東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Advanced applications of NLP and deep learning in social media data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced applications of NLP and deep learning in social media data/ Ahmed A. Abd El-Latif, Mudasir Ahman Wani, and Mohammed El-Affendi.
其他作者:	Abd El-Latif, Ahmed A.,
出版者:	Hershey, Pennsylvania :IGI Global, : 2023.,
面頁冊數:	1 online resource (303 p.)
內容註:	Chapter 1. A comprehensive study to detect social spam campaigns -- Chapter 2. ARIMA modeling and forecasting of COVID-19 second wave in the 10 most affected states of India -- Chapter 3. Clustering methods and tools to handle high-dimensional social media text data -- Chapter 4. Community detection algorithms: a critical review -- Chapter 5. Emotion recognition from text using multi-head attention-based bidirectional long short-term memory architecture using multi-level classification -- Chapter 6. Learning from small samples in the age of big data -- Chapter 7. LSTM network: a deep learning approach and applications -- Chapter 8. Machine learning-based prediction of users' involvement on social media -- Chapter 9. NLP techniques and challenges to process social media data -- Chapter 10. Trolling, cyber-stalking, cyber-bullying, and identity theft in OSNs: methods, issues, and challenges -- Chapter 11. Uncertainty quantification in advanced machine learning approaches.
標題:	Natural language processing (Computer science) -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-6909-5
ISBN:	9781668469118 (electronic bk.)

Advanced applications of NLP and deep learning in social media data
Advanced applications of NLP and deep learning in social media data[electronic resource] /Ahmed A. Abd El-Latif, Mudasir Ahman Wani, and Mohammed El-Affendi. - Hershey, Pennsylvania :IGI Global,2023. - 1 online resource (303 p.)

Includes bibliographical references and index.

Chapter 1. A comprehensive study to detect social spam campaigns -- Chapter 2. ARIMA modeling and forecasting of COVID-19 second wave in the 10 most affected states of India -- Chapter 3. Clustering methods and tools to handle high-dimensional social media text data -- Chapter 4. Community detection algorithms: a critical review -- Chapter 5. Emotion recognition from text using multi-head attention-based bidirectional long short-term memory architecture using multi-level classification -- Chapter 6. Learning from small samples in the age of big data -- Chapter 7. LSTM network: a deep learning approach and applications -- Chapter 8. Machine learning-based prediction of users' involvement on social media -- Chapter 9. NLP techniques and challenges to process social media data -- Chapter 10. Trolling, cyber-stalking, cyber-bullying, and identity theft in OSNs: methods, issues, and challenges -- Chapter 11. Uncertainty quantification in advanced machine learning approaches.

"The primary objective of this book is to build a better and safer social media space by making human language available on different social media platforms intelligible for machines with the blessings of AI. This book bridges the gap between Natural Language Processing (NLP), Advanced Machine(AML) and Deep Learning (DL), and Online Social Media. This book connects various interdisciplinary domains related to Natural Language Understanding, Deep machine Leaning Technology and will be highly beneficial for the students, researchers, and academicians working in this area as this book will cover state-of-the-art technologies around NLP and DML techniques and their role in Social Media Data Analysis. Furthermore, the OSN service providers will take the advantage of this book to update, modify and make better social platforms for its users. Psychiatrists and clinicians will also be beneficial as this book's main focus are to analyze the user behavior in Online Social networks which play a key ingredient in several psychological tests"--

ISBN: 9781668469118 (electronic bk.)Subjects--Topical Terms:

565309
Natural language processing (Computer science)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA76.9.N38 / A38 2023e

Dewey Class. No.: 006.3/5

Advanced applications of NLP and deep learning in social media data
LDR:02991nmm a2200265 a 4500 001 2339092
006 m d
007 cr nn muauu
008 240607s2023 pau fob 001 0 eng d
020 $a 9781668469118 (electronic bk.)
020 $a 166846909X
020 $a 9781668469095
035 $a (CaBNVSL)slc00004516
035 $a (OCoLC)1382729866
035 $a 00304800
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
041 0 $a eng
050 4 $a QA76.9.N38 $b A38 2023e
082 0 4 $a 006.3/5 $2 23
245 0 0 $a Advanced applications of NLP and deep learning in social media data $h [electronic resource] / $c Ahmed A. Abd El-Latif, Mudasir Ahman Wani, and Mohammed El-Affendi.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2023.
300 $a 1 online resource (303 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. A comprehensive study to detect social spam campaigns -- Chapter 2. ARIMA modeling and forecasting of COVID-19 second wave in the 10 most affected states of India -- Chapter 3. Clustering methods and tools to handle high-dimensional social media text data -- Chapter 4. Community detection algorithms: a critical review -- Chapter 5. Emotion recognition from text using multi-head attention-based bidirectional long short-term memory architecture using multi-level classification -- Chapter 6. Learning from small samples in the age of big data -- Chapter 7. LSTM network: a deep learning approach and applications -- Chapter 8. Machine learning-based prediction of users' involvement on social media -- Chapter 9. NLP techniques and challenges to process social media data -- Chapter 10. Trolling, cyber-stalking, cyber-bullying, and identity theft in OSNs: methods, issues, and challenges -- Chapter 11. Uncertainty quantification in advanced machine learning approaches.
520 $a "The primary objective of this book is to build a better and safer social media space by making human language available on different social media platforms intelligible for machines with the blessings of AI. This book bridges the gap between Natural Language Processing (NLP), Advanced Machine(AML) and Deep Learning (DL), and Online Social Media. This book connects various interdisciplinary domains related to Natural Language Understanding, Deep machine Leaning Technology and will be highly beneficial for the students, researchers, and academicians working in this area as this book will cover state-of-the-art technologies around NLP and DML techniques and their role in Social Media Data Analysis. Furthermore, the OSN service providers will take the advantage of this book to update, modify and make better social platforms for its users. Psychiatrists and clinicians will also be beneficial as this book's main focus are to analyze the user behavior in Online Social networks which play a key ingredient in several psychological tests"-- $c Provided by publisher.
650 0 $a Natural language processing (Computer science) $3 565309
650 0 $a Deep learning (Machine learning) $3 3538509
650 0 $a Semantic computing. $3 1067496
650 0 $a Sentiment analysis. $2 lcstt $3 3266790
650 0 $a Web usage mining. $3 543585
650 0 $a Social media. $3 786190
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Abd El-Latif, Ahmed A., $d 1984-. $3 3675604
700 1 $a Wani, Mudasir Ahman, $d 1987-. $3 3675605
700 1 $a El-Affendi, Mohammed, $d 1971-. $3 3675606
710 2 $a IGI Global. $3 1361470
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-6909-5