Paper Group NANR 66
Neural Clinical Paraphrase Generation with Attention. Ambient Search: A Document Retrieval System for Speech Streams. CLARIN-EL Web-based Annotation Tool. Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings. The WebNLG Challenge: Generating Text from DBPedia Data. Learning to recognise named entities in …
Neural Clinical Paraphrase Generation with Attention
| Title | Neural Clinical Paraphrase Generation with Attention |
| Authors | Sadid A. Hasan, Bo Liu, Joey Liu, Ashequl Qadir, Kathy Lee, Vivek Datla, Aaditya Prakash, Oladimeji Farri |
| Abstract | Paraphrase generation is important in various applications such as search, summarization, and question answering due to its ability to generate textual alternatives while keeping the overall meaning intact. Clinical paraphrase generation is especially vital in building patient-centric clinical decision support (CDS) applications where users are able to understand complex clinical jargons via easily comprehensible alternative paraphrases. This paper presents Neural Clinical Paraphrase Generation (NCPG), a novel approach that casts the task as a monolingual neural machine translation (NMT) problem. We propose an end-to-end neural network built on an attention-based bidirectional Recurrent Neural Network (RNN) architecture with an encoder-decoder framework to perform the task. Conventional bilingual NMT models mostly rely on word-level modeling and are often limited by out-of-vocabulary (OOV) issues. In contrast, we represent the source and target paraphrase pairs as character sequences to address this limitation. To the best of our knowledge, this is the first work that uses attention-based RNNs for clinical paraphrase generation and also proposes an end-to-end character-level modeling for this task. Extensive experiments on a large curated clinical paraphrase corpus show that the attention-based NCPG models achieve improvements of up to 5.2 BLEU points and 0.5 METEOR points over a non-attention based strong baseline for word-level modeling, whereas further gains of up to 6.1 BLEU points and 1.3 METEOR points are obtained by the character-level NCPG models over their word-level counterparts. Overall, our models demonstrate comparable performance relative to the state-of-the-art phrase-based non-neural models. |
| Tasks | Document Summarization, Information Retrieval, Machine Translation, Paraphrase Generation, Question Answering, Sentence Compression, Text Generation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4207/ |
| https://www.aclweb.org/anthology/W16-4207 | |
| PWC | https://paperswithcode.com/paper/neural-clinical-paraphrase-generation-with |
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Ambient Search: A Document Retrieval System for Speech Streams
| Title | Ambient Search: A Document Retrieval System for Speech Streams |
| Authors | Benjamin Milde, Jonas Wacker, Stefan Radomski, Max M{"u}hlh{"a}user, Chris Biemann |
| Abstract | We present Ambient Search, an open source system for displaying and retrieving relevant documents in real time for speech input. The system works ambiently, that is, it unobstructively listens to speech streams in the background, identifies keywords and keyphrases for query construction and continuously serves relevant documents from its index. Query terms are ranked with Word2Vec and TF-IDF and are continuously updated to allow for ongoing querying of a document collection. The retrieved documents, in our case Wikipedia articles, are visualized in real time in a browser interface. Our evaluation shows that Ambient Search compares favorably to another implicit information retrieval system on speech streams. Furthermore, we extrinsically evaluate multiword keyphrase generation, showing positive impact for manual transcriptions. |
| Tasks | Information Retrieval, Speech Recognition |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1196/ |
| https://www.aclweb.org/anthology/C16-1196 | |
| PWC | https://paperswithcode.com/paper/ambient-search-a-document-retrieval-system |
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CLARIN-EL Web-based Annotation Tool
| Title | CLARIN-EL Web-based Annotation Tool |
| Authors | Ioannis Manousos Katakis, Georgios Petasis, Vangelis Karkaletsis |
