CLASSIFICATION AND CATEGORIZATION IN COMPUTER-ASSISTED READING AND TEXT ANALYSIS

Automated computer classification and categorization have been successfully applied in the field of document retrieval and text mining. These methods are increasingly used in the field of computer-assisted reading and analysis of texts (CARAT) in the field of the humanities and social sciences. Here, the primary aim is not to tag the document for better recall, but to help a specialized reader and analyst to navigate through the themes, concepts, and content of a textual corpus according to a particular research objective. This chapter presents some of the methods and applications of these techniques.

[1]  Wolfgang Iser,et al.  L'acte de lecture : théorie de l'effet esthétique , 1976 .

[2]  Kenneth Ward Church,et al.  Parsing, Word Associations and Typical Predicate-Argument Relations , 1989, HLT.

[3]  Allen Newell,et al.  Intellectual issues in the history of artificial intelligence , 1983 .

[4]  Étienne Brunet,et al.  Méthodes quantitatives et informatiques dans l'étude des textes , 1986 .

[5]  C. Barry Choosing Qualitative Data Analysis Software: Atlas/ti and Nudist Compared , 1998 .

[6]  William C. Mann,et al.  Rhetorical Structure Theory: Toward a functional theory of text organization , 1988 .

[7]  Jacques Jenny,et al.  Methodes Et Pratiques Formalisees D'Analyse De Contenu Et De Discours Dans La Recherche Sociologique Francaise Contemporaine. Etat Des Lieux Et Essai De Classification , 1997 .

[8]  Alastair McKinnon Some conceptual ties in Descartes' Meditations , 1979 .

[9]  Serge Lusignan Quelques Réflexions sur le Statut Epistémologique du Texte Electronique , 1985, Comput. Humanit..

[10]  William A. Gale,et al.  A sequential algorithm for training text classifiers , 1994, SIGIR '94.

[11]  Yves Kodratoff,et al.  Knowledge Discovery in Texts: A Definition, and Applications , 1999, ISMIS.

[12]  François Rastier,et al.  Arts et sciences du texte , 2001 .

[13]  Padmini Srinivasan,et al.  Automatic Text Categorization Using Neural Networks , 1997 .

[14]  W. B. Cavnar,et al.  N-gram-based text categorization , 1994 .

[15]  Stephen Grossberg,et al.  ART 2-A: An adaptive resonance algorithm for rapid category learning and recognition , 1991, Neural Networks.

[16]  U. Eco,et al.  Les limites de l'interprétation , 1992 .

[17]  Michel Bernard Introduction aux études littéraires assistées par ordinateur , 1999 .

[18]  Nello Cristianini,et al.  An introduction to Support Vector Machines , 2000 .

[19]  H. R. Jauss,et al.  Pour une esthétique de la réception , 1978 .

[20]  Jean-Guy Meunier,et al.  La classification mathématique des textes : un outil d'assistance à la lecture et à l'analyse de textes philosophiques , 2000 .

[21]  Alastair McKinnon La Philosophie et les ordinateurs , 1968 .

[22]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[23]  Bertrand Gervais,et al.  A l'écoute de la lecture , 1993 .

[24]  Peter E. Hart,et al.  The condensed nearest neighbor rule (Corresp.) , 1968, IEEE Trans. Inf. Theory.

[25]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[26]  Hans Georg Gadamer,et al.  Vérité et méthode : les grandes lignes d'une herméneutique philosophique , 1976 .

[27]  Ryszard S. Michalski,et al.  A Theory and Methodology of Inductive Learning , 1983, Artificial Intelligence.

[28]  M Damashek,et al.  Gauging Similarity with n-Grams: Language-Independent Categorization of Text , 1995, Science.

[29]  U. Eco,et al.  L'œuvre ouverte , 1965 .