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SemEval 2016: all accepted papers

212 papers · page 1 of 3 · the most cited first · ← SemEval 2016

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  1. SemEval-2016 Task 5: Aspect Based Sentiment AnalysisMaria Pontiki, Dimitris Galanis, Haris Papageorgiou et al.1,281 citations · our summary
  2. SemEval-2016 Task 4: Sentiment Analysis in TwitterPreslav Nakov, Alan Ritter, Sara Rosenthal et al.966 citations · our summary
  3. SemEval-2016 Task 6: Detecting Stance in TweetsSaif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani et al.844 citations · our summary
  4. SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual EvaluationEneko Agirre, Carmen Banea, Daniel Cer et al.519 citations · our summary
  5. SemEval-2016 Task 3: Community Question AnsweringPreslav Nakov, Lluís Màrquez, Alessandro Moschitti et al.241 citations · our summary
  6. SemEval-2016 Task 12: Clinical TempEvalSteven Bethard, Guergana Savova, Wei-Te Chen et al.182 citations · our summary
  7. MITRE at SemEval-2016 Task 6: Transfer Learning for Stance DetectionGuido Zarrella, Amy Marsh173 citations · our summary
  8. SemEval 2016 Task 11: Complex Word IdentificationGustavo Paetzold, Lucia Specia158 citations · our summary
  9. pkudblab at SemEval-2016 Task 6 : A Specific Convolutional Neural Network System for Effective Stance DetectionWan Wei, Xiao Zhang, Xuqin Liu et al.124 citations · our summary
  10. NLANGP at SemEval-2016 Task 5: Improving Aspect Based Sentiment Analysis using Neural Network Features ↗Zhiqiang Toh, Jian Su118 citations
  11. INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis ↗Sebastian Ruder, Parsa Ghaffari, John G. Breslin115 citations
  12. SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision ↗Jan Deriu, Maurice Gonzenbach, Fatih Uzdilli et al.110 citations
  13. SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases ↗Svetlana Kiritchenko, Saif Mohammad, Mohammad Salameh100 citations
  14. SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2) ↗Georgeta Bordea, Els Lefever, Paul Buitelaar88 citations
  15. KeLP at SemEval-2016 Task 3: Learning Semantic Relations between Questions and Answers ↗Simone Filice, Danilo Croce, Alessandro Moschitti et al.84 citations
  16. TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling ↗Alexander Panchenko, Stefano Faralli, Eugen Ruppert et al.63 citations
  17. ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora ↗Alberto Barrón-Cedeño, Daniele Bonadiman, Giovanni Da San Martino et al.62 citations
  18. SemEval-2016 Task 8: Meaning Representation Parsing ↗Jonathan May62 citations
  19. SemEval-2016 Task 14: Semantic Taxonomy Enrichment ↗David Jurgens, Mohammad Taher Pilehvar60 citations
  20. UWB at SemEval-2016 Task 5: Aspect Based Sentiment Analysis ↗Tomáš Hercig, Tomáš Brychcín, Lukáš Svoboda et al.60 citations
  21. DeepStance at SemEval-2016 Task 6: Detecting Stance in Tweets Using Character and Word-Level CNNs ↗Prashanth Vijayaraghavan, Ivan Sysoev, Soroush Vosoughi et al.59 citations
  22. SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings ↗Todor Mihaylov, Preslav Nakov59 citations
  23. IIT-TUDA at SemEval-2016 Task 5: Beyond Sentiment Lexicon: Combining Domain Dependency and Distributional Semantics Features for Aspect Based Sentiment Analysis ↗Ayush Kumar, Sarah Kohail, Amit Kumar et al.57 citations
  24. SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)Nathan Schneider, Dirk Hovy, Anders Johannsen et al.55 citations · our summary
  25. UWB at SemEval-2016 Task 1: Semantic Textual Similarity using Lexical, Syntactic, and Semantic Information ↗Tomáš Brychcín, Lukáš Svoboda55 citations
  26. XRCE at SemEval-2016 Task 5: Feedbacked Ensemble Modeling on Syntactico-Semantic Knowledge for Aspect Based Sentiment Analysis ↗Caroline Brun, Julien Perez, Claude Roux55 citations
