Paper Group NANR 1
Neural Networks For Negation Scope Detection. Optimistic Gittins Indices. Using Bilingual Segments in Generating Word-to-word Translations. Adaptive Concentration Inequalities for Sequential Decision Problems. Sentiment Lexicons for Arabic Social Media. A Language Independent Method for Generating Large Scale Polarity Lexicons. Global Pre-ordering …
Neural Networks For Negation Scope Detection
| Title | Neural Networks For Negation Scope Detection |
| Authors | Federico Fancellu, Adam Lopez, Bonnie Webber |
| Abstract | |
| Tasks | Machine Translation, Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1047/ |
| https://www.aclweb.org/anthology/P16-1047 | |
| PWC | https://paperswithcode.com/paper/neural-networks-for-negation-scope-detection |
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Optimistic Gittins Indices
| Title | Optimistic Gittins Indices |
| Authors | Eli Gutin, Vivek Farias |
| Abstract | Starting with the Thomspon sampling algorithm, recent years have seen a resurgence of interest in Bayesian algorithms for the Multi-armed Bandit (MAB) problem. These algorithms seek to exploit prior information on arm biases and while several have been shown to be regret optimal, their design has not emerged from a principled approach. In contrast, if one cared about Bayesian regret discounted over an infinite horizon at a fixed, pre-specified rate, the celebrated Gittins index theorem offers an optimal algorithm. Unfortunately, the Gittins analysis does not appear to carry over to minimizing Bayesian regret over all sufficiently large horizons and computing a Gittins index is onerous relative to essentially any incumbent index scheme for the Bayesian MAB problem. The present paper proposes a sequence of ‘optimistic’ approximations to the Gittins index. We show that the use of these approximations in concert with the use of an increasing discount factor appears to offer a compelling alternative to a variety of index schemes proposed for the Bayesian MAB problem in recent years. In addition, we show that the simplest of these approximations yields regret that matches the Lai-Robbins lower bound, including achieving matching constants. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6036-optimistic-gittins-indices |
| http://papers.nips.cc/paper/6036-optimistic-gittins-indices.pdf | |
| PWC | https://paperswithcode.com/paper/optimistic-gittins-indices |
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Using Bilingual Segments in Generating Word-to-word Translations
| Title | Using Bilingual Segments in Generating Word-to-word Translations |
| Authors | Kavitha Mahesh, Gabriel Pereira Lopes, Lu{'\i}s Gomes |
| Abstract | We defend that bilingual lexicons automatically extracted from parallel corpora, whose entries have been meanwhile validated by linguists and classified as correct or incorrect, should constitute a specific parallel corpora. And, in this paper, we propose to use word-to-word translations to learn morph-units (comprising of bilingual stems and suffixes) from those bilingual lexicons for two language pairs L1-L2 and L1-L3 to induce a bilingual lexicon for the language pair L2-L3, apart from also learning morph-units for this other language pair. The applicability of bilingual morph-units in L1-L2 and L1-L3 is examined from the perspective of pivot-based lexicon induction for language pair L2-L3 with L1 as bridge. While the lexicon is derived by transitivity, the correspondences are identified based on previously learnt bilingual stems and suffixes rather than surface translation forms. The induced pairs are validated using a binary classifier trained on morphological and similarity-based features using an existing, automatically acquired, manually validated bilingual translation lexicon for language pair L2-L3. In this paper, we discuss the use of English (EN)-French (FR) and English (EN)-Portuguese (PT) lexicon of word-to-word translations in generating word-to-word translations for the language pair FR-PT with EN as pivot language. Generated translations are filtered out first using an SVM-based FR-PT classifier and then are manually validated. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4508/ |
| https://www.aclweb.org/anthology/W16-4508 | |
| PWC | https://paperswithcode.com/paper/using-bilingual-segments-in-generating-word |
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Adaptive Concentration Inequalities for Sequential Decision Problems
| Title | Adaptive Concentration Inequalities for Sequential Decision Problems |
| Authors | Shengjia Zhao, Enze Zhou, Ashish Sabharwal, Stefano Ermon |
| Abstract | A key challenge in sequential decision problems is to determine how many samples are needed for an agent to make reliable decisions with good probabilistic guarantees. We introduce Hoeffding-like concentration inequalities that hold for a random, adaptively chosen number of samples. Our inequalities are tight under natural assumptions and can greatly simplify the analysis of common sequential decision problems. In particular, we apply them to sequential hypothesis testing, best arm identification, and sorting. The resulting algorithms rival or exceed the state of the art both theoretically and empirically. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6493-adaptive-concentration-inequalities-for-sequential-decision-problems |
| http://papers.nips.cc/paper/6493-adaptive-concentration-inequalities-for-sequential-decision-problems.pdf | |
| PWC | https://paperswithcode.com/paper/adaptive-concentration-inequalities-for |
