Experiential Sampling on Multiple Data Streams
نویسندگان
چکیده
منابع مشابه
Succinct Sampling on Streams
A streaming model is one where data items arrive over long period of time, either one item at a time or in bursts. Typical tasks include computing various statistics over a sliding window of some fixed time horizon. What makes the streaming model interesting is that as the time progresses, old items expire and new ones arrive. One of the simplest and most central tasks in this model is sampling...
متن کاملKSample: Dynamic Sampling Over Unbounded Data Streams
Data sampling over data streams is common practice to allow the analysis of data in real-time. However, sampling over data streams becomes complex when the stream does not fit in memory, and worse yet, when the length of the stream is unknown. A well-known technique for sampling data streams is the Reservoir Sampling. It requires a fixed-size reservoir that corresponds to the resulting sample s...
متن کاملWeighted Random Sampling over Data Streams
In this work, we present a comprehensive treatment of weighted random sampling (WRS) over data streams. More precisely, we examine two natural interpretations of the item weights, describe an existing algorithm for each case ([2,4]), discuss sampling with and without replacement and show adaptations of the algorithms for several WRS problems and evolving data streams.
متن کاملWeighted Sampling Without Replacement from Data Streams
Weighted sampling without replacement has proved to be a very important tool in designing new algorithms. Efraimidis and Spirakis (IPL 2006) presented an algorithm for weighted sampling without replacement from data streams. Their algorithm works under the assumption of precise computations over the interval [0, 1]. Cohen and Kaplan (VLDB 2008) used similar methods for their bottom-k sketches. ...
متن کاملStratified Reservoir Sampling over Heterogeneous Data Streams
Reservoir sampling is a well-known technique for random sampling over data streams. In many streaming applications, however, an input stream may be naturally heterogeneous, i.e., composed of substreams whose statistical properties may also vary considerably. For this class of applications, the conventional reservoir sampling technique does not guarantee a statistically sufficient number of tupl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Multimedia
سال: 2006
ISSN: 1520-9210
DOI: 10.1109/tmm.2006.879875