  27. RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and Character-Level Neural Translation on AMR Parsing Accuracy ↗Guntis Barzdins, Didzis Gosko54 citations
  28. TakeLab at SemEval-2016 Task 6: Stance Classification in Tweets Using a Genetic Algorithm Based Ensemble ↗Martin Tutek, Ivan Sekulić, Paula Gombar et al.50 citations
  29. UTHealth at SemEval-2016 Task 12: an End-to-End System for Temporal Information Extraction from Clinical Notes ↗Hee-Jin Lee, Hua Xu, Jingqi Wang et al.49 citations
  30. CAMR at SemEval-2016 Task 8: An Extended Transition-based AMR ParserChuan Wang, Sameer Pradhan, Xiaoman Pan et al.48 citations · our summary
  31. CMU at SemEval-2016 Task 8: Graph-based AMR Parsing with Infinite Ramp Loss ↗Jeffrey Flanigan, Chris Dyer, Noah A. Smith et al.48 citations
  32. SemEval-2016 Task 2: Interpretable Semantic Textual Similarity ↗Eneko Agirre, Aitor Gonzalez-Agirre, Iñigo Lopez-Gazpio et al.48 citations
  33. Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction ↗Jason Fries46 citations
  34. UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering ↗Marc Franco-Salvador, Sudipta Kar, Thamar Solorio et al.46 citations
  35. Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity. ↗Barbara Rychalska, Katarzyna Pakulska, Krystyna Chodorowska et al.44 citations
  36. USFD at SemEval-2016 Task 6: Any-Target Stance Detection on Twitter with Autoencoders ↗Isabelle Augenstein, Andreas Vlachos, Kalina Bontcheva44 citations
  37. SENSEI-LIF at SemEval-2016 Task 4: Polarity embedding fusion for robust sentiment analysis ↗Mickael Rouvier, Benoit Favre42 citations
  38. AUEB-ABSA at SemEval-2016 Task 5: Ensembles of Classifiers and Embeddings for Aspect Based Sentiment Analysis ↗Dionysios Xenos, Panagiotis Theodorakakos, John Pavlopoulos et al.38 citations
  39. CU-GWU Perspective at SemEval-2016 Task 6: Ideological Stance Detection in Informal Text ↗Heba Elfardy, Mona Diab38 citations
  40. GTI at SemEval-2016 Task 5: SVM and CRF for Aspect Detection and Unsupervised Aspect-Based Sentiment Analysis ↗Tamara Álvarez-López, Jonathan Juncal-Martínez, Milagros Fernández-Gavilanes et al.38 citations
  41. UNIMELB at SemEval-2016 Tasks 4A and 4B: An Ensemble of Neural Networks and a Word2Vec Based Model for Sentiment Classification ↗Steven Xu, HuiZhi Liang, Timothy Baldwin37 citations
  42. SV000gg at SemEval-2016 Task 11: Heavy Gauge Complex Word Identification with System Voting ↗Gustavo Paetzold, Lucia Specia35 citations
  43. IUCL at SemEval-2016 Task 6: An Ensemble Model for Stance Detection in Twitter ↗Can Liu, Wen Li, Bradford Demarest et al.34 citations
  44. SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering ↗Mitra Mohtarami, Yonatan Belinkov, Wei-Ning Hsu et al.32 citations
  45. CDE-IIITH at SemEval-2016 Task 12: Extraction of Temporal Information from Clinical documents using Machine Learning techniques ↗Veera Raghavendra Chikka29 citations
  46. LTG at SemEval-2016 Task 11: Complex Word Identification with Classifier Ensembles ↗Shervin Malmasi, Mark Dras, Marcos Zampieri29 citations
  47. ltl.uni-due at SemEval-2016 Task 6: Stance Detection in Social Media Using Stacked Classifiers ↗Michael Wojatzki, Torsten Zesch29 citations
  48. NileTMRG at SemEval-2016 Task 5: Deep Convolutional Neural Networks for Aspect Category and Sentiment Extraction ↗Talaat Khalil, Samhaa R. El-Beltagy28 citations
  49. UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement ↗Hua He, John Wieting, Kevin Gimpel et al.28 citations
  50. Tohoku at SemEval-2016 Task 6: Feature-based Model versus Convolutional Neural Network for Stance Detection ↗Yuki Igarashi, Hiroya Komatsu, Sosuke Kobayashi et al.27 citations
