Concept

Text mining

Related publications (208)

Evaluating Attention Networks for Anaphora Resolution

Andrei Popescu-Belis, Nikolaos Pappas, Lesly Sadiht Miculicich Werlen

In this paper, we evaluate the results of using inter and intra attention mechanisms from two architectures, a Deep Attention Long Short-Term Memory-Network (LSTM-N) (Cheng et al., 2016) and a Decomposable Attention model (Parikh et al., 2016), for anaphor ...

Idiap2017

Kamusi Pre:D – Lexicon-based source-side predisambiguation for MT and other text processing applications

Martin Benjamin

Kamusi has been developing a system to analyze texts on the source side and present users with sense-specified dictionary options. Similarly to spellcheck, the user selects the intended meaning. We then use a multilingual lexical database to bridge to matc ...

ENeL2016

Distribution-Matching Embedding for Visual Domain Adaptation

Mathieu Salzmann

Domain-invariant representations are key to addressing the domain shift problem where the training and test examples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typical ...

2016

Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation

Marina Boia

While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...

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

Combining Content Analytics and Activity Tracking to Identify User Interests and Enable Knowledge Discovery

Denis Gillet, Maria Jesus Rodriguez Triana, Adrian Christian Holzer, Andrii Vozniuk

Finding relevant content is one of the core activities of users interacting with a content repository, be it knowledge workers using an organizational knowledge management system at a workplace or self-regulated learners collaborating in a learning environ ...

2016

EU-FP7-IMARS: Analysis of Mars multi-resolution images using auto-coregistration, data mining and crowd source techniques: Processed results - A first look

Anton Ivanov

Understanding planetary atmosphere-surface exchange and extra-terrestrial-surface formation processes within our Solar System is one of the fundamental goals of planetary science research. There has been a revolution in planetary surface observations over ...

Copernicus Gesellschaft Mbh2016

Mobility: topic detection in social networks

Dominique Georges Léon Boullier, Jean-François Lucas

Social networks such as Facebook and Twitter are privileged platforms for teenagers’ expression and information sharing. This study, based on a Big Data approach, aims to explore how persons under 18 years old “talk” about their mobility behaviors and aspi ...

2016

SwissCheese at SemEval-2016 Task 4: Sentiment Classification Using an Ensemble of Convolutional Neural Networks with Distant Supervision

Martin Jaggi, Aurélien Lucchi

In this paper, we propose a classifier for predicting message-level sentiments of English micro-blog messages from Twitter. Our method builds upon the convolutional sentence embedding approach proposed by (Severyn and Moschitti, 2015a; Severyn and Moschitt ...

2016

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