Search Results for author:
Found 7 papers, 2 papers with code
Zero-Shot Cross-Lingual Opinion Target Extraction
In this work, we address the lack of available annotated data for specific languages by proposing a zero-shot cross-lingual approach for the extraction of opinion target expressions.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Evaluating Architectural Choices for Deep Learning Approaches for Question Answering over Knowledge Bases
We address the task of answering simple questions, consisting in predicting the subject and predicate of a triple given a question.
AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data
We present the first multilingual QALD pipeline that induces a model from training data for mapping a natural language question into logical form as probabilistic inference.
Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture
We propose a neural network based system to address the task of Aspect-Based Sentiment Analysis to compete in Task 2 of the ESWC-2016 Challenge on Semantic Sentiment Analysis.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Improving Opinion-Target Extraction with Character-Level Word Embeddings
In this work, we investigate whether character-level models can improve the performance for the identification of opinion target expressions.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Aspect-Based Relational Sentiment Analysis Using a Stacked Neural Network Architecture
We present a novel neural architecture for sentiment analysis as a relation extraction problem that addresses this problem by dividing it into three subtasks: i) identification of aspect and opinion terms, ii) labeling of opinion terms with a sentiment, and iii) extraction of relations between opinion terms and aspect terms.
