


default search action
SemEval@NAACL-HLT 2015: Denver, Colorado, USA
- Daniel M. Cer, David Jurgens, Preslav Nakov, Torsten Zesch:

Proceedings of the 9th International Workshop on Semantic Evaluation, SemEval@NAACL-HLT 2015, Denver, Colorado, USA, June 4-5, 2015. The Association for Computer Linguistics 2015, ISBN 978-1-941643-40-2 - Wei Xu, Chris Callison-Burch, Bill Dolan:

SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT). 1-11 - Guido Zarrella, John C. Henderson, Elizabeth M. Merkhofer, Laura Strickhart:

MITRE: Seven Systems for Semantic Similarity in Tweets. 12-17 - Helena Gómez-Adorno, Darnes Vilariño, David Pinto, Grigori Sidorov:

CICBUAPnlp: Graph-Based Approach for Answer Selection in Community Question Answering Task. 18-22 - Dario Bertero, Pascale Fung:

HLTC-HKUST: A Neural Network Paraphrase Classifier using Translation Metrics, Semantic Roles and Lexical Similarity Features. 23-28 - Ngoc Phuoc An Vo, Simone Magnolini

, Octavian Popescu:
FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter. 29-33 - Jiang Zhao, Man Lan:

ECNU: Leveraging Word Embeddings to Boost Performance for Paraphrase in Twitter. 34-39 - Rob van der Goot, Gertjan van Noord:

ROB: Using Semantic Meaning to Recognize Paraphrases. 40-44 - Mahalakshmi Shanumuga Sundaram, Anand Kumar Madasamy

, Soman Kotti Padannayil:
AMRITA_CEN$@$SemEval-2015: Paraphrase Detection for Twitter using Unsupervised Feature Learning with Recursive Autoencoders. 45-50 - Taneeya Satyapanich, Hang Gao, Tim Finin:

Ebiquity: Paraphrase and Semantic Similarity in Twitter using Skipgrams. 51-55 - Ergun Biçici:

RTM-DCU: Predicting Semantic Similarity with Referential Translation Machines. 56-63 - Asli Eyecioglu

, Bill Keller
:
Twitter Paraphrase Identification with Simple Overlap Features and SVMs. 64-69 - Mladen Karan, Goran Glavas, Jan Snajder, Bojana Dalbelo Basic, Ivan Vulic, Marie-Francine Moens:

TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay. 70-74 - Rafael-Michael Karampatsis:

CDTDS: Predicting Paraphrases in Twitter via Support Vector Regression. 75-79 - Yang Liu, Chengjie Sun, Lei Lin, Xiaolong Wang:

yiGou: A Semantic Text Similarity Computing System Based on SVM. 80-84 - Liling Tan, Carolina Scarton, Lucia Specia, Josef van Genabith:

USAAR-SHEFFIELD: Semantic Textual Similarity with Deep Regression and Machine Translation Evaluation Metrics. 85-89 - Md. Rashadul Hasan Rakib, Aminul Islam, Evangelos E. Milios:

TrWP: Text Relatedness using Word and Phrase Relatedness. 90-95 - Hanna Béchara, Hernani Costa, Shiva Taslimipoor, Rohit Gupta, Constantin Orasan, Gloria Corpas Pastor

, Ruslan Mitkov:
MiniExperts: An SVM Approach for Measuring Semantic Textual Similarity. 96-101 - Ngoc Phuoc An Vo, Simone Magnolini

, Octavian Popescu:
FBK-HLT: A New Framework for Semantic Textual Similarity. 102-106 - Sakethram Karumuri, Viswanadh Kumar Reddy Vuggumudi, Sai Charan Raj Chitirala:

UMDuluth-BlueTeam: SVCSTS - A Multilingual and Chunk Level Semantic Similarity System. 107-110 - Nataliia Plotnikova, Gabriella Lapesa, Thomas Proisl, Stefan Evert:

SemantiKLUE: Semantic Textual Similarity with Maximum Weight Matching. 111-116 - Jiang Zhao, Man Lan, Junfeng Tian:

ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation. 117-122 - Hamed Hassanzadeh

, Tudor Groza, Anthony N. Nguyen, Jane Hunter:
UQeResearch: Semantic Textual Similarity Quantification. 123-127 - Naoko Miura, Tomohiro Takagi:

WSL: Sentence Similarity Using Semantic Distance Between Words. 128-131 - Davide Buscaldi, Jorge García Flores, Iván V. Meza, Isaac Rodriguez:

