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Text mining [[electronic resource] ] : applications and theory / / Michael W. Berry, Jacob Kogan



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Autore: Berry Michael W Visualizza persona
Titolo: Text mining [[electronic resource] ] : applications and theory / / Michael W. Berry, Jacob Kogan Visualizza cluster
Pubblicazione: Hoboken, NJ, : John Wiley & Sons, 2010
Descrizione fisica: 1 online resource (223 p.)
Disciplina: 006.3/12
Soggetto topico: Data mining
Natural language processing (Computer science)
Soggetto genere / forma: Electronic books.
Altri autori: KoganJacob <1954->  
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: Text Mining; Contents; List of Contributors; Preface; PART I TEXT EXTRACTION, CLASSIFICATION, AND CLUSTERING; 1 Automatic keyword extraction from individual documents; 2 Algebraic techniques for multilingual document clustering; 3 Content-based spam email classification using machine-learning algorithms; 4 Utilizing nonnegative matrix factorization for email classification problems; 5 Constrained clustering with k-means type algorithms; PART II ANOMALY AND TREND DETECTION; 6 Survey of text visualization techniques; 7 Adaptive threshold setting for novelty mining; 8 Text mining and cybercrime
PART III TEXT STREAMS9 Events and trends in text streams; 10 Embedding semantics in LDA topic models; Index
Sommario/riassunto: Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine
Titolo autorizzato: Text mining  Visualizza cluster
ISBN: 1-282-55136-1
9786612551369
0-470-68964-1
0-470-68965-X
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996200265003316
Lo trovi qui: Univ. di Salerno
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