書目名稱 | Fundamentals of Predictive Text Mining | 編輯 | Sholom M. Weiss,Nitin Indurkhya,Tong Zhang | 視頻video | http://file.papertrans.cn/351/350483/350483.mp4 | 概述 | Presents a comprehensive, practical and easy-to-read introduction to text mining.Updated and expanded with new content on deep learning, graph models, mining social media, and errors and pitfalls in b | 叢書名稱 | Texts in Computer Science | 圖書封面 |  | 描述 | 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. | 出版日期 | Textbook 2015Latest edition | 關鍵詞 | Document Classification; Information Extraction; Information Retrieval; Machine Learning; Text Mining | 版次 | 2 | doi | https://doi.org/10.1007/978-1-4471-6750-1 | isbn_softcover | 978-1-4471-7113-3 | isbn_ebook | 978-1-4471-6750-1Series ISSN 1868-0941 Series E-ISSN 1868-095X | issn_series | 1868-0941 | copyright | Springer-Verlag London 2015 |
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