In addition to ordinary words and names, real text contains non-standard “words” (NSWs), including numbers, abbreviations, dates, currency amounts and acronyms. Typically, one cannot find NSWs in a dictionary, nor can one find their pronunciation by an application of ordinary “letter-to-sound” rules. Non-standard words also have a greater propensity than ordinary words to be ambiguous with resp...

This paper reports findings from a case study that investigated the Chinese reading strategies of English speaking learners of Chinese as a Foreign Language (CFL). We focused on CFL learners’ reading of different genres in two different formats, paper-based format and computer-based hypertext format (henceforth hypertext format). Since Chinese characters are categorized in deep orthography, whi...

Every text has at least one topic and at least one genre. Evidence for a text’s topic and genre comes, in part, from its lexical and syntactic features—features used in both Automatic Topic Classification and Automatic Genre Classification (AGC). Because an ideal AGC system should be stable in the face of changes in topic distribution, we assess five previously published AGC methods with respec...

We present the project of classification of Prague Discourse Treebank documents (Czech journalistic texts) for their genres. Our main interest lies in opening the possibility to observe how text coherence is realized in different types (in the genre sense) of language data and, in the future, in exploring the ways of using genres as a feature for multi-sentence-level language technologies. In t...

Our project aims at understanding text genres within the domain of the news. Advances in computational methods and availability of digital corpora has ushered in a new age of empirically testing intuitions about genres and styles, in particular the automatic classification of a document to its genre. At the same time, identifying systematic patterns of difference between genres, both quantitati...

INTRODUCTION Starting with a vast number of unstructured or semi-structured documents, text mining tools analyze and sift through them to present to users more valuable information specific to their information needs. The technologies in text mining include information extrac-In this chapter, we share our hands-on experience with one specific text mining task — text classification [Sebastiani, ...

From a Systemic Semiotic perspective, instances of organisational communication (texts) and their general patterns (text types or genres) are treated as distinct from workplace action and their general patterns (action types). Administrative and Manufacturing systems demonstrate how genres and action types are discursively organised into workpractices. Different kinds of action can be identifie...

In this paper, we present an inferential model for text type and genre identification of web pages, where text types are inferred using a modified form of Bayes’ theorem, and genres are derived using a few simple if-then rules. As the genre system on the web is a complex reality, and web pages are much more unpredictable and individualized than paper documents, we propose this approach as an al...

A digital library is a collection of services and information objects for storing, accessing, and retrieving digital objects. Automatic text summarization presents salient information in a condensed form suitable for user needs. This thesis amalgamates digital libraries and automatic text summarization by extending the Greenstone Digital Library software suite to include the University of Lethb...