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This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access: - information extraction and retrieval; - text classification and clustering; - opinion mining; - comprehension aids (automatic summarization, machine translation, visualization). In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications concerned, by highlighting the relationship between models and applications and by illustrating the behavior of each model on real collections. Textual Information Access is organized around four themes: informational retrieval and ranking models, classification and clustering (regression logistics, kernel methods, Markov fields, etc.), multilingualism and machine translation, and emerging applications such as information exploration. Contents Part 1: Information Retrieval 1. Probabilistic Models for Information Retrieval, Stéphane Clinchant and Eric Gaussier. 2. Learnable Ranking Models for Automatic Text Summarization and Information Retrieval, Massih-Réza Amini, David Buffoni, Patrick Gallinari, Tuong Vinh Truong and Nicolas Usunier. Part 2: Classification and Clustering 3. Logistic Regression and Text Classification, Sujeevan Aseervatham, Eric Gaussier, Anestis Antoniadis, Michel Burlet and Yves Denneulin. 4. Kernel Methods for Textual Information Access, Jean-Michel Renders. 5. Topic-Based Generative Models for Text Information Access, Jean-Cédric Chappelier. 6. Conditional Random Fields for Information Extraction, Isabelle Tellier and Marc Tommasi. Part 3: Multilingualism 7. Statistical Methods for Machine Translation, Alexandre Allauzen and François Yvon. Part 4: Emerging Applications 8. Information Mining: Methods and Interfaces for Accessing Complex Information, Josiane Mothe, Kurt Englmeier and Fionn Murtagh. 9. Opinion Detection as a Topic Classification Problem, Juan-Manuel Torres-Moreno, Marc El-Bèze, Patrice Bellot and Fréderic Béchet.
This book constitutes the proceedings of the 7th International Conference on Advances in Natural Language Processing held in Reykjavik, Iceland, in August 2010.
Cet ouvrage de synthèse sur les fondements théoriques et épistémologiques de la science de l’information répond à trois questions : – existe-t-il une science de l’information à part entière ? – comment se définit l’information, objet de cette science ? – y a-t-il une spécificité française de la science de l’information ? Ce livre compare les chemins parcourus par la science de l’information en France et dans le reste du monde. Il contextualise cette évolution à l’aune d’une diversité d’inscriptions disciplinaires. L’enjeu de la science de l’information est de concilier l’approche réaliste de la connaissance, l’approche individualiste des sciences cognitives et l’approche collectiviste où les domaines sont façonnés et les comportements sont modulés par les environnements, les cultures et les construits sociaux partagés. Cette étude sera utile à tous les chercheurs, étudiants et professionnels désirant approfondir leurs connaissances sur les fondements théoriques de la science de l’information.
Cet ouvrage réconcilie la philosophie, la biologie, la sociologie et les sciences cognitives grâce à un dénominateur commun, la conscience. Il en présente un aspect particulier, le concept d’auto-motivation de champ d’activité en tant que moteur biologique d’un état de conscience, et dont l’informatique systémique permet de révéler l’existence. Si la conscience est mal définie, un cadre réduit permet d’en donner une définition plus précise, observable malgré toute la complexité psychologique, sociale et technique de l’individu. Ces observations sont de deux natures : une nature d’activité principale et une nature cognitivo-linguistique, modulées par des facteurs de contrôle intrinsèques et extrinsèques. L’argument exposé consiste à présenter un état de conscience relatif à la notion de besoin informationnel instinctif, donc physiologique, et dont les traces porteuses sur les supports physiques (revues, abonnements, etc.) ou numériques (sms, web, etc.), sont analysables par l’extraction de connaissances.
French-English compilation of ISO standards on data processing and EDP definitions (glossarys) - covers arithmetic and logical operations, organization, representation, preparation and handling of data, information retrieval, digital computer programmeing, information theory, etc.
The technological interoperability of digital libraries must be rethought in order to adapt to new uses and networks. Informative digital environments aimed at responding to heritage, cultural, scientific or commercial demands have taken over the global cyberspace and have redesigned the techno-informative landscape of the Web. However, while the technological models demonstrate their effectiveness and explain to a large extent the creation of digital libraries, archives and deposits, the subjacent concept of uses continues to cause debate. The information technologies used by heterogeneous digital libraries enable a technical interoperability of content. This is not enough to allow the adhesion of a public connected to very different information profiles and techniques. This book explores the avenues of a user-orientated interoperability where the questions of consultation interfaces and content description processes are studied. - Discusses Metadata as a resource for linking - Provides a practical approach - A valuable resource for anyone involved in digital library developments and digital collections and services
Collective Intelligence and Digital Archives DIGITAL TOOLS AND USES SET Coordinated by Imad Saleh This book presents the most up-to-date research from different areas of digital archives to show how and why collective intelligence is being developed to organize and better communicate new masses of information. Current archive digitization projects produce an enormous amount of digital data (Big Data). Thanks to the proactive approach of large public institutions, this data is increasingly accessible. Despite the recent stabilization of technical and legal frameworks, the use of data has yet to be enriched by processes such as collective intelligence. By exploring the field of digital humanities, audiovisual archives, preservation of cultural heritage, crowdsourcing and the recovery of scientific archives, this book presents and analyzes concrete examples of collective intelligence for use in digital archives.