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Title: Online mining maximal frequent itemsets over the data stream
Page Link: Online mining maximal frequent itemsets over the data stream -
Posted By: seminar class
Created at: Monday 28th of March 2011 07:03:26 PM
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DESCRIPTION:
A data stream is a massive, open-ended sequence of data elements continuously generated at a rapid rate. Mining data streams is more difficult than mining static databases because the huge, high-speed and continuous characteristics of streaming data. In this paper, we propose a new one-pass algorithm called DSM-MFI (stands for Data Stream Mining for Maximal Frequent Itemsets), which mines the set of all maximal frequent itemsets in landmark windows over data streams.
The proposed algorithm DSM-MFI ....etc

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Title: uml diagrams for vast vertical mining of sequential generator patterns
Page Link: uml diagrams for vast vertical mining of sequential generator patterns -
Posted By:
Created at: Saturday 22nd of April 2017 08:41:22 PM
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Title: An Efficient Algorithm for Mining Frequent Patterns full report
Page Link: An Efficient Algorithm for Mining Frequent Patterns full report -
Posted By: project topics
Created at: Monday 05th of April 2010 10:50:32 PM
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An Efficient Algorithm for Mining Frequent Patterns
Abstract:
Mining frequent patterns are one of the most important research topics in data mining. The function is to mine the transactional data which describes the behavior of the transaction. In an online business or in an online shopping the customers can purchase items together. Frequent patterns are patterns such as item sets, subsequences or substructures that appear in a data set frequently. Many efficient algorithms were developed based on the data structure a ....etc

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Title: new patterns of diseases and pest attacks with changes in rainfall patterns
Page Link: new patterns of diseases and pest attacks with changes in rainfall patterns -
Posted By:
Created at: Friday 22nd of December 2017 02:56:09 PM
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Title: PBFMCSP Prefix Based Fast Mining of Closed Sequential Patterns
Page Link: PBFMCSP Prefix Based Fast Mining of Closed Sequential Patterns -
Posted By: seminar class
Created at: Tuesday 15th of March 2011 06:50:30 PM
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Abstract -
In recent years, mining of sequential patterns has been studied extensively in various domains. Most of the existing algorithms find patterns in transactional databases. This paper proposes a novel algorithm to mine closed sequential patterns using an inverted matrix and prefix based sequence element matrix. Inverted matrix minimizes the search space for discovering various sequential patterns of different items. We use a prefix based sequence element matrix to minimize the scans required at levels k and ....etc

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Title: An Efficient Algorithm for Mining Frequent Patterns
Page Link: An Efficient Algorithm for Mining Frequent Patterns -
Posted By: sivakesava574
Created at: Friday 20th of January 2012 03:22:33 PM
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Title: there are new patterns of disease and pest attack with changes in rainfall patterns
Page Link: there are new patterns of disease and pest attack with changes in rainfall patterns -
Posted By:
Created at: Thursday 12th of June 2014 06:13:41 AM
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Title: SPEED Mining Maximal Sequential Patterns over Data Streams
Page Link: SPEED Mining Maximal Sequential Patterns over Data Streams -
Posted By: seminar class
Created at: Monday 14th of February 2011 12:31:32 PM
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presented by:
Chedy Ra¨ıssi,Pascal Poncelet,Maguelonne Teisseire

ABSTRACT
Many recent real-world applications, such as network traf-_c monitoring, intrusion detection systems, sensor networkdata analysis, click stream mining and dynamic tracing of_nancial transactions, call for studying a new kind of data.Called stream data, this model is, in fact, a continuous, potentiallyin_nite ow of information as opposed to _nite,statically stored data sets extensively studied by researchersof the data mining community. An important appl ....etc

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Title: Finding frequent items over general update streams
Page Link: Finding frequent items over general update streams -
Posted By: smart paper boy
Created at: Friday 12th of August 2011 02:06:24 PM
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Abstract.
We present novel space and time-efficient algorithms for finding frequent items over general update streams. Our algorithms are based on a novel adaptation of the popular dyadic intervals method for finding frequent items. The algorithms improve upon existing algorithms in both theory and practice.
1 Introduction
There is a growing class of applications in areas of business and scientific data processing that continuously monitor large volumes of rapidly arriving data for detecting user-programmed scenarios, some o ....etc

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Title: A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets
Page Link: A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets -
Posted By: project topics
Created at: Monday 02nd of May 2011 12:55:28 PM
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A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets-IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 4,-java

Abstract—
+
Given a large spatio-temporal database of events, where each event consists of the fields event ID, time, location, and event type, mining spatio-temporal sequential patterns identifies significant event-type sequences. Such spatio-temporal sequential patterns are crucial to the investigation of spatial and temporal evolutions of phenomena in many application domains. R ....etc

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