SOPA: Random Forests Regression for the Semantic Textual Similarity task. 132-137 - Gábor Recski

, Judit Ács:
MathLingBudapest: Concept Networks for Semantic Similarity. 138-142 - Piyush Arora, Chris Hokamp, Jennifer Foster, Gareth J. F. Jones:

DCU: Using Distributional Semantics and Domain Adaptation for the Semantic Textual Similarity SemEval-2015 Task 2. 143-147 - Md. Arafat Sultan, Steven Bethard, Tamara Sumner:

DLS$@$CU: Sentence Similarity from Word Alignment and Semantic Vector Composition. 148-153 - Basma Hassan

, Samir E. AbdelRahman, Reem Bahgat:
FCICU: The Integration between Sense-Based Kernel and Surface-Based Methods to Measure Semantic Textual Similarity. 154-158 - Evan Jaffe, Lifeng Jin, David King, Marten van Schijndel

:
AZMAT: Sentence Similarity Using Associative Matrices. 159-163 - Rajendra Banjade, Nobal Bikram Niraula, Nabin Maharjan, Vasile Rus, Dan Stefanescu, Mihai C. Lintean, Dipesh Gautam:

NeRoSim: A System for Measuring and Interpreting Semantic Textual Similarity. 164-171 - Lushan Han, Justin Martineau, Doreen Cheng, Christopher Thomas:

Samsung: Align-and-Differentiate Approach to Semantic Textual Similarity. 172-177 - Eneko Agirre, Aitor Gonzalez-Agirre, Iñigo Lopez-Gazpio, Montse Maritxalar

, German Rigau
, Larraitz Uria
:
UBC: Cubes for English Semantic Textual Similarity and Supervised Approaches for Interpretable STS. 178-183 - Ana Alves

, David Simões, Hugo Gonçalo Oliveira, Adriana Ferrugento:
ASAP-II: From the Alignment of Phrases to Textual Similarity. 184-189 - Tu Thanh Vu, Quan Hung Tran, Son Bao Pham:

TATO: Leveraging on Multiple Strategies for Semantic Textual Similarity. 190-195 - Yongshuai Hou, Cong Tan, Xiaolong Wang, Yaoyun Zhang, Jun Xu, Qingcai Chen:

HITSZ-ICRC: Exploiting Classification Approach for Answer Selection in Community Question Answering. 196-202 - Massimo Nicosia, Simone Filice, Alberto Barrón-Cedeño, Iman Saleh, Hamdy Mubarak, Wei Gao, Preslav Nakov, Giovanni Da San Martino, Alessandro Moschitti, Kareem Darwish, Lluís Màrquez, Shafiq R. Joty, Walid Magdy:

QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English. 203-209 - Xiaoqiang Zhou, Baotian Hu, Jiaxin Lin, Yang Xiang, Xiaolong Wang:

ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge. 210-214 - Quan Hung Tran, Vu D. Tran

, Tu Vu, Minh Nguyen, Son Bao Pham:
JAIST: Combining multiple features for Answer Selection in Community Question Answering. 215-219 - Amin Heydari Alashty, Saeed Rahmani, Meysam Roostaee, Seyed Mostafa Fakhrahmad

:
Shiraz: A Proposed List Wise Approach to Answer Validation. 220-225 - Reham Mohamed, Maha Ragab, Heba Abdelnasser

, Nagwa M. El-Makky, Marwan Torki:
Al-Bayan: A Knowledge-based System for Arabic Answer Selection. 226-230 - Ngoc Phuoc An Vo, Simone Magnolini

, Octavian Popescu:
FBK-HLT: An Application of Semantic Textual Similarity for Answer Selection in Community Question Answering. 231-235 - Liang Yi, Jianxiang Wang, Man Lan:

ECNU: Using Multiple Sources of CQA-based Information for Answers Selection and YES/NO Response Inference. 236-241 - Ivan Zamanov, Marina Kraeva, Nelly Hateva, Ivana Yovcheva, Ivelina Nikolova, Galia Angelova:

Voltron: A Hybrid System For Answer Validation Based On Lexical And Distance Features. 242-246 - Björn Rudzewitz, Ramon Ziai:

CoMiC: Adapting a Short Answer Assessment System for Answer Selection. 247-251 - Eneko Agirre, Carmen Banea, Claire Cardie, Daniel M. Cer, Mona T. Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Iñigo Lopez-Gazpio, Montse Maritxalar

