IHS-RD-Belarus at SemEval-2016 Task 5: Detecting Sentiment Polarity Using the Heatmap of Sentence
نویسنده
چکیده
This paper describes the system submitted by IHS-RD-Belarus team for the sentiment detection polarity subtask on Aspect Based Sentiment Analysis task at the SemEval 2016 workshop on semantic evaluation. We developed a system based on artificial neural network to detect the sentiment polarity of opinions. Evaluation on the test data set showed that our system achieved the F-score of 0.83 for restaurants domain (rank 4 out of 28 submissions) and F-score of 0.78 for laptops domain (rank 4 out of 21 submissions).
منابع مشابه
IHS-RD-Belarus at SemEval-2016 Task 1: Multistage Approach for Measuring Semantic Similarity
This paper describes the system for rating the degree of semantic equivalence between two text snippets developed by IHS-RD-Belarus for the SemEval 2016 STS shared task (Task 1). To predict the human ratings of text similarity we use a support vector regression model with multiple features representing similarity and difference scores calculated for each
متن کاملIHS R&D Belarus: Cross-domain extraction of product features using CRF
This paper describes the aspect extraction system submitted by IHS R&D Belarus team at the SemEval-2014 shared task related to Aspect-Based Sentiment Analysis. Our system is based on IHS Goldfire linguistic processor and uses a rich set of lexical, syntactic and statistical features in CRF model. We participated in two domain-specific tasks – restaurants and laptops – with the same system train...
متن کاملECNU at SemEval-2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect-Based Sentiment Analysis in Reviews
This paper describes our systems submitted to the Sentence-level and Text-level AspectBased Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection phase and Sentiment Polarity Classification phase. We participated in the second phase of both subtasks in laptop and restaurant domains, which focuses on the sentiment analysis based on ...
متن کاملIHS-RD-Belarus: Identification and Normalization of Disorder Concepts in Clinical Notes
This paper describes clinical disorder recognition and encoding system submitted by IHS R&D Belarus team at the SemEval-2015 shared task related to analysis of clinical texts. Our system is based on IHS Goldfire Linguistic Processor and uses a rich set of lexical, syntactic and semantic features. The proposed system consists of two components: a CRF-based approach to recognize disorder entities...
متن کاملMayAnd at SemEval-2016 Task 5: Syntactic and word2vec-based approach to aspect-based polarity detection in Russian
This paper describes aspect-based polarity detection system for Russian, used in aspectbased sentiment analysis task (ABSA) of SemEval-2016 (Task 5, subtask 1, slot 3). The system consists of two independent classifiers: for opinion target expressions and for implicit opinion target mentions. We introduce a set of standard unigram features together with more sophisticated ones: based on sentenc...
متن کامل