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Synchronous data flow

by Edward A. Lee, et al. , 1987
"... Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case ..."
Abstract - Cited by 622 (45 self) - Add to MetaCart
of data flow (either atomic or large grain) in which the number of data samples produced or consumed by each node on each invocation is specified a priori. Nodes can be scheduled statically (at compile time) onto single or parallel programmable processors so the run-time overhead usually associated

Beyond Market Baskets: Generalizing Association Rules To Dependence Rules

by Craig Silverstein, SERGEY BRIN , RAJEEV MOTWANI , 1998
"... One of the more well-studied problems in data mining is the search for association rules in market basket data. Association rules are intended to identify patterns of the type: “A customer purchasing item A often also purchases item B. Motivated partly by the goal of generalizing beyond market bask ..."
Abstract - Cited by 634 (6 self) - Add to MetaCart
One of the more well-studied problems in data mining is the search for association rules in market basket data. Association rules are intended to identify patterns of the type: “A customer purchasing item A often also purchases item B. Motivated partly by the goal of generalizing beyond market

MapReduce: Simplified data processing on large clusters.

by Jeffrey Dean , Sanjay Ghemawat - In Proceedings of the Sixth Symposium on Operating System Design and Implementation (OSDI-04), , 2004
"... Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of ..."
Abstract - Cited by 3439 (3 self) - Add to MetaCart
Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details

Attribute-based encryption for fine-grained access control of encrypted data

by Vipul Goyal, Amit Sahai, Omkant Pandey, Brent Waters - In Proc. of ACMCCS’06 , 2006
"... As more sensitive data is shared and stored by third-party sites on the Internet, there will be a need to encrypt data stored at these sites. One drawback of encrypting data, is that it can be selectively shared only at a coarse-grained level (i.e., giving another party your private key). We develop ..."
Abstract - Cited by 522 (23 self) - Add to MetaCart
develop a new cryptosystem for fine-grained sharing of encrypted data that we call Key-Policy Attribute-Based Encryption (KP-ABE). In our cryptosystem, ciphertexts are labeled with sets of attributes and private keys are associated with access structures that control which ciphertexts a user is able

Transactional Memory: Architectural Support for Lock-Free Data Structures

by Maurice Herlihy, J. Eliot B. Moss
"... A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lock-free data structures avoid common problems asso ..."
Abstract - Cited by 1031 (27 self) - Add to MetaCart
A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lock-free data structures avoid common problems

Dynamic Itemset Counting and Implication Rules for Market Basket Data

by Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, Shalom Tsur , 1997
"... We consider the problem of analyzing market-basket data and present several important contributions. First, we present a new algorithm for finding large itemsets which uses fewer passes over the data than classic algorithms, and yet uses fewer candidate itemsets than methods based on sampling. We in ..."
Abstract - Cited by 615 (6 self) - Add to MetaCart
, the problem of deriving associations from data has recently received a great deal of attention. The prob...

Data Preparation for Mining World Wide Web Browsing Patterns

by Robert Cooley, Bamshad Mobasher, Jaideep Srivastava - KNOWLEDGE AND INFORMATION SYSTEMS , 1999
"... The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of tra#c and the size and complexity of Web sites. The complexity of tasks such as Web site design, Web server design, and of simply navigating through a Web site have increased along with this growth. An i ..."
Abstract - Cited by 567 (43 self) - Add to MetaCart
by the proposed methods are used to discover association rules from real world data using the WEBMINER system [15].

Pig Latin: A Not-So-Foreign Language for Data Processing

by Christopher Olston, Benjamin Reed, Utkarsh Srivastava, Ravi Kumar, Andrew Tomkins
"... There is a growing need for ad-hoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively e ..."
Abstract - Cited by 607 (13 self) - Add to MetaCart
expensive at this scale. Besides, many of the people who analyze this data are entrenched procedural programmers, who find the declarative, SQL style to be unnatural. The success of the more procedural map-reduce programming model, and its associated scalable implementations on commodity hardware

Mining Association Rules between Sets of Items in Large Databases

by Rakesh Agrawal, Tomasz Imielinski, Arun Swami - IN: PROCEEDINGS OF THE 1993 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, WASHINGTON DC (USA , 1993
"... We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel esti ..."
Abstract - Cited by 3331 (16 self) - Add to MetaCart
We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel

Genomic control for association studies

by B. Devlin, Kathryn Roeder , 1999
"... A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. ..."
Abstract - Cited by 480 (13 self) - Add to MetaCart
. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with casecontrol data and yet, like family-based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly
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