Text Mining Teoria E Applicazioni

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Text Mining Teoria E Applicazioni

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Author : Susi Dulli
language : it
Publisher: FrancoAngeli
Release Date : 2004

Text Mining Teoria E Applicazioni written by Susi Dulli and has been published by FrancoAngeli this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.

Fundamentals Of Predictive Text Mining

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Author : Sholom M. Weiss
language : en
Publisher: Springer
Release Date : 2015-09-07

Fundamentals Of Predictive Text Mining written by Sholom M. Weiss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-07 with Computers categories.

This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining social media, errors and pitfalls in big data evaluation, Twitter sentiment analysis, and dependency parsing discussion. The fully updated content also features in-depth discussions on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Features: includes chapter summaries and exercises; explores the application of each method; provides several case studies; contains links to free text-mining software.

Text Mining With Machine Learning

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Author : Jan Žižka
language : en
Publisher: CRC Press
Release Date : 2019-10-31

Text Mining With Machine Learning written by Jan Žižka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.

This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.

Mining Text Data

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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03

Mining Text Data written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-03 with Computers categories.

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Text Mining

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Author : Sholom M. Weiss
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-08

Text Mining written by Sholom M. Weiss and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-08 with Computers categories.

Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they? In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi?ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.

Emerging Technologies Of Text Mining Techniques And Applications

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Author : do Prado, Hercules Antonio
language : en
Publisher: IGI Global
Release Date : 2007-10-31

Emerging Technologies Of Text Mining Techniques And Applications written by do Prado, Hercules Antonio and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-31 with Computers categories.

"This book provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, it will provide libraries with the defining reference on this topic"--Provided by publisher.

Theory And Applications For Advanced Text Mining

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Author : Shigeaki Sakurai
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-11-21

Theory And Applications For Advanced Text Mining written by Shigeaki Sakurai and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-21 with Computers categories.

Due to the growth of computer technologies and web technologies, we can easily collect and store large amounts of text data. We can believe that the data include useful knowledge. Text mining techniques have been studied aggressively in order to extract the knowledge from the data since late 1990s. Even if many important techniques have been developed, the text mining research field continues to expand for the needs arising from various application fields. This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language. I believe that this book will give new knowledge in the text mining field and help many readers open their new research fields.

L Analisi Automatica E Semi Automatica Dei Dati Testuali I

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Author : Luca Giuliano
language : it
Publisher: LED Edizioni Universitarie
Release Date : 2012-05-15T00:00:00+02:00

L Analisi Automatica E Semi Automatica Dei Dati Testuali I written by Luca Giuliano and has been published by LED Edizioni Universitarie this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-15T00:00:00+02:00 with Mathematics categories.