  51. MayoNLP at SemEval-2016 Task 1: Semantic Textual Similarity based on Lexical Semantic Net and Deep Learning Semantic Model ↗Naveed Afzal, Yanshan Wang, Hongfang Liu26 citations
  52. INF-UFRGS-OPINION-MINING at SemEval-2016 Task 6: Automatic Generation of a Training Corpus for Unsupervised Identification of Stance in Tweets ↗Marcelo Dias, Karin Becker25 citations
  53. UFAL at SemEval-2016 Task 5: Recurrent Neural Networks for Sentence Classification ↗Aleš Tamchyna, Kateřina Veselovská25 citations
  54. PLUJAGH at SemEval-2016 Task 11: Simple System for Complex Word Identification ↗Krzysztof Wróbel24 citations
  55. UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports ↗Peng Li, Heng Huang24 citations
  56. iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases ↗Eshrag Refaee, Verena Rieser24 citations
  57. SUper Team at SemEval-2016 Task 3: Building a Feature-Rich System for Community Question Answering ↗Tsvetomila Mihaylova, Pepa Gencheva, Martin Boyanov et al.23 citations
  58. UtahBMI at SemEval-2016 Task 12: Extracting Temporal Information from Clinical Text ↗Abdulrahman Khalifa, Sumithra Velupillai, Stephane Meystre23 citations
  59. ECNU at SemEval 2016 Task 6: Relevant or Not? Supportive or Not? A Two-step Learning System for Automatic Detecting Stance in Tweets ↗Zhihua Zhang, Man Lan22 citations
  60. TALN at SemEval-2016 Task 11: Modelling Complex Words by Contextual, Lexical and Semantic Features ↗Francesco Ronzano, Ahmed Abura'ed, Luis Espinosa-Anke et al.22 citations
  61. UofL at SemEval-2016 Task 4: Multi Domain word2vec for Twitter Sentiment Classification ↗Omar Abdelwahab, Adel Elmaghraby22 citations
  62. NUIG-UNLP at SemEval-2016 Task 13: A Simple Word Embedding-based Approach for Taxonomy Extraction ↗Joel Pocostales21 citations
  63. UWB at SemEval-2016 Task 6: Stance Detection ↗Peter Krejzl, Josef Steinberger21 citations
  64. Finki at SemEval-2016 Task 4: Deep Learning Architecture for Twitter Sentiment Analysis ↗Dario Stojanovski, Gjorgji Strezoski, Gjorgji Madjarov et al.20 citations
  65. LSIS at SemEval-2016 Task 7: Using Web Search Engines for English and Arabic Unsupervised Sentiment Intensity Prediction ↗Amal Htait, Sebastien Fournier, Patrice Bellot20 citations
  66. PMI-cool at SemEval-2016 Task 3: Experiments with PMI and Goodness Polarity Lexicons for Community Question Answering ↗Daniel Balchev, Yasen Kiprov, Ivan Koychev et al.20 citations
  67. ECNU at SemEval-2016 Task 3: Exploring Traditional Method and Deep Learning Method for Question Retrieval and Answer Ranking in Community Question Answering ↗Guoshun Wu, Man Lan19 citations
  68. MacSaar at SemEval-2016 Task 11: Zipfian and Character Features for ComplexWord Identification ↗Marcos Zampieri, Liling Tan, Josef van Genabith19 citations
  69. SemEval-2016 Task 9: Chinese Semantic Dependency Parsing ↗Wanxiang Che, Yanqiu Shao, Ting Liu et al.19 citations
  70. ISTI-CNR at SemEval-2016 Task 4: Quantification on an Ordinal Scale ↗Andrea Esuli18 citations
  71. TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification ↗Georgios Balikas, Massih-Reza Amini18 citations
  72. UniPI at SemEval-2016 Task 4: Convolutional Neural Networks for Sentiment Classification ↗Giuseppe Attardi, Daniele Sartiano18 citations
  73. HMC at SemEval-2016 Task 11: Identifying Complex Words Using Depth-limited Decision Trees ↗Maury Quijada, Julie Medero17 citations
  74. JU_NLP at SemEval-2016 Task 11: Identifying Complex Words in a Sentence ↗Niloy Mukherjee, Braja Gopal Patra, Dipankar Das et al.17 citations
  75. JUNITMZ at SemEval-2016 Task 1: Identifying Semantic Similarity Using Levenshtein Ratio ↗Sandip Sarkar, Dipankar Das, Partha Pakray et al.16 citations
  76. JU_NLP at SemEval-2016 Task 6: Detecting Stance in Tweets using Support Vector Machines ↗Braja Gopal Patra, Dipankar Das, Sivaji Bandyopadhyay16 citations