, Rada Mihalcea, German Rigau
, Larraitz Uria
, Janyce Wiebe:
SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability. 252-263 - Christian Hänig

, Robert Remus, Xose de la Puente:
ExB Themis: Extensive Feature Extraction from Word Alignments for Semantic Textual Similarity. 264-268 - Preslav Nakov, Lluís Màrquez, Walid Magdy, Alessandro Moschitti, James R. Glass, Bilal Randeree:

SemEval-2015 Task 3: Answer Selection in Community Question Answering. 269-281 - Yonatan Belinkov, Mitra Mohtarami, Scott Cyphers, James R. Glass:

VectorSLU: A Continuous Word Vector Approach to Answer Selection in Community Question Answering Systems. 282-287 - Andrea Moro, Roberto Navigli:

SemEval-2015 Task 13: Multilingual All-Words Sense Disambiguation and Entity Linking. 288-297 - Marianna Apidianaki

, Li Gong:
LIMSI: Translations as Source of Indirect Supervision for Multilingual All-Words Sense Disambiguation and Entity Linking. 298-302 - Noémie Elhadad, Sameer Pradhan, Sharon Lipsky Gorman, Suresh Manandhar, Wendy W. Chapman, Guergana K. Savova:

SemEval-2015 Task 14: Analysis of Clinical Text. 303-310 - Jun Xu, Yaoyun Zhang, Jingqi Wang, Yonghui Wu, Min Jiang, Ergin Soysal, Hua Xu:

UTH-CCB: The Participation of the SemEval 2015 Challenge - Task 14. 311-314 - Vít Baisa, Jane Bradbury, Silvie Cinková, Ismaïl El Maarouf, Adam Kilgarriff, Octavian Popescu:

SemEval-2015 Task 15: A CPA dictionary-entry-building task. 315-324 - Yukun Feng, Qiao Deng, Dong Yu:

BLCUNLP: Corpus Pattern Analysis for Verbs Based on Dependency Chain. 325-328 - Rocco Tripodi, Marcello Pelillo:

WSD-games: a Game-Theoretic Algorithm for Unsupervised Word Sense Disambiguation. 329-334 - Dirk Weissenborn, Feiyu Xu, Hans Uszkoreit:

DFKI: Multi-objective Optimization for the Joint Disambiguation of Entities and Nouns & Deep Verb Sense Disambiguation. 335-339 - Eniafe Festus Ayetiran, Guido Boella:

EBL-Hope: Multilingual Word Sense Disambiguation Using a Hybrid Knowledge-Based Technique. 340-344 - Marten Postma, Rubén Izquierdo, Piek Vossen:

VUA-background : When to Use Background Information to Perform Word Sense Disambiguation. 345-349 - Petr Fanta, Roman Sudarikov, Ondrej Bojar

:
TeamUFAL: WSD+EL as Document Retrieval. 350-354 - Pablo Ruiz, Thierry Poibeau:

EL92: Entity Linking Combining Open Source Annotators via Weighted Voting. 355-359 - Pierpaolo Basile, Annalina Caputo, Giovanni Semeraro:

UNIBA: Combining Distributional Semantic Models and Sense Distribution for Multilingual All-Words Sense Disambiguation and Entity Linking. 360-364 - Steve L. Manion:

SUDOKU: Treating Word Sense Disambiguation & Entitiy Linking as a Deterministic Problem - via an Unsupervised & Iterative Approach. 365-369 - Nghia Huynh, Quoc Ho:

TeamHCMUS: Analysis of Clinical Text. 370-374 - Kai Hakala:

UTU: Adapting Biomedical Event Extraction System to Disorder Attribute Detection. 375-379 - Maryna Chernyshevich, Vadim Stankevitch:

IHS-RD-Belarus: Identification and Normalization of Disorder Concepts in Clinical Notes. 380-384 - Omid Ghiasvand, Rohit J. Kate:

UWM: A Simple Baseline Method for Identifying Attributes of Disease and Disorder Mentions in Clinical Text. 385-388 - Goran Glavas:

TAKELAB: Medical Information Extraction and Linking with MINERAL. 389-393 - Jitendra Jonnagaddala

