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Utilisation de PLSI en recherche d'information

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Data Summarization with Social Contexts

Karl Aberer, Tian Guo, Rameez Rahman, Hao Zhuang, Xia Hu

While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...

Assoc Computing Machinery2016

N-gram-Based Low-Dimensional Representation for Document Classification

Rémi Philippe Lebret, Ronan Collobert

The bag-of-words (BOW) model is the common approach for classifying documents, where words are used as feature for training a classifier. This generally involves a huge number of features. Some techniques, such as Latent Semantic Analysis (LSA) or Latent D ...

2015

Keyword Extraction and Clustering for Document Recommendation in Conversations

Andrei Popescu-Belis, Maryam Habibi

This paper addresses the problem of keyword extraction from conversations, with the goal of using these keywords to retrieve, for each short conversation fragment, a small number of potentially relevant documents, which can be recommended to participants. ...

2015

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This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

Springer2013

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We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., co ...

Springer2012

In conventional vector space model for information retrieval, query vector generation is imperfect for retrieval of precise documents which are de-sired by user. In this paper, we present a stochastic based approach for optimiz-ing query vector without use ...

2012

Using Crowdsourcing to Compare Document Recommendation Strategies for Conversations

Andrei Popescu-Belis, Maryam Habibi

This paper explores a crowdsourcing approach to the evaluation of a document recommender system intended for use in meetings. The system uses words from the conversation to perform just-in-time document retrieval. We compare several versions of the system, ...

2012

Using Crowdsourcing to Compare Document Recommendation Strategies for Conversations

Andrei Popescu-Belis, Maryam Habibi

Idiap2012

Discovering Routines from Large-Scale Human Locations using Probabilistic Topic Models

Daniel Gatica-Perez, Katayoun Farrahi

In this work we discover the daily location-driven routines which are contained in a massive real-life human dataset collected by mobile phones. Our goal is the discovery and analysis of human routines which characterize both individual and group behaviors ...

2011

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