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For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...
In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...
Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...
Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, ...
Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model that is able to generate descriptive sentences given a sample image. This m ...
Since 2004 the European Commission's Joint Research Centre (JRC) has been analysing the online version of printed media in over twenty languages and has automatically recognised and compiled large amounts of named entities (persons and organisations) and t ...
A popular application in Natural Language Processing (NLP) is the Sentiment Analysis (SA), i.e., the task of extracting contextual polarity from a given text. The social network Twitter provides an immense amount of text (called tweets) generated by users ...
My research focusses on the automatic extraction of canonical references from publications in Classics. Such references are the standard way of citing classical texts and are found in great numbers throughout monographs, journal articles and commentaries. ...
Massive digitization of archival material, coupled with automatic document processing techniques and data visualisation tools offers great opportunities for reconstructing and exploring the past. Unprecedented wealth of historical data (e.g. names of perso ...
Recently, there has been a lot of effort to represent words in continuous vector spaces. Those representations have been shown to capture both semantic and syntactic information about words. However, distributed representations of phrases remain a challeng ...
