Realizing the value of web content classification, the book, “Automatic Identification of Genre in Web pages, has been published. This serves as a compendium to genetically codify web content. Marina Sanitini in the book with the help of 12 chapters has provided a focus comprehensively on newer aspects of web content study by looking at the taxonomy as well as other the origin of texts. This wa...

In this publication we describe a novel two-dimensional approach for automatic music genre classification. Although the subject poses a well studied task in Music Information Retrieval, some fundamental issues of genre classification have not been covered so far. Especially many modern genres are influenced by manifold musical styles. Most of all, this holds true for the broad category “World M...

Nowadays, powerful music compression tools and cheap mass storage devices have become widely available. This allows average consumers to transfer entire music collections from the distribution medium, such as CDs and DVDs, to their computer hard drive. To locate specific pieces of music, they are usually labeled with artist and title. Yet the user would benefit from a more intuitive organizatio...

We propose an attribute-based taxonomy approach to providing alternative labels to music. Labels, such as genre, are often used as ground-truth for describing song similarity in music information retrieval (MIR) systems. A consistent labelling scheme is usually a key in determining quality of classifier learning in training and performance in testing of an MIR system. We examine links between c...

A novel software system that automatically classifies musical recordings based on genre is presented and discussed. This system is intended as a demonstration of how automated musical feature extraction from MIDI files, machine learning and pattern recognition techniques can be applied to the general tasks of music classification and grouping. The nebulous definitions and overlapping boundaries...

Background: While the Semantic Web concept holds considerable promise, it requires that “machine-readable meaning” of Web content be explicitly marked up. Yet accurate and consistent manual annotation of large quantities of consumer health content is infeasible. Objectives: We set out to develop computerized methods for the task. Methods: First, we created a partial taxonomy of consumer health ...

Over the past decade, there has been an increasing interest in the study of interactional metadiscourse markers in different contexts. However, not much research has been conducted about the discourse of journal author guidelines, especially the use of meta-discourse markers in this genre. Therefore, this corpus-based study had three main aims: 1) to delve deep into the types, frequencies and f...

We present a strategy to perform automatic genre classification of musical signals. The technique divides the signals into 21.3 milliseconds frames, from which 4 features are extracted. The values of each feature are treated over 1-second analysis segments. Some statistical results of the features along each analysis segment are used to determine a vector of summary features that characterizes ...

We introduce the Free Music Archive (FMA), an open and easily accessible dataset which can be used to evaluate several tasks in music information retrieval (MIR), a field concerned with browsing, searching, and organizing large music collections. The community’s growing interest in feature and end-to-end learning is however restrained by the limited availability of large audio datasets. By rele...