To allow the average-voice-based speech synthesis technique to generate synthetic speech that is more similar to that of the target speaker, we propose a model training technique that introduces the label of speaker class. Speaker class represents the voice characteristics of speakers. In the proposed technique, first, all training data are clustered to determine classes of speaker type. The av...

Frequent Itemsets (FIs) mining is a fundamental primitive in data mining that requires to identify all itemsets appearing in a fraction at least θ of a transactional dataset D. Often though, the ultimate goal of mining D is not an analysis of the dataset per se, but the understanding of the underlying process that generated D. Specifically, in many applications D is a collection of samples obta...

The collection of census data is an important task with respect to providing support for decision makers. However, the collection of census data is also resource intensive. This is especially the case in areas which feature poor communication and transport networks. In this paper a method is proposed for collecting census data by applying classification techniques to relevant satellite imagery....

In this paper, we compare three different generalization methods for in-domain and cross-domain opinion holder extraction being simple unsupervised word clustering, an induction method inspired by distant supervision and the usage of lexical resources. The generalization methods are incorporated into diverse classifiers. We show that generalization causes significant improvements and that the i...

Sentiment Classification seeks to identify a piece of text according to its author’s general feeling toward their subject, be it positive or negative. Traditional machine learning techniques have been applied to this problem with reasonable success, but they have been shown to work well only when there is a good match between the training and test data with respect to topic. This paper demonstr...

While substantial studies have been achieved on sentiment polarity classification to date, lacking enough opinion-annotated corpora for reliable t rain ing is still a challenge. In this paper we propose to improve a supported vector machines based polarity classifier by enriching both training data and test data via opinion paraphrasing. In particular, we first extract an equivalent set of attr...

Discriminative learning methods for classification perform well when training and test data are drawn from the same distribution. In many situations, though, we have labeled training data for a source domain, and we wish to learn a classifier which performs well on a target domain with a different distribution. Under what conditions can we adapt a classifier trained on the source domain for use...

background:  due to difficulty in obtaining anatomical reduction, management of the unstable intertrochanteric fractures in elderly osteoporotic patients is challenging. the purpose of this study is to compare the results of hip arthroplasty (total, hemi, or bipolar) with dhs in the elderly patients with unstable intertrochanteric fractures.   methods:  we prospectively studied and followed-up ...