Paper Group NANR 116
Classifying ReachOut posts with a radial basis function SVM. A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature. Sub-Word Similarity based Search for Embeddings: Inducing Rare-Word Embeddings for Word Similarity Tasks and Language Modelling. An Open Web Platform for Rule-Based Speech-to-Sign Translation. Domain Adaptation …
Classifying ReachOut posts with a radial basis function SVM
| Title | Classifying ReachOut posts with a radial basis function SVM |
| Authors | Chris Brew |
| Abstract | |
| Tasks | |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0315/ |
| https://www.aclweb.org/anthology/W16-0315 | |
| PWC | https://paperswithcode.com/paper/classifying-reachout-posts-with-a-radial |
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A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature
| Title | A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature |
| Authors | Suchet Chachra, Asma Ben Abacha, Sonya Shooshan, Laritza Rodriguez, Dina Demner-Fushman |
| Abstract | Readers usually rely on abstracts to identify relevant medical information from scientific articles. Abstracts are also essential to advanced information retrieval methods. More than 50 thousand scientific publications in PubMed lack author-generated abstracts, and the relevancy judgements for these papers have to be based on their titles alone. In this paper, we propose a hybrid summarization technique that aims to select the most pertinent sentences from articles to generate an extractive summary in lieu of a missing abstract. We combine i) health outcome detection, ii) keyphrase extraction, and iii) textual entailment recognition between sentences. We evaluate our hybrid approach and analyze the improvements of multi-factor summarization over techniques that rely on a single method, using a collection of 295 manually generated reference summaries. The obtained results show that the hybrid approach outperforms the baseline techniques with an improvement of 13{%} in recall and 4{%} in F1 score. |
| Tasks | Information Retrieval, Natural Language Inference, Text Summarization |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1104/ |
| https://www.aclweb.org/anthology/C16-1104 | |
| PWC | https://paperswithcode.com/paper/a-hybrid-approach-to-generation-of-missing |
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Sub-Word Similarity based Search for Embeddings: Inducing Rare-Word Embeddings for Word Similarity Tasks and Language Modelling
| Title | Sub-Word Similarity based Search for Embeddings: Inducing Rare-Word Embeddings for Word Similarity Tasks and Language Modelling |
| Authors | Mittul Singh, Clayton Greenberg, Youssef Oualil, Dietrich Klakow |
| Abstract | Training good word embeddings requires large amounts of data. Out-of-vocabulary words will still be encountered at test-time, leaving these words without embeddings. To overcome this lack of embeddings for rare words, existing methods leverage morphological features to generate embeddings. While the existing methods use computationally-intensive rule-based (Soricut and Och, 2015) or tool-based (Botha and Blunsom, 2014) morphological analysis to generate embeddings, our system applies a computationally-simpler sub-word search on words that have existing embeddings. Embeddings of the sub-word search results are then combined using string similarity functions to generate rare word embeddings. We augmented pre-trained word embeddings with these novel embeddings and evaluated on a rare word similarity task, obtaining up to 3 times improvement in correlation over the original set of embeddings. Applying our technique to embeddings trained on larger datasets led to on-par performance with the existing state-of-the-art for this task. Additionally, while analysing augmented embeddings in a log-bilinear language model, we observed up to 50{%} reduction in rare word perplexity in comparison to other more complex language models. |
| Tasks | Language Modelling, Morphological Analysis, Word Embeddings |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1194/ |
| https://www.aclweb.org/anthology/C16-1194 | |
| PWC | https://paperswithcode.com/paper/sub-word-similarity-based-search-for |
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An Open Web Platform for Rule-Based Speech-to-Sign Translation
| Title | An Open Web Platform for Rule-Based Speech-to-Sign Translation |
| Authors | Manny Rayner, Pierrette Bouillon, Sarah Ebling, Johanna Gerlach, Irene Strasly, Nikos Tsourakis |
| Abstract | |
| Tasks | Machine Translation, Sign Language Recognition, Sign Language Translation, Speech Recognition |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2027/ |
| https://www.aclweb.org/anthology/P16-2027 | |
| PWC | https://paperswithcode.com/paper/an-open-web-platform-for-rule-based-speech-to |
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Domain Adaptation of Polarity Lexicon combining Term Frequency and Bootstrapping
| Title | Domain Adaptation of Polarity Lexicon combining Term Frequency and Bootstrapping |
