Emerging Technologies in Data Mining and Information Security

Proceedings of IEMIS 2018, Volume 2
 Paperback
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9789811314971
Veröffentl:
2018
Einband:
Paperback
Erscheinungsdatum:
03.09.2018
Seiten:
916
Autor:
Ajith Abraham
Gewicht:
1358 g
Format:
235x155x49 mm
Serie:
813, Advances in Intelligent Systems and Computing
Sprache:
Englisch
Beschreibung:

The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23¿25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.
Comprises original research work by academics, scientists, and research scholars as well as professionals, decision makers, and industrial practitioners
The Study of Sentimental State of Human from Tweet Text.- Data Analytic Techniques with Hardware Based Encryption for High Profile Dataset.- Exploring Student Migration in Rural Region of Bangladesh.- Analysis on Lightning News And Correlation With Lightning Imaging Sensor (LIS) Data.- Design of Business Canvas Model for Social Media.- EEG Signal Analysis Using Different Clustering Techniques.- Viable Crop Prediction Scenario in Big Data Using a Novel Approach.- A Graph Based Approach on Extractive Summarization.- Promises and Challenges of Big Data in a Data Driven World.- A Proposed Approach for Improving Hadoop Performance For Handling Small Files.- Identification of the Recurrence of Breast Cancer by Discriminant Analysis.- Spam Detection in SMS based on Feature Selection Techniques.- Analysis and Design of an Efficient Temporal Data Mining Model for the Indian Stock Market.- Community Detection Methods in Social Network Analysis.- A Comparative Study on Cluster Analysis of Micro-Blogging Data.

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