, Siaw-Teng Liaw, Pradeep Kumar Ray
, Manish Kumar, Hong-Jie Dai:
TMUNSW: Identification of Disorders and Normalization to SNOMED-CT Terminology in Unstructured Clinical Notes. 394-398 - Kristina Doing-Harris, Sean Igo, Jianlin Shi, John F. Hurdle:

UtahPOET: Disorder Mention Identification and Context Slot Filling with Cognitive Inspiration. 399-405 - André Leal, Bruno Martins, Francisco M. Couto:

ULisboa: Recognition and Normalization of Medical Concepts. 406-411 - Parth Pathak, Pinal Patel, Vishal Panchal, Sagar Soni, Kinjal Dani, Amrish Patel, Narayan Choudhary:

ezDI: A Supervised NLP System for Clinical Narrative Analysis. 412-416 - James Gung, John David Osborne, Steven Bethard:

CUAB: Supervised Learning of Disorders and their Attributes using Relations. 417-421 - Sérgio Matos, José Sequeira, José Luís Oliveira:

BioinformaticsUA: Machine Learning and Rule-Based Recognition of Disorders and Clinical Attributes from Patient Notes. 422-426 - Asma Ben Abacha, Aikaterini Karanasiou, Yassine Mrabet, Júlio Cesar dos Reis:

LIST-LUX: Disorder Identification from Clinical Texts. 427-432 - Chad Mills, Gina-Anne Levow:

CMILLS: Adapting Semantic Role Labeling Features to Dependency Parsing. 433-437 - Ted Pedersen:

Duluth: Word Sense Discrimination in the Service of Lexicography. 438-442 - Irene Russo, Tommaso Caselli, Carlo Strapparava:

SemEval-2015 Task 9: CLIPEval Implicit Polarity of Events. 443-450 - Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M. Mohammad, Alan Ritter, Veselin Stoyanov:

SemEval-2015 Task 10: Sentiment Analysis in Twitter. 451-463 - Aliaksei Severyn, Alessandro Moschitti:

UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification. 464-469 - Aniruddha Ghosh, Guofu Li, Tony Veale, Paolo Rosso, Ekaterina Shutova, John A. Barnden, Antonio Reyes:

SemEval-2015 Task 11: Sentiment Analysis of Figurative Language in Twitter. 470-478 - Canberk Özdemir, Sabine Bergler:

CLaC-SentiPipe: SemEval2015 Subtasks 10 B, E, and Task 11. 479-485 - Maria Pontiki

, Dimitris Galanis
, Haris Papageorgiou, Suresh Manandhar, Ion Androutsopoulos:
SemEval-2015 Task 12: Aspect Based Sentiment Analysis. 486-495 - Zhiqiang Toh, Jian Su:

NLANGP: Supervised Machine Learning System for Aspect Category Classification and Opinion Target Extraction. 496-501 - Mauro Dragoni:

SHELLFBK: An Information Retrieval-based System For Multi-Domain Sentiment Analysis. 502-509 - Abeed Sarker

, Azadeh Nikfarjam, Davy Weissenbacher, Graciela Gonzalez-Hernandez:
DIEGOLab: An Approach for Message-level Sentiment Classification in Twitter. 510-514 - Li Dong, Furu Wei, Yichun Yin, Ming Zhou, Ke Xu:

Splusplus: A Feature-Rich Two-stage Classifier for Sentiment Analysis of Tweets. 515-519 - Ayushi Dalmia, Manish Gupta, Vasudeva Varma:

IIIT-H at SemEval 2015: Twitter Sentiment Analysis - The Good, the Bad and the Neutral! 520-526 - Sebastian Ebert, Ngoc Thang Vu, Hinrich Schütze:

CIS-positive: A Combination of Convolutional Neural Networks and Support Vector Machines for Sentiment Analysis in Twitter. 527-532 - Milagros Fernández Gavilanes, Tamara Álvarez-López, Jonathan Juncal-Martínez, Enrique Costa-Montenegro, Francisco Javier González-Castaño:

GTI: An Unsupervised Approach for Sentiment Analysis in Twitter. 533-538 - Héctor Cerezo-Costas, Diego Celix-Salgado:

Gradiant-Analytics: Training Polarity Shifters with CRFs for Message Level Polarity Detection. 539-544 - Peijia Li, Weiqun Xu, Chenglong Ma, Jia Sun, Yonghong Yan:

IOA: Improving SVM Based Sentiment Classification Through Post Processing. 545-550 - Huizhi Liang, Richard Fothergill, Timothy Baldwin:

