Paper Group NANR 120
Combining Predicate-Argument Structure and Operator Projection: Clause Structure in Role and Reference Grammar. Clinical Event Detection with Hybrid Neural Architecture. Extracting Personal Medical Events for User Timeline Construction using Minimal Supervision. Detecting mentions of pain and acute confusion in Finnish clinical text. Arabic-English …
Combining Predicate-Argument Structure and Operator Projection: Clause Structure in Role and Reference Grammar
| Title | Combining Predicate-Argument Structure and Operator Projection: Clause Structure in Role and Reference Grammar |
| Authors | Laura Kallmeyer, Rainer Osswald |
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| Published | 2017-09-01 |
| URL | https://www.aclweb.org/anthology/W17-6207/ |
| https://www.aclweb.org/anthology/W17-6207 | |
| PWC | https://paperswithcode.com/paper/combining-predicate-argument-structure-and |
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Clinical Event Detection with Hybrid Neural Architecture
| Title | Clinical Event Detection with Hybrid Neural Architecture |
| Authors | Adyasha Maharana, Meliha Yetisgen |
| Abstract | Event detection from clinical notes has been traditionally solved with rule based and statistical natural language processing (NLP) approaches that require extensive domain knowledge and feature engineering. In this paper, we have explored the feasibility of approaching this task with recurrent neural networks, clinical word embeddings and introduced a hybrid architecture to improve detection for entities with smaller representation in the dataset. A comparative analysis is also done which reveals the complementary behavior of neural networks and conditional random fields in clinical entity detection. |
| Tasks | Feature Engineering, Word Embeddings |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2345/ |
| https://www.aclweb.org/anthology/W17-2345 | |
| PWC | https://paperswithcode.com/paper/clinical-event-detection-with-hybrid-neural |
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Extracting Personal Medical Events for User Timeline Construction using Minimal Supervision
| Title | Extracting Personal Medical Events for User Timeline Construction using Minimal Supervision |
| Authors | Aakanksha Naik, Chris Bogart, Carolyn Rose |
| Abstract | In this paper, we describe a system for automatic construction of user disease progression timelines from their posts in online support groups using minimal supervision. In recent years, several online support groups have been established which has led to a huge increase in the amount of patient-authored text available. Creating systems which can automatically extract important medical events and create disease progression timelines for users from such text can help in patient health monitoring as well as studying links between medical events and users{'} participation in support groups. Prior work in this domain has used manually constructed keyword sets to detect medical events. In this work, our aim is to perform medical event detection using minimal supervision in order to develop a more general timeline construction system. Our system achieves an accuracy of 55.17{%}, which is 92{%} of the performance achieved by a supervised baseline system. |
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| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2346/ |
| https://www.aclweb.org/anthology/W17-2346 | |
| PWC | https://paperswithcode.com/paper/extracting-personal-medical-events-for-user |
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Detecting mentions of pain and acute confusion in Finnish clinical text
| Title | Detecting mentions of pain and acute confusion in Finnish clinical text |
| Authors | Hans Moen, Kai Hakala, Farrokh Mehryary, Laura-Maria Peltonen, Tapio Salakoski, Filip Ginter, Sanna Salanter{"a} |
| Abstract | We study and compare two different approaches to the task of automatic assignment of predefined classes to clinical free-text narratives. In the first approach this is treated as a traditional mention-level named-entity recognition task, while the second approach treats it as a sentence-level multi-label classification task. Performance comparison across these two approaches is conducted in the form of sentence-level evaluation and state-of-the-art methods for both approaches are evaluated. The experiments are done on two data sets consisting of Finnish clinical text, manually annotated with respect to the topics pain and acute confusion. Our results suggest that the mention-level named-entity recognition approach outperforms sentence-level classification overall, but the latter approach still manages to achieve the best prediction scores on several annotation classes. |
| Tasks | Information Retrieval, Multi-Label Classification, Named Entity Recognition |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2347/ |
| https://www.aclweb.org/anthology/W17-2347 | |
| PWC | https://paperswithcode.com/paper/detecting-mentions-of-pain-and-acute |
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Arabic-English Text Translation Leveraging Hybrid NER
| Title | Arabic-English Text Translation Leveraging Hybrid NER |
| Authors | Emna Hkiri, Souheyl Mallat, Mounir Zrigui |
| Abstract | |
| Tasks | Information Retrieval, Machine Translation, Morphological Analysis, Word Sense Disambiguation |
| Published | 2017-11-01 |
| URL | https://www.aclweb.org/anthology/Y17-1019/ |
| https://www.aclweb.org/anthology/Y17-1019 | |
