SemEval 2014: all accepted papers
- ShrdLite: Semantic Parsing Using a Handmade Grammar ↗Peter Ljunglöf
- SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity ↗Carmen Banea, Di Chen, Rada Mihalcea et al.
- Supervised Methods for Aspect-Based Sentiment Analysis ↗Hussam Hamdan, Patrice Bellot, Frederic Béchet
- Swiss-Chocolate: Sentiment Detection using Sparse SVMs and Part-Of-Speech n-Grams ↗Martin Jaggi, Fatih Uzdilli, Mark Cieliebak
- Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis ↗Alexandre Denis, Samuel Cruz-Lara, Nadia Bellalem et al.
- TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths - an IR Approach ↗Arun Kumar Jayapal, Martin Emms, John Kelleher
- TJP: Identifying the Polarity of Tweets from Contexts ↗Tawunrat Chalothorn, Jeremy Ellman
- TMUNSW: Disorder Concept Recognition and Normalization in Clinical Notes for SemEval-2014 Task 7 ↗Jitendra Jonnagaddala, Manish Kumar, Hong-Jie Dai et al.
- TUGAS: Exploiting unlabelled data for Twitter sentiment analysis ↗Silvio Amir, Miguel B. Almeida, Bruno Martins et al.
- Team Z: Wiktionary as a L2 Writing Assistant ↗Anubhav Gupta
- TeamX: A Sentiment Analyzer with Enhanced Lexicon Mapping and Weighting Scheme for Unbalanced Data ↗Yasuhide Miura, Shigeyuki Sakaki, Keigo Hattori et al.
- The Impact of Z_score on Twitter Sentiment Analysis ↗Hussam Hamdan, Patrice Bellot, Frederic Béchet
- The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic SimilarityJohannes Bjerva, Johan Bos, Rob van der Goot et al.our summary
- Think Positive: Towards Twitter Sentiment Analysis from Scratch ↗Cícero dos Santos
- ThinkMiners: Disorder Recognition using Conditional Random Fields and Distributional Semantics ↗Ankur Parikh, Avinesh PVS, Joy Mustafi et al.
- Turku: Broad-Coverage Semantic Parsing with Rich Features ↗Jenna Kanerva, Juhani Luotolahti, Filip Ginter
- UBham: Lexical Resources and Dependency Parsing for Aspect-Based Sentiment Analysis ↗Viktor Pekar, Naveed Afzal, Bernd Bohnet
- UIO-Lien: Entailment Recognition using Minimal Recursion Semantics ↗Elisabeth Lien, Milen Kouylekov
- UKPDIPF: Lexical Semantic Approach to Sentiment Polarity Prediction in Twitter Data ↗Lucie Flekova, Oliver Ferschke, Iryna Gurevych
- ULisboa: Identification and Classification of Medical Concepts ↗André Leal, Diogo Gonçalves, Bruno Martins et al.
- UMCC_DLSI: A Probabilistic Automata for Aspect Based Sentiment Analysis ↗Yenier Castañeda, Armando Collazo, Elvis Crego et al.
- UMCC_DLSI: Sentiment Analysis in Twitter using Polirity Lexicons and Tweet Similarity ↗Pedro Aniel Sánchez-Mirabal, Yarelis Ruano Torres, Suilen Hernández Alvarado et al.
- UMCC_DLSI_SemSim: Multilingual System for Measuring Semantic Textual Similarity ↗Alexander Chávez, Héctor Dávila, Yoan Gutiérrez et al.
- UNAL-NLP: Combining Soft Cardinality Features for Semantic Textual Similarity, Relatedness and Entailment ↗Sergio Jimenez, George Dueñas, Julia Baquero et al.
- UNAL-NLP: Cross-Lingual Phrase Sense Disambiguation with Syntactic Dependency Trees ↗Emilio Silva-Schlenker, Sergio Jimenez, Julia Baquero
- UNIBA: Combining Distributional Semantic Models and Word Sense Disambiguation for Textual Similarity ↗Pierpaolo Basile, Annalina Caputo, Giovanni Semeraro
- UNITOR: Aspect Based Sentiment Analysis with Structured Learning ↗Giuseppe Castellucci, Simone Filice, Danilo Croce et al.
- UO_UA: Using Latent Semantic Analysis to Build a Domain-Dependent Sentiment Resource ↗Reynier Ortega Bueno, Adrian Fonseca Bruzón, Carlos Muñiz Cuza et al.
- UTH_CCB: A report for SemEval 2014 – Task 7 Analysis of Clinical Text ↗Yaoyun Zhang, Jingqi Wang, Buzhou Tang et al.
- UTU: Disease Mention Recognition and Normalization with CRFs and Vector Space Representations ↗Suwisa Kaewphan, Kai Hakala, Filip Ginter
- UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic ↗Islam Beltagy, Stephen Roller, Gemma Boleda et al.
- UWB: Machine Learning Approach to Aspect-Based Sentiment Analysis ↗Tomáš Brychcín, Michal Konkol, Josef Steinberger
- UniPi: Recognition of Mentions of Disorders in Clinical Text ↗Giuseppe Attardi, Vittoria Cozza, Daniele Sartiano
- University_of_Warwick: SENTIADAPTRON - A Domain Adaptable Sentiment Analyser for Tweets - Meets SemEval ↗Richard Townsend, Aaron Kalair, Ojas Kulkarni et al.
- UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual Entailment ↗Rohit Gupta, Hanna Béchara, Ismail El Maarouf et al.
- V3: Unsupervised Generation of Domain Aspect Terms for Aspect Based Sentiment Analysis ↗Aitor García-Pablos, Montse Cuadros, German Rigau
- XRCE: Hybrid Classification for Aspect-based Sentiment Analysis ↗Caroline Brun, Diana Nicoleta Popa, Claude Roux
- ezDI: A Hybrid CRF and SVM based Model for Detecting and Encoding Disorder Mentions in Clinical Notes ↗Parth Pathak, Pinal Patel, Vishal Panchal et al.
- haLF: Comparing a Pure CDSM Approach with a Standard Machine Learning System for RTE ↗Lorenzo Ferrone, Fabio Massimo Zanzotto
- iTac: Aspect Based Sentiment Analysis using Sentiment Trees and Dictionaries ↗Fritjof Bornebusch, Glaucia Cancino, Melanie Diepenbeck et al.
- tucSage: Grammar Rule Induction for Spoken Dialogue Systems via Probabilistic Candidate Selection ↗Arodami Chorianopoulou, Georgia Athanasopoulou, Elias Iosif et al.
- ÚFAL: Using Hand-crafted Rules in Aspect Based Sentiment Analysis on Parsed Data ↗Kateřina Veselovská, Aleš Tamchyna
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