Classification of Web page content is essential to many tasks in Web information retrieval
such as maintaining Web directories and focused crawling. The uncontrolled nature of Web …

Text mining is a new and exciting area of computer science research that tries to solve the
crisis of information overload by combining techniques from data mining, machine learning …

Many real-world domains are relational in nature, consisting of a set of objects related to
each other in complex ways. This paper focuses on predicting the existence and the type of …

Thresholding strategies in automated text categorization are an underexplored area of
research. This paper presents an examination of the effect of thresholding strategies on the …

We study an approach to text categorization that combines distributional clustering of words
and a Support Vector Machine (SVM) classifier. This word-cluster representation is …

Hypertext poses new research challenges for text classification. Hyperlinks, HTML tags,
category labels distributed over linked documents, and meta data extracted from related …

Most real-world data is heterogeneous and richly interconnected. Examples include the
Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning …

Abstract The semantic Web Services vision requires that each service be annotated with
semantic metadata. Manually creating such metadata is tedious and error-prone, and many …

In this paper we address the problem of discovering missing hypertext links in Wikipedia.
The method we propose consists of two steps: first, we compute a cluster of highly similar …

Purpose–To provide an integrated perspective to similarities and differences between
approaches to automated classification in different research communities (machine learning …