The CoMeRe project aims to build a kernel corpus of different computer-mediated communication (CMC) genres with interactions in French as the main language, by assembling interactions stemming from networks such as the Internet or telecommunications, as well as mono and multimodal, and synchronous and asynchronous communications. Corpora are assembled using a standard, thanks to the Text Encodi...

This paper explores the task of building an accurate prepositional phrase attachment corpus for new genres while avoiding a large investment in terms of time and money by crowdsourcing judgments. We develop and present a system to extract prepositional phrases and their potential attachments from ungrammatical and informal sentences and pose the subsequent disambiguation tasks as multiple choic...

This paper describes a Verb Phrase Ellipsis (VPE) detection system, built for robustness, accuracy and domain independence. The system is corpus-based, and uses machine learning techniques on free text that has been automatically parsed. Tested on a mixed corpus comprising a range of genres, the system achieves a 70% F1-score. This system is designed as the first stage of a complete VPE resolut...

We are compiling a corpus of Dutch texts annotated with discourse structure and lexical cohesion, containing initially 80 texts from expository and persuasive genres. We are using this resource for corpus-based studies of discourse relations, discourse markers, cohesion, and genre differences. We are also exploring the possibilities of automatic text segmentation and semi-automatic discourse an...

Categorization of text in IR has traditionally focused on topic. As use of the Internet and e−mail increases, categorization has become a key area of research as users demand methods of prioritizing documents. This work investigates text classification by format style, i.e. "genre", and demonstrates, by complementing topic classification, that it can significantly improve retrieval of informati...

The CoMeRe project aims to build a kernel corpus of different Computer-Mediated Communication (CMC) genres with interactions in French as the main language, by assembling interactions stemming from networks such as the Internet or telecommunication, as well as mono and multimodal, synchronous and asynchronous communications. Corpora are assembled using a standard, thanks to the TEI (Text Encodi...

Due to the large amount of available patent data, it is no longer feasible for industry actors to manually create their own terminology lists and ontologies. Furthermore, domain specific thesauruses are rarely accessible to the research community. In this paper we present extraction of hyponymy lexical relations conducted on patent text using lexico-syntactic patterns. We explore the lexico-syn...

Abstract Genre recognition is a critical facet of text comprehension and text classification. In three experiments, we assessed the minimum number of words in a sentence needed for genre recognition to occur, the distribution of genres across text, and the relationship between reading ability and genre recognition. We also propose and demonstrate a computational model for genre recognition. Usi...

The present study aims at the quantitative classification of texts and text types. By way of a case study, 398 Slovenian texts from different genres and authors are analyzed as to their word length. It is shown that word length is an important factor in the synergetic self-regulation of texts and text types, and that word length may significantly contribute to a new typology of discourse types.

A simple method for categorizing texts into pre-determined text genre categories using the statistical standard technique of discriminant analysis is demonstrated with application to the Brown corpus. Discriminant analysis makes it possible use a large number of parameters that may be specific for a certain corpus or information stream, and combine them into a small number of functions, with th...