Abstract:
Frequent pattern mining is a heavily researched area in the field of data mining
with wide range of applications. One of them is to use frequent pattern discovery methods
in Web log data. Discovering hidden information from Web log data is called Web usage
mining. The aim of discovering frequent patterns in Web log data is to obtain information
about the navigational behavior of the users. This can be used for advertising purposes, for
creating dynamic user profiles etc. In this paper three pattern mining approaches are
....etc

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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 of ....etc

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Abstract.
The problem of estimating the kth frequency moment Fk, for any
non-negative integral value of k, over a data stream by looking at the items exactly
once as they arrive, was considered in a seminal paper by Alon, Matias and
Szegedy . They present a sampling based algorithm to estimate Fk where,
k 2, using space O(n1 1/k)). Coppersmith and Kumar and , using
different methods, present algorithms for estimating Fk with space complexity
O
(n1 1/(k 1)). In this paper, we present an algorithm for estimati ....etc

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Abstract.
We present a randomized procedure named Hierarchical Sampling from Sketches (HSS) that can be used for estimating a class of functions over the frequency vector f of update streams of the form (S) = Pn i=1 ( fi ).We illustrate this by applying the HSS technique to design nearly space-optimal algorithms for estimating the pth moment of the frequency vector, for real p _ 2 and for estimating the entropy of a data stream. 3
1 Introduction
A variety of applications in diverse areas, such as, networking, database syst ....etc

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A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets-IEE 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. Rec ....etc

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there are new patterns of disease and pest attack with changes in rainfall patterns

As climate change alters environmental conditions, the incidence and global patterns of human diseases are changing. These modifications to disease profiles and the effects upon human pharmaceutical usage are discussed. Climate-related environmental changes are associated with a rise in the incidence of chronic diseases already prevalent in the Northern Hemisphere, for example, cardiovascular disease and mental illness, leading to greater use of associated heav ....etc

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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 and ....etc

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Abstract.
We present an algorithm for estimating entropy of data streams consisting of insertion and deletion operations using O(1) space.
1 1 Introduction
Recently, there has been an emergence of monitoring applications in diverse areas, including, network traf_c monitoring, network topology monitoring, sensor networks, _nancial market monitoring, web-log monitoring, etc.. In these applications, data is generated rapidly and continuously, and must be analyzed very ef_ciently, in realtime, to identify large trends, anomalies ....etc

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An Efficient Algorithm for Mining Frequent Patterns ....etc

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Efficient storage and querying of sequential patterns in database systems
Presented By:
Alexandros Nanopoulosa, , Maciej Zakrzewiczb, , Tadeusz Morzyb, and Yannis Manolopoulos

Abstract
The number of patterns discovered by data mining can become tremendous, in some cases exceeding the size of the original database. Therefore, there is a requirement for querying previously generated mining results or for querying the database against discovered patters. In this paper, we focus on developing methods for the storage and querying of large ....etc

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