1. INTRODUZIONE ALL’ANALISI DEI DATI TESTUALI 1.1. Informazioni e dati (p. 9). – 1.2. Testo, significato e interpretazione (p. 19). – 1.3 Classificazione dei testi e formazione del corpus (p. 23). - Approfondimenti tematici (p. 27). – Riferimenti bibliografici (p. 29). 2. TESTI ON LINE: LUOGHI E PROCEDURE 2.1. I luoghi della Rete (p. 32). – 2.2. I blog (p. 36). – 2.3. Il download e la sua etica (p. 40). – 2.4. Documento-testo, selezione e pre-trattamento (p. 44). – 2.5. Il corpus utilizzato negli esempi: “Bullismo” (p. 48). - Approfondimenti tematici (p. 49). – Riferimenti bibliografici (p. 51). 3. LA GROUNDED THEORY 3.1. Le origini della Grounded Theory (p. 53). – 3.2. La costruzione delle teorie (p. 57). – 3.3. Il processo di codifica e di concettualizzazione (p. 61). – Approfondimenti tematici (p. 66). – Riferimenti bibliografici (p. 67). 4. LAVORARE CON ATLAS.TI5 4.1. La barra degli strumenti (p. 69). - 4.2. La preparazione dei documenti (p. 71). - 4.3. Creazione di una unità ermeneutica (p. 72). - 4.4. Codificare un testo (p. 79). - 4.5. Le famiglie e le super famiglie di codici (p. 85). - 4.6. Le query (p. 88). - 4.7. I network - Rappresentazioni di relazioni (p. 93) 5. LAVORARE CON NVIVO7 – ORGANIZZARE E CODIFICARE IL TESTO 5.1. Creare un progetto di lavoro (p. 97). - 5.2. L'organizzazione dei dati: i casi e gli attributi (p. 102). - 5.3. La barra degli strumenti (p. 105). - 5.4. La formattazione del testo (p. 107). - 5.5. La creazione di nodi di codici (p. 108). - 5.6. Ri-organizzare codici e nodi (p. 118). - 5.7. I rapporti di lavoro (p. 124). - 5.8. Creare elementi di lavoro aggiuntivi (p. 125) 6. LAVORARE CON NVIVO7 – INTERROGARE E RAPPRESENTARE IL TESTO 6.1. Le query (p. 129). – 6.2. I modelli (p. 141). 6.3. Le relazioni (p. 145). 7. L’ANALISI QUANTITATIVA DEL LESSICO 7.1. I pionieri della linguistica quantitativa (p. 150). - 7.2. La costruzione dei lessici di frequenza (p. 153). - 7.3. La scuola francese della statistica testuale (p. 154). - 7.4. Estrazione dell'informazione e tecnologie di Text Mining (p. 155). - 7.5. Gli elementi costitutivi del testo: le parole (p. 156). - Approfondimenti tematici (p. 161). - Riferimenti bibliografici (p. 162) 8. LAVORARE CON LEXICO3 8.1. Preparazione del corpus (p. 166). - 8.2. Le chiavi di partizione corpus (p. 168). - 8.3. La barra degli strumenti (p. 170). - 8.4. Frammentazione del corpus e formazione del vocabolario (p. 172). - 8.5. Analisi delle partizioni del corpus (p. 174). - 8.6. Grafico di distribuzione per la partizione (p. 176). - 8.7. Analisi di specificità (p. 177). - Raggruppamenti di forme grafiche (p. 180). - 8.9. Concordanze (p. 182). - 8.10. Cartografia dei paragrafi (p. 185). - 8.11. Altre funzioni e salvataggio del rapporto (p. 186). - Riferimenti bibliografici (p. 187) 9. LAVORARE CON TALTAC2: IL TRATTAMENTO DEL TESTO 9.1. La barra degli strumenti (p. 189). - 9.2. Preparazione del corpus (p. 191). - 9.3. Creazione di una sessione di lavoro (p. 193) - 9.4. Fase di pre-trattamento: normalizzazione (p. 196). - 9.5. Analisi del vocabolario (p. 200). - 9.6. Il riconoscimento delle forme grammaticali (p. 209). - 9.7. La lemmatizzazione (p. 211). - Riferimenti bibliografici (p. 213) 10. LAVORARE CON TALTAC2: L’ANALISI LESSICALE 10.1. Text Data Mining ed esplorazione delle tabelle (p. 215). - 10.2. Estrazione dei segmenti ripetuti e lessicalizzazione (p. 219). - 10.3. Estrazione delle forme specifiche (p. 223). - 10.4. Estrazione delle forme peculiari (p. 227). - 10.5. Confronto con un dizionario tematico: aggettivi positivi e negativi (p. 231). - Riferimenti bibliografici (p. 234) 11. LAVORARE CON TALTAC2: L’ANALISI DEL CONTENUTO 11.1. Il recupero di informazione: le concordanze (p. 238). - 11.2. L'estrazione di informazione per parole chiave (p. 239). - 11.3. Categorizzazione del corpus da regole (p. 241). - 11.4. Esportazione di tabelle e ricostruzione del corpus (p. 243) - Esempi di ricerca (p. 246)

Text Mining

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Author : Ashok N. Srivastava
language : en
Publisher: CRC Press
Release Date : 2009-06-15

Text Mining written by Ashok N. Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-15 with Business & Economics categories.

The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te

Text Mining

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Author : Michael W. Berry
language : en
Publisher: John Wiley & Sons
Release Date : 2010-05-03

Text Mining written by Michael W. Berry and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-03 with Mathematics categories.

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 learning, and natural language processing can collectively capture, classify, and interpret words and their contexts. As suggested in the preface, text mining is needed when “words are not enough.” This book: Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis. Presents a survey of text visualization techniques and looks at the multilingual text classification problem. Discusses the issue of cybercrime associated with chatrooms. Features advances in visual analytics and machine learning along with illustrative examples. Is accompanied by a supporting website featuring datasets. Applied mathematicians, statisticians, practitioners and students in computer science, bioinformatics and engineering will find this book extremely useful.