Support Vector Regression

. We propose a novel type of document classification task that quantifies how much a given document (review) appreciates the target object using not binary polarity (good or bad) but …...

We present a new method that compresses sentences by removing words. In a first stage, it generates candidate compressions by re- moving branches from the source sentence’s dependency tree using …...

We present a new method to generate extractive multi-document summaries. The method uses Integer Linear Programming to jointly maximize the importance of the sentences it includes in the summary and …...

This paper describes the two systems for determining the semantic similarity of short texts submitted to the SemEval 2012 Task 6. Most of the research on semantic similarity of textual …...

This paper presents the UNITOR system that participated to the SemEval 2012 Task 6: Se- mantic Textual Similarity (STS). The task is here modeled as a Support Vector (SV) regres- …...

This paper deals with knowledge-based text processing which aims at an intuitive notion of textual similarity. Entities and relations rel- evant for a particular domain are identified and disambiguated by …...

We present a system submitted in the Semantic Textual Similarity (STS) task at the Second Joint Conference on Lexical and Computa- tional Semantics (*SEM 2013). Given two short text fragments, …...

This paper reports our submissions to the Semantic Textual Similarity (STS) task in ∗SEM Shared Task 2013. We submitted three Support Vector Regression (SVR) systems in core task, using 6 …...

This paper describes the system used by the LIPN team in the Semantic Textual Similarity task at *SEM 2013. It uses a support vector re- gression model, combining different text …...

In this paper, we have studied the effect of two important factors influencing text readability in Bangla: the target reader and text properties. Accordingly, at first we have built a …...

This paper describes the system used by the LIPN team in the task 10, Multilin- gual Semantic Textual Similarity, at Sem- Eval 2014, in both the English and Span- ish …...

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 …...

Semantic text similarity (STS) is an essential problem in many Natural Language Pro- cessing tasks, which has drawn a considerable amount of attention by research community in recent years. In …...

We present ExB Themis – a word alignment- based semantic textual similarity system de- veloped for SemEval-2015 Task 2: Semantic Textual Similarity. It combines both string and semantic similarity measures …...

In this paper, we describe the system we built for Task 11 of SemEval2015, which aims at i- dentifying the sentiment intensity of figurative language in tweets. We use various …...

Semantic Textual Similarity measures similar- ity between pair of texts, even though the sim- ilar context is projected using different words. This work attempted to incorporate the con- text space …...

In this paper we describe our system (DT- Sim) submitted at SemEval-2016 Task 1: Se- mantic Textual Similarity (STS Core). We developed Support Vector Regression model with various features including …...

Community Question Answering (CAQ) sys- tems play an important role in people's lives due to the huge knowledge accumulated in them. In order to take full advantage of the huge …...

We present in this paper a system for measur- ing Semantic Text Similarity (STS) in English. We introduce three novel techniques: the use of Types, methods of linking phrases, and …...

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 …...

AbstractThis paper reports team IITPB’s participation in the SemEval 2017 Task 5 on ‘Fine-grained sentiment analysis on financial microblogs and news’. We developed 2 systems for the two tracks. One …...

AbstractThis paper describes our system for fine-grained sentiment scoring of news headlines submitted to SemEval 2017 task 5–subtask 2. Our system uses a feature-light method that consists of a Support …...

AbstractThis paper provides an evaluation of a wide range of advanced sentence-level Quality Estimation models, including Support Vector Regression, Ride Regression, Neural Networks, Gaussian Processes, Bayesian Neural Networks, Deep Kernel …...