… card or phone result in automated data storage, which brings us to a fairly new topic called
data streams. This volume covers mining aspects of data streams comprehensively: each …

… In addition to data collection, we show that Ken is well suited to … data collection mechanism
that uses a data-centric approach to choose how to disseminate queries and gather data. …

… that addresses big data classification problems. Therefore, the goal of this book is to present
some of the machine learning models and algorithms, and discuss them with examples. …

… access to personal data poses a threat to individual privacy. In this thesis, we provide
models and algorithms for protecting the privacy of individuals in such large data sets while still …

… -anonymity which require the knowledge of other records in the data. Therefore, the
randomization method can be implemented at data collection time, and does not require the use of a …

… Finally, we are interested on data collection mechanisms as they make … data among moving
vehicles in VANETs. The aim behind using the learning technique is to make the collecting …

… scheduling algorithms for data collection in sensor networks. We first classify the algorithms
… , and comment on the pros and cons of alternative models or approaches that can be used. …

… Considering this overlap, the data collection tools for these … used for data collection and
post data collection analysis for … List of Algorithms used for multi-sensor data modelling …

… of indirect data collection methodologies have led to the proliferation of uncertain data. Such
… We will explore the various models utilized for uncertain data representation. In the field of …

… data collection from a data management point of view. Data collection largely consists of data
acquisition, data … existing data or models when acquiring and labeling new data is not the …