a generic local algorithm for mining data streams in large distributed systems

Mining Data Streams: A Review - School of Informatics

Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. The research in data stream mining has gained a high attraction due to the importance of its applications and the increasing generation of streaming information. Applications of data stream analysis can

A Generic Local Algorithm for Mining Data Streams in Large ...

A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems . By Ran Wolff, Kanishka Bhaduri and Hillol Kargupta. Abstract. In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system's functionality such as message ...

A Generic Local Algorithm for Mining Data Streams in Large ...

1 A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Ran Wolff, Kanishka Bhaduri, and Hillol Kargupta Senior Member, IEEE Abstract— In a large network of computers or wireless sensors, fact that the data is static or rapidly changing.

Multi-objective optimization based privacy preserving ...

Jun 22, 2010· Unlike most multi-party privacy-preserving data mining algorithms, this approach works in an asynchronous manner through local interactions and it is highly scalable. It particularly deals with the distributed computation of the sum of a set of numbers stored at different peers in a P2P network in the context of a P2P web mining application.

DBLP: Ran Wolff - vldb.org

Ran Wolff, Kanishka Bhaduri, Hillol Kargupta: A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems. IEEE Trans. Knowl. Data Eng. 21(4): 465-478 (2009) 2008; 21 : Kanishka Bhaduri, Ran Wolff, Chris Giannella, Hillol Kargupta: Distributed Decision-Tree Induction in Peer-to-Peer Systems.

TREE CONFIGURATION GAMES FOR DISTRIBUTED …

TREE CONFIGURATION GAMES FOR DISTRIBUTED STREAM MINING SYSTEMS Hyunggon Park⁄, Deepak S. Turaga+, Olivier Verscheure+ and Mihaela van der Schaar⁄ +IBM T. J. Watson Research Center, Hawthorne, NY, USA ⁄UCLA Electrical Engineering Department, Los Angeles, CA, USA ABSTRACT We consider the problem of configuring classifier trees in dis-

Kanishka Bhaduri - Academia.edu

Kanishka Bhaduri studies Microstructures, Boundaries, and High Temperature. ... Unlike most multi-party privacy-preserving data mining algorithms, this approach works in an asynchronous manner through local interac- tions and therefore, is highly scalable. ... A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems more ...

1A Generic Local Algorithm for Mining Data Streams in ...

BibTeX @MISC{Wolff_1ageneric, author = {Ran Wolff and Kanishka Bhaduri and Hillol Kargupta and Senior Member}, title = {1A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems}, year = {}}

A Generic Local Algorithm for Mining Data Streams in Large ...

A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Article (PDF Available) in IEEE Transactions on Knowledge and Data Engineering 21(4):465 - 478 · …

A Generic Local Algorithm for Mining Data Streams in Large ...

A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Ran Wolff, Kanishka Bhaduri, and Hillol Kargupta Senior Member, IEEE Abstract—In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system's functionality

IEEE 2009 PROJECT DOTNET DATA MINING - calameo.com

IEEE 2009 PROJECT DOTNET DATA MINING @ SBGC ( Chennai, Trichy, Tamilnadu, India ) DDM17 A Survey of Uncertain Data Algorithms and Applications IEEE 2009 View / Download Abstract DDM18 Adapted One-versus-All Decision Trees for Data Stream Classification IEEE 2009 View / Download Abstract DDM19 Bayes Vector Quantizer for Class-Imbalance Problem ...

Big Data, Stream Processing & Algorithms - SlideServe

Jul 13, 2014· Download Presentation Big Data, Stream Processing & Algorithms An Image/Link below is provided (as is) to download presentation. Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.

1A Generic Local Algorithm for Mining Data Streams in ...

1A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems . By Ran Wolff, Kanishka Bhaduri, Hillol Kargupta and Senior Member. Abstract. Abstract — In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. ... k-means clustering in ...

Generic local algorithm for mining data streams - [PDF ...

1. 1 A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Ran Wolff, Kanishka Bhaduri, and Hillol Kargupta Senior Member, IEEE Abstract In a

A Fast Online Learning Algorithm for Distributed Mining of ...

such distributed data mining systems also come with signif-icant design challenges that are the focal point of this work. (1) Limited data access. In distributed data mining, each local learner has only limited access to the entire dataset [3]. There are two types of data partition [4]. In the instance-

CluSandra: A Framework and Algorithm for Data Stream ...

