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Title: all uml diagrams for Effective Pattern Discovery for Text Mining
Page Link: all uml diagrams for Effective Pattern Discovery for Text Mining -
Posted By:
Created at: Thursday 21st of March 2013 10:48:07 PM
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can i have all uml diagrams for Effective Pattern Discovery for Text Mining.
Abstract
Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase)-based approaches shoul ....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: rupadevi
Created at: Wednesday 09th of February 2011 03:38:38 PM
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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 provi ....etc

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Title: Frequent Pattern Mining in Web Log Data
Page Link: Frequent Pattern Mining in Web Log Data -
Posted By: smart paper boy
Created at: Thursday 21st of July 2011 02:52:48 PM
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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: 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: INCREMENTAL MINING USING FREQUENT PATTERN TREE
Page Link: INCREMENTAL MINING USING FREQUENT PATTERN TREE -
Posted By: project topics
Created at: Monday 12th of April 2010 11:33:19 PM
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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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Title: IMine index support for frequent item set mining
Page Link: IMine index support for frequent item set mining -
Posted By: rupadevi
Created at: Wednesday 09th of February 2011 03:38:38 PM
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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 provi ....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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An Efficient Algorithm for Mining Frequent Patterns ....etc

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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 a framework for personal mobile commerce pattern mining and prediction
Page Link: uml diagrams for a framework for personal mobile commerce pattern mining and prediction -
Posted By:
Created at: Tuesday 15th of January 2013 12:29:28 PM
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uml diagrams for a framework for personal mobile commerce pattern mining and prediction ....etc

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Title: uml diagrams of efficient relevance feedback for content based image retrieval by mining user navigation patterns
Page Link: uml diagrams of efficient relevance feedback for content based image retrieval by mining user navigation patterns -
Posted By:
Created at: Thursday 24th of January 2013 04:50:26 PM
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