RoseMerry: A Baseline Message-level Sentiment Classification System. 551-555 - Esteban Castillo, Ofelia Cervantes, Darnes Vilariño, David Báez, J. Alfredo Sánchez:

UDLAP: Sentiment Analysis Using a Graph-Based Representation. 556-560 - Zhihua Zhang, GuoShun Wu, Man Lan:

ECNU: Multi-level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features. 561-567 - Hussam Hamdan, Patrice Bellot, Frédéric Béchet:

Lsislif: Feature Extraction and Label Weighting for Sentiment Analysis in Twitter. 568-573 - Mayte Giménez, Ferran Pla, Lluís-F. Hurtado:

ELiRF: A SVM Approach for SA tasks in Twitter at SemEval-2015. 574-581 - Matthias Hagen, Martin Potthast, Michel Büchner, Benno Stein:

Webis: An Ensemble for Twitter Sentiment Detection. 582-589 - Satarupa Guha, Aditya Joshi, Vasudeva Varma:

Sentibase: Sentiment Analysis in Twitter on a Budget. 590-594 - Pierpaolo Basile, Nicole Novielli:

UNIBA: Sentiment Analysis of English Tweets Combining Micro-blogging, Lexicon and Semantic Features. 595-600 - Ayush Kumar, Vamsi Krishna, Asif Ekbal:

IITPSemEval: Sentiment Discovery from 140 Characters. 601-607 - Fatih Uzdilli, Martin Jaggi, Dominic Egger, Pascal Julmy, Leon Derczynski, Mark Cieliebak

:
Swiss-Chocolate: Combining Flipout Regularization and Random Forests with Artificially Built Subsystems to Boost Text-Classification for Sentiment. 608-612 - Silvio Amir, Wang Ling, Ramón Fernandez Astudillo, Bruno Martins, Mário J. Silva, Isabel Trancoso:

INESC-ID: A Regression Model for Large Scale Twitter Sentiment Lexicon Induction. 613-618 - Nataliia Plotnikova, Micha Kohl, Kevin Volkert, Stefan Evert, Andreas Lerner, Natalie Dykes, Heiko Ermer:

KLUEless: Polarity Classification and Association. 619-625 - Ruth Talbot, Chloe Acheampong, Richard Wicentowski:

SWASH: A Naive Bayes Classifier for Tweet Sentiment Identification. 626-630 - Richard Wicentowski:

SWATCS65: Sentiment Classification Using an Ensemble of Class Projects. 631-635 - Yousef Alhessi, Richard Wicentowski:

SWATAC: A Sentiment Analyzer using One-Vs-Rest Logistic Regression. 636-639 - William Boag, Peter Potash, Anna Rumshisky:

TwitterHawk: A Feature Bucket Based Approach to Sentiment Analysis. 640-646 - Prerna Chikersal, Soujanya Poria, Erik Cambria

:
SeNTU: Sentiment Analysis of Tweets by Combining a Rule-based Classifier with Supervised Learning. 647-651 - Ramón Fernandez Astudillo, Silvio Amir, Wang Ling, Bruno Martins, Mário J. Silva, Isabel Trancoso:

INESC-ID: Sentiment Analysis without Hand-Coded Features or Linguistic Resources using Embedding Subspaces. 652-656 - Richard Townsend, Adam Tsakalidis, Yiwei Zhou, Bo Wang, Maria Liakata, Arkaitz Zubiaga, Alexandra I. Cristea

, Rob Procter:
WarwickDCS: From Phrase-Based to Target-Specific Sentiment Recognition. 657-663 - Xu Han, Binyang Li, Jing Ma

, Yuxiao Zhang, Gaoyan Ou, Tengjiao Wang, Kam-Fai Wong:
UIR-PKU: Twitter-OpinMiner System for Sentiment Analysis in Twitter at SemEval 2015. 664-668 - Riley Collins, Daniel May, Noah Weinthal, Richard Wicentowski:

SWAT-CMW: Classification of Twitter Emotional Polarity using a Multiple-Classifier Decision Schema and Enhanced Emotion Tagging. 669-672 - Hongzhi Xu, Enrico Santus, Anna Laszlo, Chu-Ren Huang

:
LLT-PolyU: Identifying Sentiment Intensity in Ironic Tweets. 673-678 - Hoang Long Nguyen, Duc Nguyen Trung, Dosam Hwang, Jason J. Jung:

