2018
EMNLP
EMNLP 2018
MindLab Neural Network Approach at BioASQ 6B
Abstract
AbstractBiomedical Question Answering is concerned with the development of methods and systems that automatically find answers to natural language posed questions. In this work, we describe the system used in the BioASQ Challenge task 6b for document retrieval and snippet retrieval (with particular emphasis in this subtask). The proposed model makes use of semantic similarity patterns that are evaluated and measured by a convolutional neural network architecture. Subsequently, the snippet ranking performance is improved with a pseudo-relevance feedback approach in a later step. Based on the preliminary results, we reached the second position in snippet retrieval sub-task.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Trend Setter
— Information Retrieval
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Hot Topic Early Bird
— document retrieval
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Topics
Deep Learning > Architectures > Neural Networks
Natural Language Processing > Applications > Information Retrieval
Natural Language Processing > Applications > Question Answering
Machine Learning > Application Areas > Information Retrieval
Deep Learning > Architectures > Convolutional Neural Networks