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Publication: TIPSTER (2013)

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This paper describes a system for automat- ically measuring the semantic similarity be- tween two texts, which was the aim of the 2013 Semantic Textual Similarity (STS) task (Agirre et …...

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SemEval-2016 Task 2: Interpretable Semantic Textual Similarity

Authors: nan

Publication: TIPSTER (2016)

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The final goal of Interpretable Semantic Tex- tual Similarity (iSTS) is to build systems that explain which are the differences and com- monalities between two sentences. The task adds an …...

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A Multilayer Perceptron based Ensemble Technique for Fine-grained Financial Sentiment Analysis

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractIn this paper, we propose a novel method for combining deep learning and classical feature based models using a Multi-Layer Perceptron (MLP) network for financial sentiment analysis. We develop various …...

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IBA-Sys at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThis paper presents the details of our system IBA-Sys that participated in SemEval Task: Fine-grained sentiment analysis on Financial Microblogs and News. Our system participated in both tracks. For microblogs …...

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IITP at SemEval-2017 Task 5: An Ensemble of Deep Learning and Feature Based Models for Financial Sentiment Analysis

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractIn this paper we propose an ensemble based model which combines state of the art deep learning sentiment analysis algorithms like Convolution Neural Network (CNN) and Long Short Term Memory …...

25194

INF-UFRGS at SemEval-2017 Task 5: A Supervised Identification of Sentiment Score in Tweets and Headlines

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThis paper describes a supervised solution for detecting the polarity scores of tweets or headline news in the financial domain, submitted to the SemEval 2017 Fine-Grained Sentiment Analysis on Financial …...

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