| Abstract | This paper presents a new Web-based annotation tool, the {}CLARIN-EL Web-based Annotation Tool{''}. Based on an existing annotation infrastructure offered by the {}Ellogon{''} language enginneering platform, this new tool transfers a large part of Ellogon{'}s features and functionalities to a Web environment, by exploiting the capabilities of cloud computing. This new annotation tool is able to support a wide range of annotation tasks, through user provided annotation schemas in XML. The new annotation tool has already been employed in several annotation tasks, including the anotation of arguments, which is presented as a use case. The CLARIN-EL annotation tool is compared to existing solutions along several dimensions and features. Finally, future work includes the improvement of integration with the CLARIN-EL infrastructure, and the inclusion of features not currently supported, such as the annotation of aligned documents. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1713/ |
| https://www.aclweb.org/anthology/L16-1713 | |
| PWC | https://paperswithcode.com/paper/clarin-el-web-based-annotation-tool |
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Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings
| Title | Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings |
| Authors | Akash Bharadwaj, David Mortensen, Chris Dyer, Jaime Carbonell |
| Abstract | |
| Tasks | Cross-Lingual Transfer, Feature Engineering, Named Entity Recognition, Transliteration, Word Embeddings |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1153/ |
| https://www.aclweb.org/anthology/D16-1153 | |
| PWC | https://paperswithcode.com/paper/phonologically-aware-neural-model-for-named |
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The WebNLG Challenge: Generating Text from DBPedia Data
| Title | The WebNLG Challenge: Generating Text from DBPedia Data |
| Authors | Emilie Colin, Claire Gardent, Yassine M{'}rabet, Shashi Narayan, Laura Perez-Beltrachini |
| Abstract | |
| Tasks | Text Generation |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-6626/ |
| https://www.aclweb.org/anthology/W16-6626 | |
| PWC | https://paperswithcode.com/paper/the-webnlg-challenge-generating-text-from |
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Learning to recognise named entities in tweets by exploiting weakly labelled data
| Title | Learning to recognise named entities in tweets by exploiting weakly labelled data |
| Authors | Kurt Junshean Espinosa, Riza Theresa Batista-Navarro, Sophia Ananiadou |
| Abstract | Named entity recognition (NER) in social media (e.g., Twitter) is a challenging task due to the noisy nature of text. As part of our participation in the W-NUT 2016 Named Entity Recognition Shared Task, we proposed an unsupervised learning approach using deep neural networks and leverage a knowledge base (i.e., DBpedia) to bootstrap sparse entity types with weakly labelled data. To further boost the performance, we employed a more sophisticated tagging scheme and applied dropout as a regularisation technique in order to reduce overfitting. Even without hand-crafting linguistic features nor leveraging any of the W-NUT-provided gazetteers, we obtained robust performance with our approach, which ranked third amongst all shared task participants according to the official evaluation on a gold standard named entity-annotated corpus of 3,856 tweets. |
| Tasks | Named Entity Recognition |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-3921/ |
| https://www.aclweb.org/anthology/W16-3921 | |
| PWC | https://paperswithcode.com/paper/learning-to-recognise-named-entities-in |
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Exploring Language Variation Across Europe - A Web-based Tool for Computational Sociolinguistics
| Title | Exploring Language Variation Across Europe - A Web-based Tool for Computational Sociolinguistics |
| Authors | Dirk Hovy, Anders Johannsen |
| Abstract | Language varies not only between countries, but also along regional and socio-demographic lines. This variation is one of the driving factors behind language change. However, investigating language variation is a complex undertaking: the more factors we want to consider, the more data we need. Traditional qualitative methods are not well-suited to do this, an therefore restricted to isolated factors. This reduction limits the potential insights, and risks attributing undue importance to easily observed factors. While there is a large interest in linguistics to increase the quantitative aspect of such studies, it requires training in both variational linguistics and computational methods, a combination that is still not common. We take a first step here to alleviating the problem by providing an interface, www.languagevariation.com, to explore large-scale language variation along multiple socio-demographic factors {–} without programming knowledge. It makes use of large amounts of data and provides statistical analyses, maps, and interactive features that will enable scholars to explore language variation in a data-driven way. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1477/ |
