Besides for its own merits, text classification (TC) has become a cornerstone in many applications. Work presented here is part of and a pre-requisite for a project we have overtaken to create a corpus for the Arabic text process. It is an attempt to create modules automatically that would help speed up the process of classification for any text categorization task. It also serves as a tool for...

standardization of photography in plastic surgery is fundamental for pre-operative surgical planning, comparative post-operative assessment, and demonstration of surgical results.1 in rhinoplasty, slight changes in patient or camera position can lessen nasal hump, vary nose size, and alter skin tension.2 in order to prevent these common errors, photographic standardization with high-quality equ...

Feature selection methods, as a preprocessing step to machine learning, are effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improving result comprehensibility. However, the recent increase of dimensionality of data poses a severe challenge to many existing feature selection methods with respect to the efficiency and effectiveness. In this work, ...

Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to unsupervised ones without supervision information. In the literature, nearly all existing supervised feature selection methods use class labels as supervision information. In this paper, we propose to use another form ...

In this paper, we describe the problem of routing trains through a railway station. This routing problem is a subproblem of the automatic generation of timetables for the Dutch railway system. The problem of routing trains through a railway station is the problem of assigning each of the involved trains to a route through the railway station, given the detailed layout of the railway network wit...

Aircraft engines are designed to be used during several tens of years. Ensuring a proper operation of engines over their lifetime is therefore an important and difficult task. The maintenance can be improved if efficient procedures for the understanding of data flows produced by sensors for monitoring purposes are implemented. This paper details such a procedure aiming at visualizing in a meani...

Normalizing named entity abbreviations to their standard forms is an important preprocessing task for question answering, entity retrieval, event detection, microblog processing, and many other applications. Along with the quick expansion of microblogs, this task has received more and more attentions in recent years. In this paper, we propose a novel entity abbreviation generation method using ...

Recent advances in modeling early language acquisition are due not only to the development of machine-learning techniques, but also to the increasing availability of data on child language and child-adult interaction. In the absence of recordings of child-directed speech, or when models explicitly require such a representation for training data, phonemic transcriptions are commonly used as inpu...

We study the statistical performance of spherical fingerprints for a focused detector which decides whether a user of interest is among the colluders. The colluders create a noise-free forgery by preprocessing their individual copies, and then adding a white Gaussian noise sequence to form the actual forgery. Let N be the codelength, M the number of users, and K the number of colluders. We deri...

Training classifiers with datasets which suffer of imbalanced class distributions is an important problem in data mining. This issue occurs when the number of examples representing the class of interest is much lower than the ones of the other classes. Its presence in many real-world applications has brought along a growth of attention from researchers. We shortly review the many issues in mach...