SEMEVAL 2015
Related Papers
A Comparative Study of Different Sentiment Lexica for Sentiment Analysis of Tweets
We report on interoperability of different sentiment lexica with each other and with the linguistic notions negation and modal- ity for sentiment analysis of tweets in a comprehensive ablation study …...
CDTDS: Predicting Paraphrases in Twitter via Support Vector Regression
In this paper we describe a system that rec- ognizes paraphrases in Twitter for tweets that refer to the same topic. The system partici- pated in Task1 of SEMEVAL-2015 and …...
ECNU: Extracting Effective Features from Multiple Sequential Sentences for Target-dependent Sentiment Analysis in Reviews
This paper describes our systems submitted to the target-dependent sentiment polarity clas- sification subtask in aspect based sentimen- t analysis (ABSA) task (i.e., Task 12) in Se- mEval 2015. To …...
HITSZ-ICRC: An Integration Approach for QA TempEval Challenge
This paper presents the HITSZ-ICRC system designed for the QA TempEval challenge in SemEval-2015. The system used an integra- tion approach to annotate temporal informa- tion by merging temporal annotation …...
INESC-ID: Sentiment Analysis without Hand-Coded Features or Linguistic Resources using Embedding Subspaces
We present the INESC-ID system for the mes- sage polarity classification task of SemEval 2015. The proposed system does not make use of any hand-coded features or linguistic resources. It …...
KLUEless: Polarity Classification and Association
This paper describes the KLUEless system which participated in the SemEval-2015 task on “Sentiment Analysis in Twitter”. This year the updated system based on the developments for the same task …...
NLANGP: Supervised Machine Learning System for Aspect Category Classification and Opinion Target Extraction
This paper describes our system used in the Aspect Based Sentiment Analysis Task 12 of SemEval-2015. Our system is based on two supervised machine learning algorithms: sig- moidal feedforward network …...
SemantiKLUE: Semantic Textual Similarity with Maximum Weight Matching
This paper describes the SemantiKLUE sys- tem (Proisl et al., 2014) used for the SemEval- 2015 shared task on Semantic Textual Simi- larity (STS) for English. The system was de- …...
SemEval-2015 Task 10: Sentiment Analysis in Twitter
In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analy- sis in Twitter. This was the most popular sen- timent analysis shared task to …...
UNIBA: Sentiment Analysis of English Tweets Combining Micro-blogging, Lexicon and Semantic Features
This paper describes the UNIBA team partic- ipation in the Sentiment Analysis in Twitter task (Task 10) at SemEval-2015. We propose a supervised approach relying on keyword, lex- icon and …...
UNITN: Training Deep Convolutional Neural Network for Twitter Sentiment Classification
This paper describes our deep learning system for sentiment analysis of tweets. The main contribution of this work is a process to ini- tialize the parameter weights of the convolu- …...
UQeResearch: Semantic Textual Similarity Quantification
This paper presents an approach for estimat- ing the Semantic Textual Similarity of full English sentences as specified in Shared Task 2 of SemEval-2015. The semantic similarity of sentence pairs …...
UTU: Adapting Biomedical Event Extraction System to Disorder Attribute Detection
In this paper we describe our entry to the Se- mEval 2015 clinical text analysis task. We participated only in the disorder attribute de- tection task 2a. Our main goal …...
Synchronous Double-channel Recurrent Network for Aspect-Opinion Pair Extraction
AbstractOpinion entity extraction is a fundamental task in fine-grained opinion mining. Related studies generally extract aspects and/or opinion expressions without recognizing the relations between them. However, the relations are crucial …...