In this paper, we firstly propose an extended probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding EM algorithm is derived to determine the parameters. Then, we apply this model in automatic image annotation. In order to deal with the data of different modalities according to their characteristics, we present a semantic annotation model which em...

We investigate the problem of item recommendation during the first months of the collaborative tagging community Ci­ teULike. CiteULike is a so-called folksonomy where users have the possibility to organize publications through anno­ tations tags. Making reliable recommendations during the initial phase of a folksonomy is a difficult task, since infor­ mation about user preferences is meager. I...

This paper proposes an improved approach of summarization for spoken multi-party interaction, in which intra-speaker and inter-speaker topics are modeled in a graph constructed with topical relations. Each utterance is represented as a node of the graph and the edge between two nodes is weighted by the similarity between the two utterances, which is topical similarity evaluated by probabilistic...

Probabilistic Latent Semantic Analysis (PLSA) is an effective technique for information retrieval, but it has a serious drawback: it consumes a huge amount of computational resources, so it is hard to train this model on a large collection of documents. The aim of this paper is to improve time efficiency of the training algorithm. Two different approaches are explored: one is based on efficient...

Many queries on collections of text documents are too short to produce informative results. Automatic query expansion is a method of adding terms to the query without interaction from the user in order to obtain more refined results. In this investigation, we examine our novel automatic query expansion method using the probabilistic latent semantic thesaurus, which is based on probabilistic lat...

This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are selected in order to minimize a loss related to the ranking performance of the model, i.e. its ability to rank the relevant pictures above the non-relevant ones when given a text query. In order to minimize this loss, we...

We propose a method to improve the recognition rate of Bayesian classifiers by splitting the training data and using separate classifier to learn each sub-category. We use probabilistic Latent Semantic Analysis (pLSA) to split the training set automatically into subcategories. This sub-categorization is based on the similarity of training images in terms of object’s appearance or background con...

In this paper, we present a new method for refining image annotation by integrating probabilistic latent semantic analysis (PLSA) with random walk (RW) model. First, we construct a PLSA model with asymmetric modalities to estimate the posterior probabilities of each annotating keywords for an image, and then a label similarity graph is constructed by a weighted linear combination of label simil...

Tags are intensively used in social platforms to annotate resources: Tagging is a social phenomenon, because users do not only annotate to organize their resources but also to associate semantics to resources contributed by third parties. This leads often to semantic ambiguities: Popular tags are associated with very disparate meanings, even to the extend that some tags (e.g. ”beautiful” or ”to...

Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of documents. The measurement of semantics as similarity in patterns (correlations) and latent variables (factor analysis) has been enhanced by computer techniques and the use of statistics; for example, in “Latent Semantic Analy...