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Sentiment Lexicons for Arabic Social Media
| Title | Sentiment Lexicons for Arabic Social Media |
| Authors | Saif Mohammad, Mohammad Salameh, Svetlana Kiritchenko |
| Abstract | Existing Arabic sentiment lexicons have low coverage―with only a few thousand entries. In this paper, we present several large sentiment lexicons that were automatically generated using two different methods: (1) by using distant supervision techniques on Arabic tweets, and (2) by translating English sentiment lexicons into Arabic using a freely available statistical machine translation system. We compare the usefulness of new and old sentiment lexicons in the downstream application of sentence-level sentiment analysis. Our baseline sentiment analysis system uses numerous surface form features. Nonetheless, the system benefits from using additional features drawn from sentiment lexicons. The best result is obtained using the automatically generated Dialectal Hashtag Lexicon and the Arabic translations of the NRC Emotion Lexicon (accuracy of 66.6{%}). Finally, we describe a qualitative study of the automatic translations of English sentiment lexicons into Arabic, which shows that about 88{%} of the automatically translated entries are valid for English as well. Close to 10{%} of the invalid entries are caused by gross mistranslations, close to 40{%} by translations into a related word, and about 50{%} by differences in how the word is used in Arabic. |
| Tasks | Machine Translation, Sentiment Analysis |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1006/ |
| https://www.aclweb.org/anthology/L16-1006 | |
| PWC | https://paperswithcode.com/paper/sentiment-lexicons-for-arabic-social-media |
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| Framework | |
A Language Independent Method for Generating Large Scale Polarity Lexicons
| Title | A Language Independent Method for Generating Large Scale Polarity Lexicons |
| Authors | Giuseppe Castellucci, Danilo Croce, Roberto Basili |
| Abstract | Sentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts. Many approaches in literature are based on resources that model the prior polarity of words or multi-word expressions, i.e. a polarity lexicon. Such resources are defined by teams of annotators, i.e. a manual annotation is provided to associate emotional or sentiment facets to the lexicon entries. The development of such lexicons is an expensive and language dependent process, making them often not covering all the linguistic sentiment phenomena. Moreover, once a lexicon is defined it can hardly be adopted in a different language or even a different domain. In this paper, we present several Distributional Polarity Lexicons (DPLs), i.e. large-scale polarity lexicons acquired with an unsupervised methodology based on Distributional Models of Lexical Semantics. Given a set of heuristically annotated sentences from Twitter, we transfer the sentiment information from sentences to words. The approach is mostly unsupervised, and experimental evaluations on Sentiment Analysis tasks in two languages show the benefits of the generated resources. The generated DPLs are publicly available in English and Italian. |
| Tasks | Sentiment Analysis |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1007/ |
| https://www.aclweb.org/anthology/L16-1007 | |
| PWC | https://paperswithcode.com/paper/a-language-independent-method-for-generating |
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Global Pre-ordering for Improving Sublanguage Translation
| Title | Global Pre-ordering for Improving Sublanguage Translation |
| Authors | Masaru Fuji, Masao Utiyama, Eiichiro Sumita, Yuji Matsumoto |
| Abstract | When translating formal documents, capturing the sentence structure specific to the sublanguage is extremely necessary to obtain high-quality translations. This paper proposes a novel global reordering method with particular focus on long-distance reordering for capturing the global sentence structure of a sublanguage. The proposed method learns global reordering models from a non-annotated parallel corpus and works in conjunction with conventional syntactic reordering. Experimental results on the patent abstract sublanguage show substantial gains of more than 25 points in the RIBES metric and comparable BLEU scores both for Japanese-to-English and English-to-Japanese translations. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4606/ |
| https://www.aclweb.org/anthology/W16-4606 | |
| PWC | https://paperswithcode.com/paper/global-pre-ordering-for-improving-sublanguage |
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| Framework | |
A Data-driven Investigation of Corrective Feedback on Subject Omission Errors in First Language Acquisition
| Title | A Data-driven Investigation of Corrective Feedback on Subject Omission Errors in First Language Acquisition |
| Authors | Sarah Hiller, Raquel Fern{'a}ndez |
| Abstract | |
| Tasks | Language Acquisition |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/K16-1011/ |
| https://www.aclweb.org/anthology/K16-1011 | |
| PWC | https://paperswithcode.com/paper/a-data-driven-investigation-of-corrective |
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Text Simplification as Tree Labeling
| Title | Text Simplification as Tree Labeling |
| Authors | Joachim Bingel, Anders S{\o}gaard |
| Abstract | |
| Tasks | Machine Translation, Sentence Compression, Structured Prediction, Text Simplification |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2055/ |
