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MOTIVATION Scholarly biomedical publications report on the findings of a research investigation. Scientists use a well-established discourse structure to relate their work to the state of the art, express their own motivation and hypotheses and report on their methods, results and conclusions. In previous work, we have proposed ways to explicitly annotate(More)
Many practical tasks require accessing specific types of information in scientific literature; e.g. information about the objective , methods, results or conclusions of the study in question. Several schemes have been developed to characterize such information in full journal papers. Yet many tasks focus on abstracts instead. We take three schemes of(More)
We describe our approach for creating a system able to detect emotions in suicide notes. Motivated by the sparse and imbalanced data as well as the complex annotation scheme, we have considered three hybrid approaches for distinguishing between the different categories. Each of the three approaches combines machine learning with manually derived rules,(More)
This paper addresses the problem of determining the best answer in Community-based Question Answering websites by focussing on the content. Previous research on this topic relies on the exploitation of community feedback on the answers, which involves rating of either users (e.g., reputation) or answers (e.g. scores manually assigned to answers). We propose(More)
We present and evaluate several hybrid systems for sentiment identification for Twit-ter, both at the phrase and document (tweet) level. Our approach has been to use a novel combination of lexica, traditional NLP and deep learning features. We also analyse techniques based on syntactic parsing and token-based association to handle topic specific sentiment(More)
In this paper, we describe work in progress for the development of a named entity recognizer for Greek. The system aims at information extraction applications where large scale text processing is needed. Speed of analysis, system robustness, and results accuracy have been the basic guidelines for the system's design. Our system is an automated pipeline of(More)
Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical(More)
The spread of false rumours during emergencies can jeopardise the well-being of citizens as they are monitoring the stream of news from social media to stay abreast of the latest updates. In this paper, we describe the methodology we have developed within the PHEME project for the collection and sampling of conversational threads, as well as the tool we(More)
We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses,(More)