| https://www.aclweb.org/anthology/L16-1477 | |
| PWC | https://paperswithcode.com/paper/exploring-language-variation-across-europe-a |
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The CoreGram Project: Theoretical Linguistics, Theory Development and Verification
| Title | The CoreGram Project: Theoretical Linguistics, Theory Development and Verification |
| Authors | Stefan M{"u}ller |
| Abstract | |
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| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-1001/ |
| https://www.aclweb.org/anthology/Y16-1001 | |
| PWC | https://paperswithcode.com/paper/the-coregram-project-theoretical-linguistics |
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Toward the automatic extraction of knowledge of usable goods
| Title | Toward the automatic extraction of knowledge of usable goods |
| Authors | Mei Uemura, Naho Orita, Naoaki Okazaki, Kentaro Inui |
| Abstract | |
| Tasks | Natural Language Inference, Question Answering |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-2026/ |
| https://www.aclweb.org/anthology/Y16-2026 | |
| PWC | https://paperswithcode.com/paper/toward-the-automatic-extraction-of-knowledge |
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Recognizing Open-Vocabulary Relations between Objects in Images
| Title | Recognizing Open-Vocabulary Relations between Objects in Images |
| Authors | Masayasu Muraoka, Sumit Maharjan, Masaki Saito, Kota Yamaguchi, Naoaki Okazaki, Takayuki Okatani, Kentaro Inui |
| Abstract | |
| Tasks | Language Modelling, Object Recognition |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-2022/ |
| https://www.aclweb.org/anthology/Y16-2022 | |
| PWC | https://paperswithcode.com/paper/recognizing-open-vocabulary-relations-between |
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The Significance of Background Information in Acceptability Judgements of Korean Sentences
| Title | The Significance of Background Information in Acceptability Judgements of Korean Sentences |
| Authors | Jae-Woong Choe |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-1004/ |
| https://www.aclweb.org/anthology/Y16-1004 | |
| PWC | https://paperswithcode.com/paper/the-significance-of-background-information-in |
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The Inner Circle vs. the Outer Circle or British English vs. American English
| Title | The Inner Circle vs. the Outer Circle or British English vs. American English |
| Authors | Yong-hun Lee, Ki-suk Jun |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-3004/ |
| https://www.aclweb.org/anthology/Y16-3004 | |
| PWC | https://paperswithcode.com/paper/the-inner-circle-vs-the-outer-circle-or |
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The sources of new words and expressions in the Chinese Internet language and the ways by which they enter the Internet language
| Title | The sources of new words and expressions in the Chinese Internet language and the ways by which they enter the Internet language |
| Authors | Aleks Sboev, r |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-3006/ |
| https://www.aclweb.org/anthology/Y16-3006 | |
| PWC | https://paperswithcode.com/paper/the-sources-of-new-words-and-expressions-in |
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SMTPOST Using Statistical Machine Translation Approach in Filipino Part-of-Speech Tagging
| Title | SMTPOST Using Statistical Machine Translation Approach in Filipino Part-of-Speech Tagging |
| Authors | Nicco Nocon, Allan Borra |
| Abstract | |
| Tasks | Machine Translation, Part-Of-Speech Tagging |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-3010/ |
| https://www.aclweb.org/anthology/Y16-3010 | |
| PWC | https://paperswithcode.com/paper/smtpost-using-statistical-machine-translation |
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Phonological Principles for Automatic Phonetic Transcription of Khmer Orthographic Words
| Title | Phonological Principles for Automatic Phonetic Transcription of Khmer Orthographic Words |
| Authors | Makara Sok, Larin Adams |
| Abstract | |
| Tasks | |
| Published | 2016-10-01 |
| URL | https://www.aclweb.org/anthology/Y16-3013/ |
| https://www.aclweb.org/anthology/Y16-3013 | |
| PWC | https://paperswithcode.com/paper/phonological-principles-for-automatic |
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