KELabTeam: A Statistical Approach on Figurative Language Sentiment Analysis in Twitter. 679-683 - Cynthia Van Hee

, Els Lefever, Véronique Hoste:
LT3: Sentiment Analysis of Figurative Tweets: piece of cake #NotReally. 684-688 - Parth Gupta, Jon Ander Gómez

:
PRHLT: Combination of Deep Autoencoders with Classification and Regression Techniques for SemEval-2015 Task 11. 689-693 - Delia Irazú Hernández Farías, Emilio Sulis, Viviana Patti, Giancarlo Ruffo, Cristina Bosco:

ValenTo: Sentiment Analysis of Figurative Language Tweets with Irony and Sarcasm. 694-698 - Sarah McGillion, Héctor Martínez Alonso, Barbara Plank:

CPH: Sentiment analysis of Figurative Language on Twitter #easypeasy #not. 699-703 - Francesco Barbieri, Francesco Ronzano, Horacio Saggion:

UPF-taln: SemEval 2015 Tasks 10 and 11. Sentiment Analysis of Literal and Figurative Language in Twitter. 704-708 - Maria Karanasou, Christos Doulkeridis, Maria Halkidi:

DsUniPi: An SVM-based Approach for Sentiment Analysis of Figurative Language on Twitter. 709-713 - Aitor García-Pablos, Montse Cuadros, German Rigau

:
V3: Unsupervised Aspect Based Sentiment Analysis for SemEval2015 Task 12. 714-718 - Orphée De Clercq, Marjan Van de Kauter, Els Lefever, Véronique Hoste:

LT3: Applying Hybrid Terminology Extraction to Aspect-Based Sentiment Analysis. 719-724 - Anderson Uilian Kauer, Viviane Pereira Moreira:

UFRGS: Identifying Categories and Targets in Customer Reviews. 725-729 - Salud M. Jiménez-Zafra, Eugenio Martínez-Cámara, María Teresa Martín-Valdivia, Luis Alfonso Ureña López:

SINAI: Syntactic Approach for Aspect-Based Sentiment Analysis. 730-735 - Zhihua Zhang, Man Lan:

ECNU: Extracting Effective Features from Multiple Sequential Sentences for Target-dependent Sentiment Analysis in Reviews. 736-741 - Ravikanth Repaka, Ranga Reddy Pallelra, Akshay Reddy Koppula, Venkata Subhash Movva:

UMDuluth-CS8761-12: A Novel Machine Learning Approach for Aspect Based Sentiment Analysis. 742-747 - Iñaki San Vicente, Xabier Saralegi, Rodrigo Agerri

:
EliXa: A Modular and Flexible ABSA Platform. 748-752 - Hussam Hamdan, Patrice Bellot

, Frédéric Béchet:
Lsislif: CRF and Logistic Regression for Opinion Target Extraction and Sentiment Polarity Analysis. 753-758 - Satarupa Guha, Aditya Joshi, Vasudeva Varma:

SIEL: Aspect Based Sentiment Analysis in Reviews. 759-766 - José Saias:

Sentiue: Target and Aspect based Sentiment Analysis in SemEval-2015 Task 12. 767-771 - Zhifei Zhang, Jian-Yun Nie, Hongling Wang:

TJUdeM: A Combination Classifier for Aspect Category Detection and Sentiment Polarity Classification. 772-777 - Anne-Lyse Minard, Manuela Speranza, Eneko Agirre, Itziar Aldabe

, Marieke van Erp, Bernardo Magnini, German Rigau
, Ruben Urizar
:
SemEval-2015 Task 4: TimeLine: Cross-Document Event Ordering. 778-786 - Tommaso Caselli, Antske Fokkens, Roser Morante, Piek Vossen:

SPINOZA_VU: An NLP Pipeline for Cross Document TimeLines. 787-791 - Hector Llorens, Nathanael Chambers, Naushad UzZaman, Nasrin Mostafazadeh, James F. Allen, James Pustejovsky:

SemEval-2015 Task 5: QA TempEval - Evaluating Temporal Information Understanding with Question Answering. 792-800 - Paramita Mirza

, Anne-Lyse Minard:
HLT-FBK: a Complete Temporal Processing System for QA TempEval. 801-805 - Steven Bethard, Leon Derczynski, Guergana Savova, James Pustejovsky, Marc Verhagen:

SemEval-2015 Task 6: Clinical TempEval. 806-814 - Sumithra Velupillai, Danielle L. Mowery, Samir E. AbdelRahman, Lee M. Christensen, Wendy W. Chapman:

