We propose an unsupervised feature generation algorithm using the repositories of human
knowledge for effective text categorization. Conventional bag of words (BOW) depends on …

There are an increasing number of online documents and an automated document
classification is an important challenge. It is essential to be able to automatically organize …

Text classification has been widely used to assist users with the discovery of useful
information from the Internet. However, traditional classification methods are based on the …

The insufficiency and irrelevancy of training corpora is always the main task to overcome
while doing text classification. This paper proposes a Web-based text classification …

Single term based document representations, eg bag-of-words, have been widely accepted
in the machine learning, information retrieval and text mining community. One notable …

This paper proposed a knowware based supervised machine learning technique for domain
specific regression and classification of Web documents. It is simple because it is only based …

Text classification is a topic in natural language processing that is particularly useful for
Internet information processing. Methods based on supervised learning require a large …

We have developed a research support system, called Papits, that shares research
information, such as PDF files of research papers, in computers on the network and …

We present a novel method employing a hierarchical domain ontology structure to select
features representing documents. All raw words in the training documents are mapped to …

This paper introduces a new approach to creating text representations and apply it to a
standard text classification collections. The approach is based on supplementing the well …