Paper Group NANR 156
Neural Machine Translation of Logographic Language Using Sub-character Level Information. Aspect Based Sentiment Analysis into the Wild. Machine translation at Booking.com: what’s next?. A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database. Accurate Text-Enhanced Knowledge Graph Representation Learning. STEVENDU …
Neural Machine Translation of Logographic Language Using Sub-character Level Information
| Title | Neural Machine Translation of Logographic Language Using Sub-character Level Information |
| Authors | Longtu Zhang, Mamoru Komachi |
| Abstract | Recent neural machine translation (NMT) systems have been greatly improved by encoder-decoder models with attention mechanisms and sub-word units. However, important differences between languages with logographic and alphabetic writing systems have long been overlooked. This study focuses on these differences and uses a simple approach to improve the performance of NMT systems utilizing decomposed sub-character level information for logographic languages. Our results indicate that our approach not only improves the translation capabilities of NMT systems between Chinese and English, but also further improves NMT systems between Chinese and Japanese, because it utilizes the shared information brought by similar sub-character units. |
| Tasks | Machine Translation, Word Embeddings |
| Published | 2018-10-01 |
| URL | https://www.aclweb.org/anthology/W18-6303/ |
| https://www.aclweb.org/anthology/W18-6303 | |
| PWC | https://paperswithcode.com/paper/neural-machine-translation-of-logographic-1 |
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Aspect Based Sentiment Analysis into the Wild
| Title | Aspect Based Sentiment Analysis into the Wild |
| Authors | Caroline Brun, Vassilina Nikoulina |
| Abstract | In this paper, we test state-of-the-art Aspect Based Sentiment Analysis (ABSA) systems trained on a widely used dataset on actual data. We created a new manually annotated dataset of user generated data from the same domain as the training dataset, but from other sources and analyse the differences between the new and the standard ABSA dataset. We then analyse the results in performance of different versions of the same system on both datasets. We also propose light adaptation methods to increase system robustness. |
| Tasks | Aspect-Based Sentiment Analysis, Sentiment Analysis |
| Published | 2018-10-01 |
| URL | https://www.aclweb.org/anthology/W18-6217/ |
| https://www.aclweb.org/anthology/W18-6217 | |
| PWC | https://paperswithcode.com/paper/aspect-based-sentiment-analysis-into-the-wild |
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Machine translation at Booking.com: what’s next?
| Title | Machine translation at Booking.com: what’s next? |
| Authors | Maxim Khalilov |
| Abstract | |
| Tasks | Automatic Post-Editing, Machine Translation |
| Published | 2018-03-01 |
| URL | https://www.aclweb.org/anthology/W18-2104/ |
| https://www.aclweb.org/anthology/W18-2104 | |
| PWC | https://paperswithcode.com/paper/machine-translation-at-bookingcom-whats-next |
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A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database
| Title | A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database |
| Authors | Matthew Shardlow, Nhung Nguyen, Gareth Owen, Claire O{'}Donovan, Andrew Leach, John McNaught, Steve Turner, Sophia Ananiadou |
| Abstract | |
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| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1042/ |
| https://www.aclweb.org/anthology/L18-1042 | |
| PWC | https://paperswithcode.com/paper/a-new-corpus-to-support-text-mining-for-the |
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Accurate Text-Enhanced Knowledge Graph Representation Learning
| Title | Accurate Text-Enhanced Knowledge Graph Representation Learning |
| Authors | Bo An, Bo Chen, Xianpei Han, Le Sun |
| Abstract | Previous representation learning techniques for knowledge graph representation usually represent the same entity or relation in different triples with the same representation, without considering the ambiguity of relations and entities. To appropriately handle the semantic variety of entities/relations in distinct triples, we propose an accurate text-enhanced knowledge graph representation learning method, which can represent a relation/entity with different representations in different triples by exploiting additional textual information. Specifically, our method enhances representations by exploiting the entity descriptions and triple-specific relation mention. And a mutual attention mechanism between relation mention and entity description is proposed to learn more accurate textual representations for further improving knowledge graph representation. Experimental results show that our method achieves the state-of-the-art performance on both link prediction and triple classification tasks, and significantly outperforms previous text-enhanced knowledge representation models. |
| Tasks | Graph Representation Learning, Knowledge Graphs, Link Prediction, Representation Learning |
| Published | 2018-06-01 |
| URL | https://www.aclweb.org/anthology/N18-1068/ |
| https://www.aclweb.org/anthology/N18-1068 | |
| PWC | https://paperswithcode.com/paper/accurate-text-enhanced-knowledge-graph |
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STEVENDU2018’s system in VarDial 2018: Discriminating between Dutch and Flemish in Subtitles
| Title | STEVENDU2018’s system in VarDial 2018: Discriminating between Dutch and Flemish in Subtitles |
| Authors | Steven Du, Yuan Yuan Wang |