| PWC | https://paperswithcode.com/paper/arabic-english-text-translation-leveraging |
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On the ``Calligraphy’’ of Books
| Title | On the ``Calligraphy’’ of Books | |
| Authors | Vanessa Queiroz Marinho, Henrique Ferraz de Arruda, Thales Sinelli, Luciano da Fontoura Costa, Diego Raphael Amancio |
| Abstract | Authorship attribution is a natural language processing task that has been widely studied, often by considering small order statistics. In this paper, we explore a complex network approach to assign the authorship of texts based on their mesoscopic representation, in an attempt to capture the flow of the narrative. Indeed, as reported in this work, such an approach allowed the identification of the dominant narrative structure of the studied authors. This has been achieved due to the ability of the mesoscopic approach to take into account relationships between different, not necessarily adjacent, parts of the text, which is able to capture the story flow. The potential of the proposed approach has been illustrated through principal component analysis, a comparison with the chance baseline method, and network visualization. Such visualizations reveal individual characteristics of the authors, which can be understood as a kind of calligraphy. |
| Tasks | Machine Translation, Sentiment Analysis |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2401/ |
| https://www.aclweb.org/anthology/W17-2401 | |
| PWC | https://paperswithcode.com/paper/on-the-calligraphy-of-books-1 |
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TTCS$^\mathcalE$: a Vectorial Resource for Computing Conceptual Similarity
| Title | TTCS$^\mathcalE$: a Vectorial Resource for Computing Conceptual Similarity |
| Authors | Enrico Mensa, Daniele P. Radicioni, Antonio Lieto |
| Abstract | In this paper we introduce the TTCS$^{\mathcal{E}}$, a linguistic resource that relies on BabelNet, NASARI and ConceptNet, that has now been used to compute the conceptual similarity between concept pairs. The conceptual representation herein provides uniform access to concepts based on BabelNet synset IDs, and consists of a vector-based semantic representation which is compliant with the Conceptual Spaces, a geometric framework for common-sense knowledge representation and reasoning. The TTCS$^{\mathcal{E}}$ has been evaluated in a preliminary experimentation on a conceptual similarity task. |
| Tasks | Common Sense Reasoning |
| Published | 2017-04-01 |
| URL | https://www.aclweb.org/anthology/W17-1912/ |
| https://www.aclweb.org/anthology/W17-1912 | |
| PWC | https://paperswithcode.com/paper/ttcse-a-vectorial-resource-for-computing |
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Distantly Supervised POS Tagging of Low-Resource Languages under Extreme Data Sparsity: The Case of Hittite
| Title | Distantly Supervised POS Tagging of Low-Resource Languages under Extreme Data Sparsity: The Case of Hittite |
| Authors | Maria Sukhareva, Francesco Fuscagni, Johannes Daxenberger, Susanne G{"o}rke, Doris Prechel, Iryna Gurevych |
| Abstract | This paper presents a statistical approach to automatic morphosyntactic annotation of Hittite transcripts. Hittite is an extinct Indo-European language using the cuneiform script. There are currently no morphosyntactic annotations available for Hittite, so we explored methods of distant supervision. The annotations were projected from parallel German translations of the Hittite texts. In order to reduce data sparsity, we applied stemming of German and Hittite texts. As there is no off-the-shelf Hittite stemmer, a stemmer for Hittite was developed for this purpose. The resulting annotation projections were used to train a POS tagger, achieving an accuracy of 69{%} on a test sample. To our knowledge, this is the first attempt of statistical POS tagging of a cuneiform language. |
| Tasks | Information Retrieval, Machine Translation |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2213/ |
| https://www.aclweb.org/anthology/W17-2213 | |
| PWC | https://paperswithcode.com/paper/distantly-supervised-pos-tagging-of-low |
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Merging knowledge bases in different languages
| Title | Merging knowledge bases in different languages |
| Authors | Jer{'o}nimo Hern{'a}ndez-Gonz{'a}lez, Estevam R. Hruschka Jr., Tom M. Mitchell |
| Abstract | Recently, different systems which learn to populate and extend a knowledge base (KB) from the web in different languages have been presented. Although a large set of concepts should be learnt independently from the language used to read, there are facts which are expected to be more easily gathered in local language (e.g., culture or geography). A system that merges KBs learnt in different languages will benefit from the complementary information as long as common beliefs are identified, as well as from redundancy present in web pages written in different languages. In this paper, we deal with the problem of identifying equivalent beliefs (or concepts) across language specific KBs, assuming that they share the same ontology of categories and relations. In a case study with two KBs independently learnt from different inputs, namely web pages written in English and web pages written in Portuguese respectively, we report on the results of two methodologies: an approach based on personalized PageRank and an inference technique to find out common relevant paths through the KBs. The proposed inference technique efficiently identifies relevant paths, outperforming the baseline (a dictionary-based classifier) in the vast majority of tested categories. |
