Text Mining: From Ontology Learning to Automated Text Processing Applications - Tapa blanda

Sinopsis

Foreword.- PART I. Text Mining Techniques and Methodologies.- Thomas Eckart, Dirk Goldhahn, and Uwe Quasthoff: Building large resources for text mining.- Hristo Tanev: Learning Textologies: Networks of Linked Word Clusters.- Zornitsa Kozareva: Simple, Fast and Accurate Taxonomy Learning.- Patrick Oesterling, Christian Heine, Gunther H. Weber and Gerik Scheuermann: A Topology-Based Approach to Visualize the Thematic Composition of Document Collections.- Alexander Mehler, Tim vor der Brück, Rüdiger Gleim and Tim Geelhaar: Towards a Network Model of the Coreness of Texts; An Experiment in Classifying Latin Texts using the TTLab Latin Tagger.- PART II. Text Mining Applications. Stefan Bordag and Christian Hänig and Christian Beutenmüller: A structuralist approach for personal knowledge exploration systems on mobile devices.- Frank Oemig and Bernd Blobel: Natural Language Processing Supporting Interoperability in Healthcare.- Veronica Perez-Rosas, Cristian Bologa, Mihai Burzo and Rada Mihalcea: Deception Detection Within and Across Cultures.- Jonathan Sonntag and Manfred Stede: Sentiment Analysis: What's your Opinion?.- Marten Düring and Antal van den Bosch: Multi-perspective Event Detection in Texts Documenting the 1944 Battle of Arnhem.- Marco Büchler, Philip R. Burns, Martin Müller, Emily Franzini and Greta Franzini: Towards a Historical Text Re-use Detection.

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