Sentiment analysis of documents aims to characterise the positive or negative sentiment expressed in documents. It has been formulated as a supervised classification problem, which requires large numbers of labelled documents. Semi-supervised sentiment classification using limited documents or words labelled with sentiment-polarities are approaches to reducing labelling cost for effective learn...

BACKGROUND The process of merging data of different data sources is referred to as record linkage. A medical environment with increased preconditions on privacy protection demands the transformation of clear-text attributes like first name or date of birth into one-way encrypted pseudonyms. When performing an automated or privacy preserving record linkage there might be the need of a binary cla...

In this paper, a new approach for mapping based on the concept of objects and relationships between these objects is proposed to take advantage from both supervised and unsupervased classification methods. On the one hand, objects obtained after a supervised classification are represented by an adjacency graph model. On the other hand, objects obtained after unsupervised classification are repr...

In this paper, we propose to fuse both clustering and supervised classification approach in order to outperform the results of a classification algorithm. Indeed the results of the learning in supervised classification depend on the method and on the parameters chosen. Moreover the learning process is particularly difficult which few learning data and/or imprecise learning data. Hence, we defin...

In this paper, we propose to develop the supervised classification method Fuzzy Pattern Matching to be in addition a non supervised one. The goal is to monitor dynamic systems with a limited prior knowledge about their functioning. The detection of the occurrence of new states as well as the reinforcement of the estimation of their membership functions are performed online thanks to the combina...

The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification. In this paper, we proposed a novel method, called semi-supervised marginal Fisher analysis (SSMFA), to process HSI of natural scenes, which uses ...

seismic facies analysis (sfa) aims to classify similar seismic traces based on amplitude, phase,frequency, and other seismic attributes. sfa has proven useful in interpreting seismic data, allowingsignificant information on subsurface geological structures to be extracted. while facies analysis hasbeen widely investigated through unsupervised-classification-based studies, there are few casesass...

This paper compares multilook Polarimetric SAR (PolSAR) image classification using three types of learning: a supervised, an unsupervised and a semisupervised. The multilook PolSAR pixel values are complex covariance matrices and they are described by mixtures of Wishart distributions. Tests in synthetic and real images showed that the supervised and semisupervised classifications provided the ...