000			02040nam a22002297a 4500
008			230926b2013 |||||||| |||| 00| 0 eng d
020			_a9781466510968
082			_a006.312 AMI-A
100			_aAmin, Anang Hudaya Muhamad
245			_aInternet-scale pattern recognition : _bnew techniques for voluminous data sets and data clouds / _cAnang Hudaya Muhamad Amin, Asad I. Khan and Benny B. Nasution
260			_aBoca Raton _bCRC Press _c2013
300			_a179 p.
500			_aFor machine intelligence applications to work successfully, machines must perform reliably under variations of data and must be able to keep up with data streams. Internet-Scale Pattern Recognition: New Techniques for Voluminous Data Sets and Data Clouds unveils computational models that address performance and scalability to achieve higher levels of reliability. It explores different ways of implementing pattern recognition using machine intelligence. Based on the authors’ research from the past 10 years, the text draws on concepts from pattern recognition, parallel processing, distributed systems, and data networks. It describes fundamental research on the scalability and performance of pattern recognition, addressing issues with existing pattern recognition schemes for Internet-scale data deployment. The authors review numerous approaches and introduce possible solutions to the scalability problem. By presenting the concise body of knowledge required for reliable and scalable pattern recognition, this book shortens the learning curve and gives you valuable insight to make further innovations. It offers an extendable template for Internet-scale pattern recognition applications as well as guidance on the programming of large networks of devices.
650			_aPattern recognition systems
650			_aWeb usage mining
650			_aData mining
650			_aMathematical statistics--Data processing
650			_aMathematical statistics
650			_aBig data
700			_aKhan, Asad I.
700			_aNasution, Benny B.
999			_c90935 _d90935