Screen LibraryAnomaly detection : techniques and applications /
"When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identifica...
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| Group Author: | ; ; ; |
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| Published: |
Nova Science Publishers, Inc.,
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| Publisher Address: | New York, NY : |
| Publication Dates: | [2021] |
| Literature type: | Book |
| Language: | English |
| Series: |
Computer science, technology and applications
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| Subjects: | |
| Summary: |
"When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspicion by differing significantly from the majority of data is called anomaly detection. With progress in technology and the widespread use of data for the purpose of business, spam faced by individuals and companies is increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, machine learning, artificial intelligence, deep learning, image processing, cloud computing, audio processing, video processing, VoIP, data science, wireless sensor, etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data. This book will mainly target researchers and higher graduate learners in computer science and data science"-- |
| Carrier Form: | viii, 177 pages : illustrations ; 23 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9781536192643 1536192643 |
| Index Number: | TK5105 |
| CLC: | TP393.08 |
| Call Number: | TP393.08/A615 |
| Contents: | Secured and automated key establishment and data forwarding scheme for the Internet of Things / N. V. Kousik, R. Arshath Raja, N. Yuvaraj and S. Anbu Chelian, Associate Professor, School of Computing and Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India, et al. -- A study of enhanced anomaly detection techniques using evolutionary-based optimization for improved detection accuracy / Vidhya Sathish, PhD, and Sheik Abdul Khader, PhD, Assistant Professor, Shri Krishnaswamy College for Women, Chennai, et al. -- Anomaly detection and applications / Huichen Shu, PhD, Clausthal University of Technology, Germany. |