Recently, the research towards Brodatz database for texture classification done at considerable amount of study has been published, the effective classification are vulnerable towards for training and test sets. This study presents the novel texture classification method based on feature descriptor, called spatial cooccurrence with discrete shearlet transformation through the LPboosting classif...

We investigate the task of medical concept coreference resolution in clinical text using two semi-supervised methods, co-training and multi-view learning with posterior regularization. By extracting semantic and temporal features of medical concepts found in clinical text, we create conditionally independent data views; co-training MaxEnt classifiers on this data works almost as well as supervi...

This paper introduces a new bootstrapping method closely related to co-training and scoped-learning. The method is tested on a Web information extraction task of learning course names from web pages in which we use very few labelled items as seed data (10 web pages) and combine with an unlabelled set (174 web pages). The overall performance improved the precision/recall from 3.11%/0.31% for a b...

keep in mind the importance of cadmium, cobalt and nickel ions as environmentally and economically strategic heavy metals, the application of two acidic extractants, named bis(2-diethylhexyl)phosphoric acid (dehpa) and 2-thenoyltrifluoroacetone (htta), was assessed for the extraction-recovery of these ions from leached solution of spent rechargeable ni-cd batteries. the conditions for leaching ...

Seeds are another product in addition to leaves (raw materials for teas) of tea (Camellia sinensis L.) plant. The great increase of tea consumption in recent years raises the challenge of finding commercial applications for tea seeds. In the present study, supercritical carbon dioxide (SC-CO(2)) extraction edible oil from tea seed was carried out, response surface methodology (RSM) was used to ...

Identification of diseases based on processing and analysis of medical images is of great importance for medical doctors to assist them in their decision making. In this work, a new feature extraction method based on human tissue density patterns, named Analysis of Human Tissue Densities (AHTD) is presented. The proposed method uses radiological densities of human tissues in Hounsfield Units to...

This paper proposes a semi-supervised learning method for relation extraction. Given a small amount of labeled data and a large amount of unlabeled data, it first bootstraps a moderate number of weighted support vectors via SVM through a co-training procedure with random feature projection and then applies a label propagation (LP) algorithm via the bootstrapped support vectors. Evaluation on th...

We present results on the relation discovery task, which addresses some of the shortcomings of supervised relation extraction by applying minimally supervised methods. We describe a detailed experimental design that compares various configurations of conceptual representations and similarity measures across six different subsets of the ACE relation extraction data. Previous work on relation dis...

We focus on the problem of predicting functional properties of the proteins corresponding to genes in the yeast genome. Our goal is to study the effectiveness of approaches that utilize all data sources that are available in this problem setting, including unlabeled and relational data, and abstracts of research papers. We study transduction and co-training for using unlabeled data. We investig...