Web Page Prediction by Clustering and Integrated Distance Measure

Poornalatha, G; Raghavendra, Prakash S.

doi:10.1109/asonam.2012.231

Cited by 6 publications

(5 citation statements)

References 16 publications

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“…We experimented the size of initial caches with 5 different sizes (determined as the percentage of the testing data), i.e. 5%, 10%, 15%, 20%, and 25% of the total of the testing data [7]. Table demonstrates that results of the experiment by varying the size of a cache.…”

Section: Evaluation and Resultsmentioning

confidence: 99%

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Proxy Server Systems Improvement Using Frequent Itemset Pattern-Based Techniques

Butkote

Phuboon-op²,

Chomphuwiset

2014

Proceedings of the 2nd International Conference on Intelligent Systems and Image Processing 2014

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In the Internet, proxy servers are tools that are used to facilitate clients for accessing websites and save network bandwidth. Basically, proxy servers uses cache to stored visited sites in order to deliver faster web accesses to users, without requesting to external target servers. With the limitation of cache size, however, a number of techniques have been proposed to potentially increase the performance of cache replacement methods. The objective of this study is to apply a data mining technique to generate frequent itemset patterns of the internet access by users. Data transactions are generated based on the allocated time slots of internet usage. As the public the Internet cluster, different users can use the same single computer; therefore, generating data transaction base on computer IP address is used by many users and may not extract the behavior of users. Association rules are generated using FP-growth algorithm. The frequent itemsets (rules) are then used to implement and extension of LRU cache-replacement technique. The experimental results show that the proposed technique provides promising result and is superior to the base-line cache replacement techniques (i.e. FIFO and LRU).

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Section: Evaluation and Resultsmentioning

confidence: 99%

“…Clustering-based techniques can also be applied for increasing the performance of cache replacement mechanism. Poornalatha G. [7] invent a clustering-based technique that separate data transaction into different groups, association repository [8]. The, pre-fetching web pages are loaded into cached based of the repository information.…”

Section: Introductionmentioning

confidence: 99%

Proxy Server Systems Improvement Using Frequent Itemset Pattern-Based Techniques

Butkote

Phuboon-op²,

Chomphuwiset

2014

Proceedings of the 2nd International Conference on Intelligent Systems and Image Processing 2014

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“…In [4], the author proposes a prediction model based on clustering of web user sessions. Author makes use of various data mining techniques on the logs in the server to predict the next page.…”

Section: Literature Surveymentioning

confidence: 99%

Prefetching of Web Objects For Effective Retrieval Process Through Data Mining Techniques

Singh

Chitra²

2021

Preprint

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With the exponential increase of the internet’s user base, performance enhancing network architectures and algorithms has manifested themselves as a requisite. Algorithms for Prefetching and Caching of Web Objects have been observed to effectively minimize user perceived latency. These algorithms are made use of in architectures limited to a particular user. We can further improve the performance of these algorithms by making use of techniques like data mining. We propose an innovative idea of implementing Prefetching and Caching algorithms in a Clustered Network. This will enable all users in a particular cluster to make use of pre-fetched and cached web objects from all other users. The result of simulations indicates a reduction in web latency, internet traffic, and bandwidth consumed.

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“…They proposed a new modified Markov Model to alleviate the issue of scalability in the number of paths. Poornalatha G et al [19] presented a paper to solve the problem of predicting the next web page to be accessed by the user based on the mining of web server logs that maintains the information of users who access the web site. Section 2, describes the Markov Model and Dynamic Nested Markov Model, Section 3, describes the experimental results and finally section 4 describes the future work and conclusion.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of Models for Predicting User’s Next Request in Web Usage Mining

Nigam¹,

Tokekar²,

Jain³

2015

IJCI

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Prediction of web user behavior is the demand of today competitive edge of World Wide Web. Predicting the next web page is not sufficient, evaluation of prediction models is important because every model have its own pros and cons. Prediction results will be helpful if high prediction accuracy is achieved with minimum complexity, which are depended on the prediction model. Various models and their variations are proposed for predicting the next web page accessed by the web user. Markov model and their variations are found suitable for web prediction. In this research we have evaluated and compared various models for predicting next web page accessed by the web user. Experiments are conducted on three different real datasets.

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Web Page Prediction by Clustering and Integrated Distance Measure

Cited by 6 publications

References 16 publications

Proxy Server Systems Improvement Using Frequent Itemset Pattern-Based Techniques

Proxy Server Systems Improvement Using Frequent Itemset Pattern-Based Techniques

Prefetching of Web Objects For Effective Retrieval Process Through Data Mining Techniques

Evaluation of Models for Predicting User’s Next Request in Web Usage Mining

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