Text mining : from ontology learning to automated text processing applications / edited by Chris Biemann, Alexander Mehler.

Springer eBooks

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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