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Robustness, replicability and scalability in topic modelling

Publications associées (32)

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Extracting Mobile Behavioral Patterns with the Distant N-Gram Topic Model

Daniel Gatica-Perez, Katayoun Farrahi

Mining patterns of human behavior from large-scale mobile phone data has potential to understand certain phenomena in society. The study of such human-centric massive datasets requires new mathematical models. In this paper, we propose a probabilistic topi ...

2012

As we live our daily lives, our surroundings know about it. Our surroundings consist of people, but also our electronic devices. Our mobile phones, for example, continuously sense our movements and interactions. This socio-geographic data could be continuo ...

EPFL2011

Mining Human Location-Routines Using a Multi-Level Approach to Topic Modeling

Daniel Gatica-Perez, Katayoun Farrahi

In this work we address the problem of modeling varying time duration sequences for large-scale human routine discovery from cellphone sensor data using a multi-level approach to probabilistic topic models. We use an unsupervised learning approach that dis ...

2010

Fisher Kernels and Probabilistic Latent Semantic Models

Emmanuel Eckard

Tasks that rely on semantic content of documents, notably Information Retrieval and Document Classification, can benefit from a good account of document context, i.e. the semantic association between documents. To this effect, the scheme of latent semantic ...

EPFL2010

Modeling and Understanding Flickr Communities through Topic-based Analysis

Daniel Gatica-Perez, Radu Andrei Negoescu

With the increased presence of digital imaging devices there also came an explosion in the amount of multimedia content available online. Users have transformed from passive consumers of media into content creators and have started organizing themselves in ...

2010

Rôle de la matrice d'information et pondération des composantes dans les noyaux de Fisher pour PLSI

Jean-Cédric Chappelier, Emmanuel Eckard

ABSTRACT. An information-geometric approach for document similarities in the framework of “Probabilistic Latent Semantic Indexing” was ﬁrst proposed by T. Hofmann (2000) and later extended (“revisited”) by Nyffenegger et al. (2006). This paper presents an ...

2009

The Probabilistic Latent Semantic indexing model, introduced by T. Hofmann (1999), has engendered applications ill numerous fields, notably document classification and information retrieval. In this context, the Fisher kernel was found to be an appropriate ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009

A Thousand Words in a Scene

Daniel Gatica-Perez, Jean-Marc Odobez, Pedro Manuel Da Silva Quelhas

This paper presents a novel approach for visual scene modeling and classification, investigating the combined use of text modeling methods and local invariant features. Our work attempts to elucidate (1) whether a text-like \emph{bag-of-visterms} represent ...

2007

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Pedro Manuel Da Silva Quelhas

The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...

École Polytechnique Fédérale de Lausanne2007

Scene image classification and segmentation with quantized local descriptors and latent aspect modeling

Pedro Manuel Da Silva Quelhas

EPFL2007