| Authors | Salud Mar{'\i}a Jim{'e}nez-Zafra, Maite Martin, M. Dolores Molina-Gonzalez, L. Alfonso Ure{~n}a-L{'o}pez |
| Abstract | |
| Tasks | Domain Adaptation, Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0422/ |
| https://www.aclweb.org/anthology/W16-0422 | |
| PWC | https://paperswithcode.com/paper/domain-adaptation-of-polarity-lexicon |
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How to Address Smart Homes with a Social Robot? A Multi-modal Corpus of User Interactions with an Intelligent Environment
| Title | How to Address Smart Homes with a Social Robot? A Multi-modal Corpus of User Interactions with an Intelligent Environment |
| Authors | Patrick Holthaus, Christian Leichsenring, Jasmin Bernotat, Viktor Richter, Marian Pohling, Birte Carlmeyer, Norman K{"o}ster, Sebastian Meyer zu Borgsen, Ren{'e} Zorn, Birte Schiffhauer, Kai Frederic Engelmann, Florian Lier, Simon Schulz, Philipp Cimiano, Friederike Eyssel, Thomas Hermann, Franz Kummert, David Schlangen, Sven Wachsmuth, Petra Wagner, Britta Wrede, Sebastian Wrede |
| Abstract | In order to explore intuitive verbal and non-verbal interfaces in smart environments we recorded user interactions with an intelligent apartment. Besides offering various interactive capabilities itself, the apartment is also inhabited by a social robot that is available as a humanoid interface. This paper presents a multi-modal corpus that contains goal-directed actions of naive users in attempts to solve a number of predefined tasks. Alongside audio and video recordings, our data-set consists of large amount of temporally aligned sensory data and system behavior provided by the environment and its interactive components. Non-verbal system responses such as changes in light or display contents, as well as robot and apartment utterances and gestures serve as a rich basis for later in-depth analysis. Manual annotations provide further information about meta data like the current course of study and user behavior including the incorporated modality, all literal utterances, language features, emotional expressions, foci of attention, and addressees. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1549/ |
| https://www.aclweb.org/anthology/L16-1549 | |
| PWC | https://paperswithcode.com/paper/how-to-address-smart-homes-with-a-social |
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SimpleScience: Lexical Simplification of Scientific Terminology
| Title | SimpleScience: Lexical Simplification of Scientific Terminology |
| Authors | Yea-Seul Kim, Jessica Hullman, Matthew Burgess, Eytan Adar |
| Abstract | |
| Tasks | Lexical Simplification, Word Embeddings |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1114/ |
| https://www.aclweb.org/anthology/D16-1114 | |
| PWC | https://paperswithcode.com/paper/simplescience-lexical-simplification-of |
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Nonparametric Bayesian Models for Spoken Language Understanding
| Title | Nonparametric Bayesian Models for Spoken Language Understanding |
| Authors | Kei Wakabayashi, Johane Takeuchi, Kotaro Funakoshi, Mikio Nakano |
| Abstract | |
| Tasks | Slot Filling, Spoken Language Understanding |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1232/ |
| https://www.aclweb.org/anthology/D16-1232 | |
| PWC | https://paperswithcode.com/paper/nonparametric-bayesian-models-for-spoken |
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Task Lineages: Dialog State Tracking for Flexible Interaction
| Title | Task Lineages: Dialog State Tracking for Flexible Interaction |
| Authors | Sungjin Lee, Am Stent, a |
| Abstract | |
| Tasks | Speech Recognition, Spoken Language Understanding |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3602/ |
| https://www.aclweb.org/anthology/W16-3602 | |
| PWC | https://paperswithcode.com/paper/task-lineages-dialog-state-tracking-for |
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Stochastic Online AUC Maximization
| Title | Stochastic Online AUC Maximization |
| Authors | Yiming Ying, Longyin Wen, Siwei Lyu |
| Abstract | Area under ROC (AUC) is a metric which is widely used for measuring the classification performance for imbalanced data. It is of theoretical and practical interest to develop online learning algorithms that maximizes AUC for large-scale data. A specific challenge in developing online AUC maximization algorithm is that the learning objective function is usually defined over a pair of training examples of opposite classes, and existing methods achieves on-line processing with higher space and time complexity. In this work, we propose a new stochastic online algorithm for AUC maximization. In particular, we show that AUC optimization can be equivalently formulated as a convex-concave saddle point problem. From this saddle representation, a stochastic online algorithm (SOLAM) is proposed which has time and space complexity of one datum. We establish theoretical convergence of SOLAM with high probability and demonstrate its effectiveness and efficiency on standard benchmark datasets. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6065-stochastic-online-auc-maximization |