  77. LIMSI-COT at SemEval-2016 Task 12: Temporal relation identification using a pipeline of classifiers ↗Julien Tourille, Olivier Ferret, Aurélie Névéol et al.16 citations
  78. MTE-NN at SemEval-2016 Task 3: Can Machine Translation Evaluation Help Community Question Answering? ↗Francisco Guzmán, Preslav Nakov, Lluís Màrquez16 citations
  79. USAAR at SemEval-2016 Task 13: Hyponym Endocentricity ↗Liling Tan, Francis Bond, Josef van Genabith16 citations
  80. IDI@NTNU at SemEval-2016 Task 6: Detecting Stance in Tweets Using Shallow Features and GloVe Vectors for Word Representation ↗Henrik Bøhler, Petter Asla, Erwin Marsi et al.15 citations
  81. QU-IR at SemEval 2016 Task 3: Learning to Rank on Arabic Community Question Answering Forums with Word Embedding ↗Rana Malhas, Marwan Torki, Tamer Elsayed15 citations
  82. AI-KU at SemEval-2016 Task 11: Word Embeddings and Substring Features for Complex Word Identification ↗Onur Kuru14 citations
  83. CLaC at SemEval-2016 Task 11: Exploring linguistic and psycho-linguistic Features for Complex Word Identification ↗Elnaz Davoodi, Leila Kosseim14 citations
  84. GUIR at SemEval-2016 task 12: Temporal Information Processing for Clinical Narratives ↗Arman Cohan, Kevin Meurer, Nazli Goharian14 citations
  85. MSejrKu at SemEval-2016 Task 14: Taxonomy Enrichment by Evidence Ranking ↗Michael Schlichtkrull, Héctor Martínez Alonso14 citations
  86. QCRI at SemEval-2016 Task 4: Probabilistic Methods for Binary and Ordinal Quantification ↗Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani14 citations
  87. TGB at SemEval-2016 Task 5: Multi-Lingual Constraint System for Aspect Based Sentiment Analysis ↗Fatih Samet Çetin, Ezgi Yıldırım, Can Özbey et al.14 citations
  88. Tweester at SemEval-2016 Task 4: Sentiment Analysis in Twitter Using Semantic-Affective Model Adaptation ↗Elisavet Palogiannidi, Athanasia Kolovou, Fenia Christopoulou et al.14 citations
  89. UWB at SemEval-2016 Task 11: Exploring Features for Complex Word Identification ↗Michal Konkol14 citations
  90. UWB at SemEval-2016 Task 2: Interpretable Semantic Textual Similarity with Distributional Semantics for Chunks ↗Miloslav Konopík, Ondřej Pražák, David Steinberger et al.14 citations
  91. CNRC at SemEval-2016 Task 1: Experiments in Crosslingual Semantic Textual Similarity ↗Chi-kiu Lo, Cyril Goutte, Michel Simard13 citations
  92. CU-NLP at SemEval-2016 Task 8: AMR Parsing using LSTM-based Recurrent Neural Networks ↗William Foland, James H. Martin13 citations
  93. CoastalCPH at SemEval-2016 Task 11: The importance of designing your Neural Networks right ↗Joachim Bingel, Natalie Schluter, Héctor Martínez Alonso13 citations
  94. ECNU at SemEval-2016 Task 7: An Enhanced Supervised Learning Method for Lexicon Sentiment Intensity Ranking ↗Feixiang Wang, Zhihua Zhang, Man Lan13 citations
  95. UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures ↗Timothy Baldwin, Huizhi Liang, Bahar Salehi et al.13 citations
  96. UofR at SemEval-2016 Task 8: Learning Synchronous Hyperedge Replacement Grammar for AMR Parsing ↗Xiaochang Peng, Daniel Gildea13 citations
  97. bunji at SemEval-2016 Task 5: Neural and Syntactic Models of Entity-Attribute Relationship for Aspect-based Sentiment Analysis ↗Toshihiko Yanase, Kohsuke Yanai, Misa Sato et al.13 citations
  98. AmritaCEN at SemEval-2016 Task 11: Complex Word Identification using Word Embedding ↗Sanjay S.P, Anand Kumar M, Soman K P12 citations
  99. CUFE at SemEval-2016 Task 4: A Gated Recurrent Model for Sentiment Classification ↗Mahmoud Nabil, Amir Atyia, Mohamed Aly12 citations
  100. ICL-HD at SemEval-2016 Task 8: Meaning Representation Parsing - Augmenting AMR Parsing with a Preposition Semantic Role Labeling Neural Network ↗Lauritz Brandt, David Grimm, Mengfei Zhou et al.12 citations

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