03851nam a22005295i 4500 978-981-13-6347-4 DE-He213 20210619065623.0 cr nn 008mamaa 190318s2019 si | s |||| 0|eng d 9789811363474 978-981-13-6347-4 10.1007/978-981-13-6347-4 doi QA76.9.B45 UN bicssc COM021000 bisacsh UN thema 005.7 23 Data, Engineering and Applications [electronic resource] : Volume 1 / edited by Rajesh Kumar Shukla, Jitendra Agrawal, Sanjeev Sharma, Geetam Singh Tomer. 1st ed. 2019. Singapore : Springer Singapore : Imprint: Springer, 2019. VIII, 191 p. 89 illus., 60 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda A review of Recommender System and related Dimensions -- Collaborative Filtering Techniques in Recommendation Systems -- Predicting Users’ Interest through ELM basedCollaborative Filtering -- Application of Community Detection Technique in Text Mining -- Sentiment Analysis on WhatsApp Group Chat using R -- A Recent Survey on Information Hiding Techniques -- Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization -- Identification and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks -- Sentiment Prediction of Facebook Status updates of youngsters -- Logistic Regression for the Diagnosis of Cervical Cancer -- Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm -- Personality Trait Identification for Written Texts Using MLNB -- Deep neural network compression via knowledge distillation for embedded vision applications. This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications. . Big data. Data mining. Artificial intelligence. Big Data. https://scigraph.springernature.com/ontologies/product-market-codes/I29120 Data Mining and Knowledge Discovery. https://scigraph.springernature.com/ontologies/product-market-codes/I18030 Artificial Intelligence. https://scigraph.springernature.com/ontologies/product-market-codes/I21000 Shukla, Rajesh Kumar. editor. edt http://id.loc.gov/vocabulary/relators/edt Agrawal, Jitendra. editor. edt http://id.loc.gov/vocabulary/relators/edt Sharma, Sanjeev. editor. edt http://id.loc.gov/vocabulary/relators/edt Singh Tomer, Geetam. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) Springer Nature eBook Printed edition: 9789811363467 Printed edition: 9789811363481 Printed edition: 9789811363498 https://doi.org/10.1007/978-981-13-6347-4 ZDB-2-SCS ZDB-2-SXCS Computer Science (SpringerNature-11645) Computer Science (R0) (SpringerNature-43710)