| http://papers.nips.cc/paper/6065-stochastic-online-auc-maximization.pdf | |
| PWC | https://paperswithcode.com/paper/stochastic-online-auc-maximization |
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Reddit Temporal N-gram Corpus and its Applications on Paraphrase and Semantic Similarity in Social Media using a Topic-based Latent Semantic Analysis
| Title | Reddit Temporal N-gram Corpus and its Applications on Paraphrase and Semantic Similarity in Social Media using a Topic-based Latent Semantic Analysis |
| Authors | Anh Dang, Abidalrahman Moh{'}d, Aminul Islam, Rosane Minghim, Michael Smit, Evangelos Milios |
| Abstract | This paper introduces a new large-scale n-gram corpus that is created specifically from social media text. Two distinguishing characteristics of this corpus are its monthly temporal attribute and that it is created from 1.65 billion comments of user-generated text in Reddit. The usefulness of this corpus is exemplified and evaluated by a novel Topic-based Latent Semantic Analysis (TLSA) algorithm. The experimental results show that unsupervised TLSA outperforms all the state-of-the-art unsupervised and semi-supervised methods in SEMEVAL 2015: paraphrase and semantic similarity in Twitter tasks. |
| Tasks | Information Retrieval, Language Modelling, Machine Translation, Named Entity Recognition, Paraphrase Identification, Rumour Detection, Semantic Similarity, Semantic Textual Similarity, Speech Recognition |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1335/ |
| https://www.aclweb.org/anthology/C16-1335 | |
| PWC | https://paperswithcode.com/paper/reddit-temporal-n-gram-corpus-and-its |
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Transforming Dependency Structures to Logical Forms for Semantic Parsing
| Title | Transforming Dependency Structures to Logical Forms for Semantic Parsing |
| Authors | Siva Reddy, Oscar T{"a}ckstr{"o}m, Michael Collins, Tom Kwiatkowski, Dipanjan Das, Mark Steedman, Mirella Lapata |
| Abstract | The strongly typed syntax of grammar formalisms such as CCG, TAG, LFG and HPSG offers a synchronous framework for deriving syntactic structures and semantic logical forms. In contrast{—}partly due to the lack of a strong type system{—}dependency structures are easy to annotate and have become a widely used form of syntactic analysis for many languages. However, the lack of a type system makes a formal mechanism for deriving logical forms from dependency structures challenging. We address this by introducing a robust system based on the lambda calculus for deriving neo-Davidsonian logical forms from dependency trees. These logical forms are then used for semantic parsing of natural language to Freebase. Experiments on the Free917 and Web-Questions datasets show that our representation is superior to the original dependency trees and that it outperforms a CCG-based representation on this task. Compared to prior work, we obtain the strongest result to date on Free917 and competitive results on WebQuestions. |
| Tasks | Question Answering, Semantic Parsing |
| Published | 2016-01-01 |
| URL | https://www.aclweb.org/anthology/Q16-1010/ |
| https://www.aclweb.org/anthology/Q16-1010 | |
| PWC | https://paperswithcode.com/paper/transforming-dependency-structures-to-logical |
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Improving Document Ranking using Query Expansion and Classification Techniques for Mixed Script Information Retrieval
| Title | Improving Document Ranking using Query Expansion and Classification Techniques for Mixed Script Information Retrieval |
| Authors | Subham Kumar, Anwesh Sinha Ray, Sabyasachi Kamila, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya |
| Abstract | |
| Tasks | Document Ranking, Information Retrieval, Transliteration |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-6311/ |
| https://www.aclweb.org/anthology/W16-6311 | |
| PWC | https://paperswithcode.com/paper/improving-document-ranking-using-query |
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Linguistic Issues in the Machine Transliteration of Chinese, Japanese and Arabic Names
| Title | Linguistic Issues in the Machine Transliteration of Chinese, Japanese and Arabic Names |
| Authors | Jack Halpern |
| Abstract | |
| Tasks | Entity Extraction, Transliteration |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2707/ |
| https://www.aclweb.org/anthology/W16-2707 | |
| PWC | https://paperswithcode.com/paper/linguistic-issues-in-the-machine |
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Scalable Semi-Supervised Query Classification Using Matrix Sketching
| Title | Scalable Semi-Supervised Query Classification Using Matrix Sketching |
| Authors | Young-Bum Kim, Karl Stratos, Ruhi Sarikaya |
| Abstract | |
| Tasks | Intent Classification, Representation Learning, Sentence Classification |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-2002/ |
| https://www.aclweb.org/anthology/P16-2002 | |
| PWC | https://paperswithcode.com/paper/scalable-semi-supervised-query-classification |
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