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Cognitive language engineering towards robust human-computer interaction

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Mapping Affinities in Academic Organizations

Frédéric Kaplan, Boris Beaude, Dario Rodighiero

Scholarly affinities are one of the most fundamental hidden dynamics that drive scientific development. Some affinities are actual, and consequently can be measured through classical academic metrics such as co-authoring. Other affinities are potential, an ...

2018

Text Similarity in Vector Space Models: A Comparative Study

Kenneth Younge, Omid Shahmirzadi, Adam Lugowski

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to ...

2018

Using Robust Principal Component Analysis to Reduce EEG Intra-Trial Variability

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ping-Keng Jao

Practical brain-computer interfaces need to overcome several challenges, including tolerance to signal variability within- and across sessions. We introduce Robust Principal Component Analysis (RPCA) as a potential approach to tackle intra-trial variabilit ...

2018

Cities, from Information to Interaction

João Vitor Meirelles de Miranda

From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded ...

2018

Social babbling: The emergence of symbolic gestures and words

Aude Billard, Laura Bénédicte Marine Cohen

Language acquisition theories classically distinguish passive language understanding from active language production. However, recent findings show that brain areas such as Broca's region are shared in language understanding and production. Furthermore, th ...

PERGAMON-ELSEVIER SCIENCE LTD2018

Word Sequence Modeling using Deep Learning

Joël Yvon Roland Legrand

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 ...

EPFL2016

Learning Explainable User Sentiment and Preferences for Information Filtering

Nikolaos Pappas

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 ...

EPFL2016

Building Word Embeddings for Solving Natural Language Processing

Rémi Philippe Lebret

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 ...

École Polytechnique Fédérale de Lausanne2016

Word Embeddings for Natural Language Processing

Rémi Philippe Lebret

EPFL2016

JRC-Names: Multilingual Entity Name variants and titles as Linked Data

Maud Ehrmann

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 ...

2016