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| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2403/ |
| https://www.aclweb.org/anthology/W17-2403 | |
| PWC | https://paperswithcode.com/paper/merging-knowledge-bases-in-different |
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Spectral Graph-Based Method of Multimodal Word Embedding
| Title | Spectral Graph-Based Method of Multimodal Word Embedding |
| Authors | Kazuki Fukui, Takamasa Oshikiri, Hidetoshi Shimodaira |
| Abstract | In this paper, we propose a novel method for multimodal word embedding, which exploit a generalized framework of multi-view spectral graph embedding to take into account visual appearances or scenes denoted by words in a corpus. We evaluated our method through word similarity tasks and a concept-to-image search task, having found that it provides word representations that reflect visual information, while somewhat trading-off the performance on the word similarity tasks. Moreover, we demonstrate that our method captures multimodal linguistic regularities, which enable recovering relational similarities between words and images by vector arithmetics. |
| Tasks | Graph Embedding, Image Retrieval, Machine Translation, Part-Of-Speech Tagging, Question Answering, Text Classification, Visual Question Answering |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2405/ |
| https://www.aclweb.org/anthology/W17-2405 | |
| PWC | https://paperswithcode.com/paper/spectral-graph-based-method-of-multimodal |
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A Graph Based Semi-Supervised Approach for Analysis of Derivational Nouns in Sanskrit
| Title | A Graph Based Semi-Supervised Approach for Analysis of Derivational Nouns in Sanskrit |
| Authors | Amrith Krishna, Pavankumar Satuluri, Harshavardhan Ponnada, Muneeb Ahmed, Gulab Arora, Kaustubh Hiware, Pawan Goyal |
| Abstract | Derivational nouns are widely used in Sanskrit corpora and represent an important cornerstone of productivity in the language. Currently there exists no analyser that identifies the derivational nouns. We propose a semi supervised approach for identification of derivational nouns in Sanskrit. We not only identify the derivational words, but also link them to their corresponding source words. Our novelty comes in the design of the network structure for the task. The edge weights are featurised based on the phonetic, morphological, syntactic and the semantic similarity shared between the words to be identified. We find that our model is effective for the task, even when we employ a labelled dataset which is only 5 {%} to that of the entire dataset. |
| Tasks | Semantic Similarity, Semantic Textual Similarity |
| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2409/ |
| https://www.aclweb.org/anthology/W17-2409 | |
| PWC | https://paperswithcode.com/paper/a-graph-based-semi-supervised-approach-for |
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A Systematic Comparison of Syntactic Representations of Dependency Parsing
| Title | A Systematic Comparison of Syntactic Representations of Dependency Parsing |
| Authors | Guillaume Wisniewski, Oph{'e}lie Lacroix |
| Abstract | |
| Tasks | Dependency Parsing |
| Published | 2017-05-01 |
| URL | https://www.aclweb.org/anthology/W17-0419/ |
| https://www.aclweb.org/anthology/W17-0419 | |
| PWC | https://paperswithcode.com/paper/a-systematic-comparison-of-syntactic |
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Dependency Tree Transformation with Tree Transducers
| Title | Dependency Tree Transformation with Tree Transducers |
| Authors | Felix Hennig, Arne K{"o}hn |
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| Published | 2017-05-01 |
| URL | https://www.aclweb.org/anthology/W17-0407/ |
| https://www.aclweb.org/anthology/W17-0407 | |
| PWC | https://paperswithcode.com/paper/dependency-tree-transformation-with-tree |
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Automatic Extraction of Parallel Speech Corpora from Dubbed Movies
| Title | Automatic Extraction of Parallel Speech Corpora from Dubbed Movies |
| Authors | Alp {"O}ktem, Mireia Farr{'u}s, Leo Wanner |
| Abstract | This paper presents a methodology to extract parallel speech corpora based on any language pair from dubbed movies, together with an application framework in which some corresponding prosodic parameters are extracted. The obtained parallel corpora are especially suitable for speech-to-speech translation applications when a prosody transfer between source and target languages is desired. |
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| Published | 2017-08-01 |
| URL | https://www.aclweb.org/anthology/W17-2506/ |
| https://www.aclweb.org/anthology/W17-2506 | |
| PWC | https://paperswithcode.com/paper/automatic-extraction-of-parallel-speech |
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Evaluation of language identification methods using 285 languages
| Title | Evaluation of language identification methods using 285 languages |
| Authors | Tommi Jauhiainen, Krister Lind{'e}n, Heidi Jauhiainen |
| Abstract | |
| Tasks | Language Identification |
| Published | 2017-05-01 |
| URL | https://www.aclweb.org/anthology/W17-0221/ |
| https://www.aclweb.org/anthology/W17-0221 | |
| PWC | https://paperswithcode.com/paper/evaluation-of-language-identification-methods |
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