Mining Text Data

·
· Springer Science & Business Media
電子書
524
頁數
評分和評論未經驗證 瞭解詳情

關於這本電子書

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.

為這本電子書評分

請分享你的寶貴意見。

閱讀資訊

智能手機和平板電腦
請安裝 Android 版iPad/iPhone 版「Google Play 圖書」應用程式。這個應用程式會自動與你的帳戶保持同步,讓你隨時隨地上網或離線閱讀。
手提電腦和電腦
你可以使用電腦的網絡瀏覽器聆聽在 Google Play 上購買的有聲書。
電子書閱讀器及其他裝置
如要在 Kobo 等電子墨水裝置上閱覽書籍,你需要下載檔案並傳輸到你的裝置。請按照說明中心的詳細指示,將檔案傳輸到支援的電子書閱讀器。