BluLab: Temporal Information Extraction for the 2015 Clinical TempEval Challenge. 815-819 - Bilel Moulahi, Jannik Strötgen

, Michael Gertz, Lynda Tamine:
HeidelToul: A Baseline Approach for Cross-document Event Ordering. 825-829 - Yongshuai Hou, Cong Tan, Qingcai Chen, Xiaolong Wang:

HITSZ-ICRC: An Integration Approach for QA TempEval Challenge. 830-834 - Hegler Tissot, Genevieve Gorrell

, Angus Roberts, Leon Derczynski, Marcos Didonet Del Fabro:
UFPRSheffield: Contrasting Rule-based and Support Vector Machine Approaches to Time Expression Identification in Clinical TempEval. 835-839 - Haritz Salaberri, Iker Salaberri, Olatz Arregi

, Beñat Zapirain:
IXAGroupEHUDiac: A Multiple Approach System towards the Diachronic Evaluation of Texts. 840-845 - Liling Tan, Noam Ordan:

USAAR-CHRONOS: Crawling the Web for Temporal Annotations. 846-850 - Marcos Zampieri, Alina Maria Ciobanu, Vlad Niculae, Liviu P. Dinu:

AMBRA: A Ranking Approach to Temporal Text Classification. 851-855 - Haritz Salaberri, Olatz Arregi

, Beñat Zapirain:
IXAGroupEHUSpaceEval: (X-Space) A WordNet-based approach towards the Automatic Recognition of Spatial Information following the ISO-Space Annotation Scheme. 856-861 - Jennifer D'Souza, Vincent Ng:

UTD: Ensemble-Based Spatial Relation Extraction. 862-869 - Octavian Popescu, Carlo Strapparava:

SemEval 2015, Task 7: Diachronic Text Evaluation. 870-878 - Terrence Szymanski, Gerard Lynch:

UCD : Diachronic Text Classification with Character, Word, and Syntactic N-grams. 879-883 - James Pustejovsky, Parisa Kordjamshidi, Marie-Francine Moens, Aaron Levine, Seth Dworman, Zachary Yocum:

SemEval-2015 Task 8: SpaceEval. 884-894 - Eric Nichols, Fadi Botros:

SpRL-CWW: Spatial Relation Classification with Independent Multi-class Models. 895-901 - Georgeta Bordea, Paul Buitelaar, Stefano Faralli

, Roberto Navigli:
SemEval-2015 Task 17: Taxonomy Extraction Evaluation (TExEval). 902-910 - Gregory Grefenstette:

INRIASAC: Simple Hypernym Extraction Methods. 911-914 - Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Silvie Cinková, Dan Flickinger, Jan Hajic, Zdenka Uresová:

SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing. 915-926 - Yantao Du, Fan Zhang, Xun Zhang, Weiwei Sun, Xiaojun Wan:

Peking: Building Semantic Dependency Graphs with a Hybrid Parser. 927-931 - Liling Tan, Rohit Gupta, Josef van Genabith:

USAAR-WLV: Hypernym Generation with Deep Neural Nets. 932-937 - Bamfa Ceesay, Wen-Juan Hou:

NTNU: An Unsupervised Knowledge Approach for Taxonomy Extraction. 938-943 - Els Lefever:

LT3: A Multi-modular Approach to Automatic Taxonomy Construction. 944-948 - Luis Espinosa Anke, Horacio Saggion, Francesco Ronzano:

TALN-UPF: Taxonomy Learning Exploiting CRF-Based Hypernym Extraction on Encyclopedic Definitions. 949-954 - Guillaume Cleuziou, Davide Buscaldi, Gaël Dias, Vincent Levorato, Christine Largeron:

QASSIT: A Pretopological Framework for the Automatic Construction of Lexical Taxonomies from Raw Texts. 955-959 - Guntis Barzdins, Peteris Paikens, Didzis Gosko:

Riga: from FrameNet to Semantic Frames with C6.0 Rules. 960-964 - Jenna Kanerva, Juhani Luotolahti, Filip Ginter:

Turku: Semantic Dependency Parsing as a Sequence Classification. 965-969 - Mariana S. C. Almeida, André F. T. Martins:

Lisbon: Evaluating TurboSemanticParser on Multiple Languages and Out-of-Domain Data. 970-973

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.


Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID














