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Explicit Suggestion of Query Terms for News Search using Topic Models and Word Embeddings

Publications associées (44)

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Topic-Level Extractive Summarization of Lectures and Meetings Using a Snippet Similarity Graph

Andrei Popescu-Belis

In this paper, we present an approach for topic-level video snippet-based extractive summarization, which relies on con tent-based recommendation techniques. We identify topic-level snippets using transcripts of all videos in the dataset and indexed these ...

Idiap2014

Is Deep Learning Really Necessary for Word Embeddings?

Rémi Philippe Lebret, Ronan Collobert, Joël Yvon Roland Legrand

Word embeddings resulting from neural language models have been shown to be successful for a large variety of NLP tasks. However, such architecture might be difficult to train and time-consuming. Instead, we propose to drastically sim- plify the word embed ...

Idiap2013

Combining Content with User Preferences for TED Lecture Recommendation

Andrei Popescu-Belis, Nikolaos Pappas

This paper introduces a new dataset and compares several methods for the recommendation of non-fiction audio-visual material, namely lectures from the TED website. The TED dataset contains 1,149 talks and 69,023 user profiles, who have made more than 100,0 ...

IEEE2013

Semantic Vector Machines

Vincent Etter

We first present our work in machine translation, during which we used aligned sentences to train a neural network to embed n-grams of different languages into an d-dimensional space, such that n-grams that are the translation of each other are close with ...

2009

Discovering Human Routines from Cell Phone Data with Topic Models

Daniel Gatica-Perez, Katayoun Farrahi

We present a framework to automatically discover people's routines from information extracted by cell phones. The framework is built from a probabilistic topic model learned on novel bag type representations of activity-related cues (location, proximity an ...

2008

Discovering Human Routines from Cell Phone Data with Topic Models

Daniel Gatica-Perez, Katayoun Farrahi

IDIAP2008

Google Portrait

Sébastien Marcel

This paper presents a system to retrieve and browse images from the Internet containing only one particular object of interest: the human face. This system, called Google Portrait, uses Google Image search engine to retrieve images matching a text query an ...

IDIAP2007

Keyword based indexing and searching over storage resource broker

Laurent Francioli, Adnan Abid

A keyword based metadata indexing and searching facility for Storage Resource Broker (SRB) is presented here. SRB is a popular data grid based storage system that provides means to store data and associate metadata information with the stored data. The met ...

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2007

Finding groups of people in Google news

Daniel Gatica-Perez

In this paper, we study the problem of content-based social network discovery among people who frequently appear in world news. Google news is used as the source of data. We describe a probabilistic framework for associating people with groups. A low-dimen ...

2006

Finding groups of people in Google news

Daniel Gatica-Perez

IDIAP2005