-learning strategy. The first architecture learns a linear classifier whose weights are determined by the item history while the second architecture learns a neural network whose biases are instead adjusted. We evaluate our techniques on the real-world problem of Tweet recommendation. On production data at Twitter, we demonstrate that our proposed techniques significantly beat the MF baseline and also outperform production models for Tweet recommendation. |
| Tasks | Meta-Learning, Product Recommendation |
| Published | 2017-12-01 |
| URL | http://papers.nips.cc/paper/7266-a-meta-learning-perspective-on-cold-start-recommendations-for-items |
| http://papers.nips.cc/paper/7266-a-meta-learning-perspective-on-cold-start-recommendations-for-items.pdf | |
| PWC | https://paperswithcode.com/paper/a-meta-learning-perspective-on-cold-start |
| Repo | |
| Framework | |
A non-DNN Feature Engineering Approach to Dependency Parsing – FBAML at CoNLL 2017 Shared Task
| Title | A non-DNN Feature Engineering Approach to Dependency Parsing – FBAML at CoNLL 2017 Shared Task |
| Authors | Xian Qian, Yang Liu |
| Abstract | For this year{'}s multilingual dependency parsing shared task, we developed a pipeline system, which uses a variety of features for each of its components. Unlike the recent popular deep learning approaches that learn low dimensional dense features using non-linear classifier, our system uses structured linear classifiers to learn millions of sparse features. Specifically, we trained a linear classifier for sentence boundary prediction, linear chain conditional random fields (CRFs) for tokenization, part-of-speech tagging and morph analysis. A second order graph based parser learns the tree structure (without relations), and fa linear tree CRF then assigns relations to the dependencies in the tree. Our system achieves reasonable performance {–} 67.87{%} official averaged macro F1 score |
| Tasks | Dependency Parsing, Feature Engineering, Morphological Analysis, Part-Of-Speech Tagging, Relation Classification, Tokenization, Word Embeddings |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/K17-3015/ |
| https://www.aclweb.org/anthology/K17-3015 | |
| PWC | https://paperswithcode.com/paper/a-non-dnn-feature-engineering-approach-to |
| Repo | |
| Framework | |
