Purpose – The purpose of this article is to discuss open access to scholarly full-text documents. Design/methodology/approach – Discusses open access to scholarly full-text documents. Findings – The paper shows that while open access archives are good for the majority, for publishers, editors and authors, open access articles can substantially increase their impact, and the impact factor for th...

The volume of digitized text documents on the web have been increasing rapidly. As there is huge collection of data on the web there is a need for grouping(clustering) the documents into clusters for speedy information retrieval. Clustering of documents is collection of documents into groups such that the documents within each group are similar to each other and not to documents of other groups...

The digital computer and computer networks have made it possible to search for and retrieve electronically stored documents in seconds, no matter where in the world they are stored. This is far from the reality for documents stored as paper copies. Therefore there is considerable interest in digitizing paper documents. To digitize existing paper documents, it is of great importance to be able t...

Information in the internet is evolving in terms of high volume through different sources. Extracting tuples from HTML pages has been an important issue in various web applications such as web data integration, e-commerce market monitoring, and mash ups that repurpose and selectively combine existing web data services. Data Mining is the process of analyzing data from different perspectives and...

The internet is a huge source of documents, containing a massive number of texts in multilingual languages on a wide range of topics. These texts are demonstrating in an electronic documents format hosted on the web. The documents exchanged using special forms in an Electronic Data Interchange (EDI) environment. Using web text mining approaches to mine documents in EDI environment could be new ...

Supervised learning algorithms usually require large amounts of training data to learn reasonably accurate classifiers. Yet, for many text classification tasks, providing labeled training documents is expensive, while unlabeled documents are readily available in large quantities. Learning from both, labeled and unlabeled documents, in a semi-supervised framework is a promising approach to reduc...

1. Profiling and classification of scientific documents with SAS Text Miner SAS Institute (www.sas.com) and the European Molecular Biology Laboratory (EMBL)/ the ELM Consortium (http://elm.eu.org) are cooperating on the development of a text mining-application for the automated identification and ranking of scientific articles. The so-called “topic scoring engine” is based on the SAS Text Miner...

Purpose – The purpose of this article is to discuss open access to scholarly full-text documents. Design/methodology/approach – Discusses open access to scholarly full-text documents. Findings – The paper shows that while open access archives are good for the majority, for publishers, editors and authors, open access articles can substantially increase their impact, and the impact factor for th...

Categorization of text plays an important role in the text mining field. Text categorization is the process in which documents are categorized into its predefined category. Automatic text categorization is an important task due to large amount of electronic documents. This paper presents a survey of Text categorization of Indian and non-Indian languages. There is very less work done in text cat...

Most conventional natural language processing (NLP) tools assume plain text as their input, whereas real-world documents display text more expressively, using a variety of layouts, sentence structures, and inline objects, among others. When NLP tools are applied to such text, users must first convert the text into the input/output formats of the tools. Moreover, this awkwardly obtained input ty...