Multi-label Document Categorization, the task of automatically assigning a text document into one or more categories has various real-world applications such as categorizing news articles, tagging Web pages, maintaining medical patient records and organizing digital libraries among many others. Statistical Machine Learning approaches to document categorization have focused on multi-label learni...

The aim of the paper is to describe the information retrieval model which retrieves information from text documents in natural language by neural networks. This model comes from the linguistic and conceptual approach for the analysis of text documents. The neural network model accepts the structure of conceptual, lingvistic oriented model, where the problem of document database creation and doc...

Watermarking is an important copyright protection technology which generally embeds the identity information into carrier imperceptibly. Then can be extracted to prove from watermarked even after suffering various attacks. Most of existing watermarking technologies take nature images as carriers. Different natural images, document are not so rich in color and texture, thus have less redundant c...

Applications of multi-class classification, such as document categorization, often appear in cost-sensitive settings. Recent work has significantly improved the state of the art by moving beyond “flat” classification through incorporation of class hierarchies [4]. We present a novel algorithm that goes beyond hierarchical classification and estimates the latent semantic space that underlies the...

OBJECTIVE The purpose of this article is to discuss how to convert cross-sectional images into a 3D model and embed them in a Portable Document Format (PDF) file. Four programs are used: OsiriX, MeshLab, Microsoft PowerPoint, and Adobe Acrobat. Step-by-step instructions are provided. CONCLUSION Embedding 3D radiology models into PDF files is a powerful tool that may be used for clinical, educ...