| https://www.aclweb.org/anthology/P16-2055 | |
| PWC | https://paperswithcode.com/paper/text-simplification-as-tree-labeling |
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| Framework | |
Characterizing Text Difficulty with Word Frequencies
| Title | Characterizing Text Difficulty with Word Frequencies |
| Authors | Xiaobin Chen, Detmar Meurers |
| Abstract | |
| Tasks | Language Acquisition |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0509/ |
| https://www.aclweb.org/anthology/W16-0509 | |
| PWC | https://paperswithcode.com/paper/characterizing-text-difficulty-with-word |
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| Framework | |
Evaluation Dataset (DT-Grade) and Word Weighting Approach towards Constructed Short Answers Assessment in Tutorial Dialogue Context
| Title | Evaluation Dataset (DT-Grade) and Word Weighting Approach towards Constructed Short Answers Assessment in Tutorial Dialogue Context |
| Authors | Rajendra Banjade, Nabin Maharjan, Nobal Bikram Niraula, Dipesh Gautam, Borhan Samei, Vasile Rus |
| Abstract | |
| Tasks | |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0520/ |
| https://www.aclweb.org/anthology/W16-0520 | |
| PWC | https://paperswithcode.com/paper/evaluation-dataset-dt-grade-and-word |
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Translation Using JAPIO Patent Corpora: JAPIO at WAT2016
| Title | Translation Using JAPIO Patent Corpora: JAPIO at WAT2016 |
| Authors | Satoshi Kinoshita, Tadaaki Oshio, Tomoharu Mitsuhashi, Terumasa Ehara |
| Abstract | We participate in scientific paper subtask (ASPEC-EJ/CJ) and patent subtask (JPC-EJ/CJ/KJ) with phrase-based SMT systems which are trained with its own patent corpora. Using larger corpora than those prepared by the workshop organizer, we achieved higher BLEU scores than most participants in EJ and CJ translations of patent subtask, but in crowdsourcing evaluation, our EJ translation, which is best in all automatic evaluations, received a very poor score. In scientific paper subtask, our translations are given lower scores than most translations that are produced by translation engines trained with the in-domain corpora. But our scores are higher than those of general-purpose RBMTs and online services. Considering the result of crowdsourcing evaluation, it shows a possibility that CJ SMT system trained with a large patent corpus translates non-patent technical documents at a practical level. |
| Tasks | Information Retrieval, Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4612/ |
| https://www.aclweb.org/anthology/W16-4612 | |
| PWC | https://paperswithcode.com/paper/translation-using-japio-patent-corpora-japio |
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| Framework | |
Could Speaker, Gender or Age Awareness be beneficial in Speech-based Emotion Recognition?
| Title | Could Speaker, Gender or Age Awareness be beneficial in Speech-based Emotion Recognition? |
| Authors | Maxim Sidorov, Alex Schmitt, er, Eugene Semenkin, Wolfgang Minker |
| Abstract | Emotion Recognition (ER) is an important part of dialogue analysis which can be used in order to improve the quality of Spoken Dialogue Systems (SDSs). The emotional hypothesis of the current response of an end-user might be utilised by the dialogue manager component in order to change the SDS strategy which could result in a quality enhancement. In this study additional speaker-related information is used to improve the performance of the speech-based ER process. The analysed information is the speaker identity, gender and age of a user. Two schemes are described here, namely, using additional information as an independent variable within the feature vector and creating separate emotional models for each speaker, gender or age-cluster independently. The performances of the proposed approaches were compared against the baseline ER system, where no additional information has been used, on a number of emotional speech corpora of German, English, Japanese and Russian. The study revealed that for some of the corpora the proposed approach significantly outperforms the baseline methods with a relative difference of up to 11.9{%}. |
| Tasks | Emotion Recognition, Spoken Dialogue Systems |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1010/ |
| https://www.aclweb.org/anthology/L16-1010 | |
| PWC | https://paperswithcode.com/paper/could-speaker-gender-or-age-awareness-be |
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Extracting Subevents via an Effective Two-phase Approach
| Title | Extracting Subevents via an Effective Two-phase Approach |
| Authors | Allison Badgett, Ruihong Huang |
| Abstract | |
| Tasks | |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1088/ |
| https://www.aclweb.org/anthology/D16-1088 | |
| PWC | https://paperswithcode.com/paper/extracting-subevents-via-an-effective-two |
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| Framework | |
Automatic Cross-Lingual Similarization of Dependency Grammars for Tree-based Machine Translation
| Title | Automatic Cross-Lingual Similarization of Dependency Grammars for Tree-based Machine Translation |
| Authors | Wenbin Jiang, Wen Zhang, Jinan Xu, Rangjia Cai |
| Abstract | |
| Tasks | Dependency Parsing, Information Retrieval, Machine Translation |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1048/ |
| https://www.aclweb.org/anthology/D16-1048 | |
| PWC | https://paperswithcode.com/paper/automatic-cross-lingual-similarization-of |
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