CluSandra: A Framework and Algorithm for Data Stream Cluster Analysis Jose R. Fernandez ... recommendation systems, click stream analysis) and ... type of data mining problem. Large multi-dimensional datasets are typically not uniformly distributed. By identifying the

A Generic Local Algorithm for Mining Data Streams in Large ...

large distributed system generic local algorithm mining data stream global state large network dynamic scenario decision tree thorough experimental analysis wireless sensor information retrieval communication cost global data mining model step approach message routing efficient local algorithm data mining model k-means clustering wide class ...

Monitoring Threshold Functions over Distributed Data ...

Monitoring data streams in a distributed system has attracted considerable interest in recent years. The task of feature selection (e.g., by monitoring the information gain of various features) requires a very high communication overhead when addressed using straightforward centralized algorithms. While most of the existing algorithms deal with monitoring simple aggregated values such as ...

Collective Sequential Pattern Mining in Distributed ...

R.Wolff, K. Bhaduri, and H. Kargupta: A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems. IEEE Transactions on Knowledge and Data Engineering Vol. 21 (2009), pp. 465-478. [15] E.T. Wang, and A.L. Chen: Mining Frequent Itemsets over Distributed Data Streams by Continuously Maintaining a Global Synopsis.

Generic local algorithm for mining data streams - SlideShare

Sep 03, 2012· Generic local algorithm for mining data streams 1. 1 A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Ran Wolff, Kanishka Bhaduri, and Hillol Kargupta Senior Member, IEEE Abstract— In a large network of computers or wireless sensors, fact that the data is static or rapidly changing.

A Generic Local Algorithm for Mining Data Streams in Large ...

A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems Abstract: In a large network of computers or wireless sensors, each of the components (henceforth, peers) has some data about the global state of the system. Much of the system's functionality such as message routing, information retrieval and load sharing relies on ...

Data Stream Mining | SpringerLink

H. Kargupta, Ruchita Bhargava, Kun Liu, Michael Powers, Patrick Blair, Bushra, James Dull, Kakali Sarkar, Martin Klein, Mitesh Vasa, and David Handy, VEDAS: A Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring, Proceedings of SIAM International Conference on Data Mining 2004. Google Scholar

A cost effective algorithm for outlier detection in ...

Request PDF on ResearchGate | A cost effective algorithm for outlier detection in distributed systems | Sensor networks, peer-to-peer systems, and other large distributed systems, produce, store ...

APPROVAL SHEET - Inspiring Innovation

A Generic Local Algorithm with Applications for Data Mining in Large Distributed Systems. IEEE Transactions on Knowledge and Data Engineering (TKDE) (submitted). 2007. Book Chapter 1. K. Bhaduri, K. Das, K. SivaKumar, H. Kargupta, R. Wolff, R. Chen. Algorithms for Distributed Data Stream Mining. A chapter in Data Streams: Models and

Ran Wolff | University of Haifa - Academia.edu

Unlike the traditional centralized systems, DDM offers a fundamentally distributed solution to analyze data without necessarily demanding collection of the data to a single central site. This chapter presents an introduction to distributed data mining for continuous streams.

A Generic Local Algorithm for Mining Data Streams in Large ...

A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems ... distributed processing k-means clustering data stream mining large distributed systems generic local algorithm message routing information retrieval load sharing ... IEEE Transactions on Knowledge and Data Engineering. Rocznik. 2009.

Context-Adaptive Big Data Stream Mining - Online …

Context-Adaptive Big Data Stream Mining - Online Appendix Cem Tekin*, Member, IEEE, ... Abstract—Emerging stream mining applications require clas-sification of large data streams generated by single or multi-ple heterogeneous sources. Different classifiers can be used to ... learner distributed data mining systems where each learner has

SEABIRDS GROUP & CO - webforfinalyears.weebly.com

a generic local algorithm for mining data streams in large distributed systems ieee 2009 jdm52 a pure nash equilibrium-based game theoretical method for data replication across multiple servers ieee 2009 jdm53 histogram-based global load balancing in structured peer-to-peer systems ieee 2009 jdm54 multiscale representations for fast pattern ...