The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Abstract Methods for Approximate Query Processing (AQP) are essential for dealing with
massive data. They are often the only means of providing interactive response times when …

We introduce a new sublinear space data structure—the count-min sketch—for summarizing
data streams. Our sketch allows fundamental queries in data stream summarization such as …

In the data stream scenario, input arrives very rapidly and there is limited memory to store
the input. Algorithms have to work with one or few passes over the data, space less than …

In many real-world applications, information such as web click data, stock ticker data, sensor
network data, phone call records, and traffic monitoring data appear in the form of data …

Compressed sensing is a new concept in signal processing where one seeks to minimize
the number of measurements to be taken from signals while still retaining the information …

The data stream model has recently attracted attention for its applicability to numerous types
of data, including telephone records, Web documents, and clickstreams. For analysis of such …

Publisher Summary The history of histograms is long and rich, full of detailed information in
every step. It includes the course of histograms in different scientific fields, the successes …

Most database management systems maintain statistics on the underlying relation. One of
the important statistics is that of the “hot items” in the relation: those that appear many times …

The frequent items problem is to process a stream of items and find all items occurring more
than a given fraction of the time. It is one of the most heavily studied problems in data stream …