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Title: Frequent Pattern Mining in Web Log Data
Page Link: Frequent Pattern Mining in Web Log Data -
Posted By: abypallu
Created at: Thursday 17th of August 2017 05:16:14 AM
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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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Title: IMine index support for frequent item set mining
Page Link: IMine index support for frequent item set mining -
Posted By: swarna
Created at: Thursday 17th of August 2017 05:39:42 AM
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hello..
i am Rupa devi pursuing b-tech final year (IT branch) from a JNTU affliated college and i would request you to post or mail the document related to the project title as mentioned.
and my problem regarding this project is that i am not able to understand the algorithm present in it and how i need to implement it.I know java programming language and i am doing my project haf way through .
so please post the related information about it .

Abstract :This paper presents the IMine index, a general and compact structure which provides ti ....etc

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Title: An Efficient Algorithm for Mining Frequent Patterns
Page Link: An Efficient Algorithm for Mining Frequent Patterns -
Posted By: balaje
Created at: Friday 06th of October 2017 02:46:24 PM
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An Efficient Algorithm for Mining Frequent Patterns ....etc

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Title: A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Site
Page Link: A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Site -
Posted By: doomz
Created at: Thursday 17th of August 2017 05:07:01 AM
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A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Site-IEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 2,

vb.net

Abstract I

n this paper, we present a complete framework and findings in mining Web usage patterns from Web log files of a real Web site that has all the challenging aspects of real-life Web usage mining, including evolving user profiles and external data describing an ontology of the Web content. Even though the Web site under study is part of a nonprofit organization that ....etc

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Title: pattern detection using web log data
Page Link: pattern detection using web log data -
Posted By: nazeem
Created at: Thursday 05th of October 2017 04:17:06 AM
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I want to know the full details about Pattern Detection Using Weblog Data because i have a project in this title.. ....etc

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Title: Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analy
Page Link: Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analy -
Posted By: ajitsuna
Created at: Thursday 17th of August 2017 05:29:38 AM
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The Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analysis

With the rapid development of computer information technology, a new data model-the stream data emerged. The stream data is coming continuously, quickly, changing with time, and may be unpredictable and unlimited in the way. The emergence of stream data has brought new challenges from the nature ofthe data applied to static database technology and data mining technology. At present, the stream data has been widely used in telecommunications, financial ....etc

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Title: effective pattern discovery for text mining data flow diagram
Page Link: effective pattern discovery for text mining data flow diagram -
Posted By: mrinal
Created at: Thursday 17th of August 2017 06:39:23 AM
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sir can you plz send the design process for effective pattern discovery for text mining
ASAP ....etc

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Title: Clustering and Sequential Pattern Mining of Online Collaborative Learning Data
Page Link: Clustering and Sequential Pattern Mining of Online Collaborative Learning Data -
Posted By: balaji_satish
Created at: Thursday 17th of August 2017 06:49:02 AM
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Clustering and Sequential Pattern Mining of Online Collaborative Learning Data

Abstract:
Group work is widespread in education. The growing use of online tools supporting group work generates huge amounts of data. We aim to exploit this data to support mirroring: presenting useful high-level views of information about the group, together with desired patterns characterizing the behavior of strong groups. The goal is to enable the groups and their facilitators to see relevant aspects of the group s ....etc

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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: arya spartan
Created at: Thursday 17th of August 2017 05:48:47 AM
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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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Title: INCREMENTAL MINING USING FREQUENT PATTERN TREE
Page Link: INCREMENTAL MINING USING FREQUENT PATTERN TREE -
Posted By: pankusoft
Created at: Thursday 05th of October 2017 03:21:54 AM
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Abstract:

Data mining refers to extracting or mining knowledge from large amount of data. It helps in discovering the frequent patterns. This knowledge can be help in making business decisions conventional data mining techniques were proposed to be in efficient, the source of data is incremental in nature and also they need to be re executed every time which in turn multiple database scans.

In this paper, we propose a novel data structure called CATS Tree to suit for continuously growing data sets, based on association rule mining with in ....etc

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