| Abstract | This paper introduces the submitted system for team STEVENDU2018 during VarDial 2018 Discriminating between Dutch and Flemish in Subtitles(DFS). Post evaluation analyses are also presented, the results obtained indicate that it is a challenging task to discriminate Dutch and Flemish. |
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| Published | 2018-08-01 |
| URL | https://www.aclweb.org/anthology/W18-3926/ |
| https://www.aclweb.org/anthology/W18-3926 | |
| PWC | https://paperswithcode.com/paper/stevendu2018s-system-in-vardial-2018 |
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A Parser for LTAG and Frame Semantics
| Title | A Parser for LTAG and Frame Semantics |
| Authors | David Arps, Simon Petitjean |
| Abstract | |
| Tasks | Semantic Parsing |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1351/ |
| https://www.aclweb.org/anthology/L18-1351 | |
| PWC | https://paperswithcode.com/paper/a-parser-for-ltag-and-frame-semantics |
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A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines
| Title | A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines |
| Authors | Salvatore Romeo, Giovanni Da San Martino, Alberto Barr{'o}n-Cede{~n}o, Aless Moschitti, ro |
| Abstract | Although deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution. Community Question Answering is a research area that benefits from deep linguistic analysis to improve the experience of the community of forum users. In this paper, we present a UIMA framework to distribute the computation of cQA tasks over computer clusters such that traditional systems can scale to large datasets and deliver fast processing. |
| Tasks | Community Question Answering, Question Answering |
| Published | 2018-07-01 |
| URL | https://www.aclweb.org/anthology/P18-4023/ |
| https://www.aclweb.org/anthology/P18-4023 | |
| PWC | https://paperswithcode.com/paper/a-flexible-efficient-and-accurate-framework |
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NLP Corpus Observatory – Looking for Constellations in Parallel Corpora to Improve Learners’ Collocational Skills
| Title | NLP Corpus Observatory – Looking for Constellations in Parallel Corpora to Improve Learners’ Collocational Skills |
| Authors | Gerold Schneider, Johannes Gra{"e}n |
| Abstract | |
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| Published | 2018-11-01 |
| URL | https://www.aclweb.org/anthology/W18-7108/ |
| https://www.aclweb.org/anthology/W18-7108 | |
| PWC | https://paperswithcode.com/paper/nlp-corpus-observatory-a-looking-for |
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ANCOR-AS: Enriching the ANCOR Corpus with Syntactic Annotations
| Title | ANCOR-AS: Enriching the ANCOR Corpus with Syntactic Annotations |
| Authors | Lo{"\i}c Grobol, Isabelle Tellier, {'E}ric de la Clergerie, Marco Dinarelli, L, Fr{'e}d{'e}ric ragin |
| Abstract | |
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| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1064/ |
| https://www.aclweb.org/anthology/L18-1064 | |
| PWC | https://paperswithcode.com/paper/ancor-as-enriching-the-ancor-corpus-with |
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PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering
| Title | PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering |
| Authors | Andrei Dulceanu, Thang Le Dinh, Walter Chang, Trung Bui, Doo Soon Kim, Manh Chien Vu, Seokhwan Kim |
| Abstract | |
| Tasks | Answer Selection, Community Question Answering, Question Answering |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1438/ |
| https://www.aclweb.org/anthology/L18-1438 | |
| PWC | https://paperswithcode.com/paper/photoshopquia-a-corpus-of-non-factoid |
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ParCorFull: a Parallel Corpus Annotated with Full Coreference
| Title | ParCorFull: a Parallel Corpus Annotated with Full Coreference |
| Authors | Ekaterina Lapshinova-Koltunski, Christian Hardmeier, Pauline Krielke |
| Abstract | |
| Tasks | Coreference Resolution, Machine Translation |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1065/ |
| https://www.aclweb.org/anthology/L18-1065 | |
| PWC | https://paperswithcode.com/paper/parcorfull-a-parallel-corpus-annotated-with |
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CPJD Corpus: Crowdsourced Parallel Speech Corpus of Japanese Dialects
| Title | CPJD Corpus: Crowdsourced Parallel Speech Corpus of Japanese Dialects |
| Authors | Shinnosuke Takamichi, Hiroshi Saruwatari |
| Abstract | |
| Tasks | Machine Translation, Speech Recognition, Speech Synthesis |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1067/ |
| https://www.aclweb.org/anthology/L18-1067 | |
| PWC | https://paperswithcode.com/paper/cpjd-corpus-crowdsourced-parallel-speech |
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The LREC Workshops Map
| Title | The LREC Workshops Map |
| Authors | Roberto Bartolini, Sara Goggi, Monica Monachini, Gabriella Pardelli |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1088/ |
| https://www.aclweb.org/anthology/L18-1088 | |
| PWC | https://paperswithcode.com/paper/the-lrec-workshops-map |
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Chinese Relation Classification using Long Short Term Memory Networks
| Title | Chinese Relation Classification using Long Short Term Memory Networks |
| Authors | Linrui Zhang, Dan Moldovan |
| Abstract | |
| Tasks | Relation Classification, Relation Extraction |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1077/ |
| https://www.aclweb.org/anthology/L18-1077 | |
| PWC | https://paperswithcode.com/paper/chinese-relation-classification-using-long |
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