Ensuring the safety and efficacy of pharmaceuticals and biotechnology products is one of the top challenges in healthcare today. With drug recalls continuing to make headlines, consumers and other stakeholders across the healthcare ecosystem are demanding more oversight and regulators around the globe are responding to these pressures by increasing their scrutiny and compliance requirements fro...

Opinion and market research companies gather a substantial amount of polls data which can be combined with news headlines, for the corresponding time periods they are collected. These data are analyzed in order to answer specific (predefined) questions related to the situation of each time period. However, when these tasks are fulfilled, the collected data are archived and possibly the majority...

Abstract Existing work generally classifies news headlines as a matter of short text classification. However, due to the strong domain nature and limited length headlines, their classification results are usually determined by several specific keywords, which makes traditional method ineffective. In this paper, we propose new identify keywords in expand features from sentence level word respect...

This paper discusses the problem of incongruent headlines: those which do not accurately represent the information contained in the article with which they occur. We emphasise that this phenomenon should be considered separately from recognised problematic headline types such as clickbait and sensationalism, arguing that existing natural language processing (NLP) methods applied to these relate...

This paper discusses the approach taken by the UWaterloo team to arrive at a solution for the Fine-Grained Sentiment Analysis problem posed by Task 5 of SemEval 2017. The paper describes the document vectorization and sentiment score prediction techniques used, as well as the design and implementation decisions taken while building the system for this task. The system uses text vectorization mo...