Approximating Multiple Arrival Streams by Using Aggregation

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Temporal Aggregation over Data Streams Using Multiple Granularities

Temporal aggregation is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem of computing temporal aggregates over data streams. Such aggregates are maintained using multiple levels of temporal granularities: older data is aggregated using coarser granularities while more recent data...

متن کامل

Feature Selection using Multiple Streams

Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes which serve as features may be divided into classes based on their membership in gene families or pathways. When labeling words with senses for word sense disambiguation, features fall into classes including adjacent wor...

متن کامل

Approximating matching size from random streams

We present a streaming algorithm that makes one pass over the edges of an unweighted graph presented in random order, and produces a polylogarithmic approximation to the size of the maximum matching in the graph, while using only polylogarithmic space. Prior to this work the only approximations known were a folklore Õ( p n) approximation with polylogarithmic space in an n vertex graph and a con...

متن کامل

Tight tradeoffs for approximating palindromes in streams

We consider computing the longest palindrome in a text of length n in the streaming model, where the characters arrive one-by-one, and we do not have random access to the input. While computing the answer exactly using sublinear memory is not possible in such a setting, one can still hope for a good approximation guarantee. We focus on the two most natural variants, where we aim for either addi...

متن کامل

Load Shedding using Window Aggregation Queries on Data Streams

The processes of extracting knowledge structures for continuous, rapid records are known as the Data Stream Mining. The main issue in stream mining is handling streams of elements delivered rapidly which makes it infeasible to store everything in active storage. To overcome this problem of handling voluminous data we exposed a novel load shedding system using window based aggregate function of ...

متن کامل

ذخیره 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: Stochastic Models

سال: 2006

ISSN: 1532-6349,1532-4214

DOI: 10.1080/15326340600820398