A Novel Clustering Method Using Enhanced Grey Wolf Optimizer and MapReduce

Tripathi, Ashish; Sharma, Kapil; Bala, Manju

doi:10.1016/j.bdr.2018.05.002

Cited by 94 publications

(25 citation statements)

References 29 publications

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“…Blogging has become a trend in today's growing world and with this arises the challenge for providing good content for the given query. The above discussed algorithms are exceptionally encouraging in ranking an incentive of online journals however some confinements still exit on using these calculations [7] for online journals. The ranking values of blogs are selected by ranking algorithm is regularly low.…”

Section: Dmentioning

confidence: 99%

“…To get the accurate results for the query, endeavours have been devised to get a generalized and optimal algorithm for the ranking. There is a need to comprehend the quick expand in the input provided by user [7]. This research helps a portion of famous ranking algorithms which are already present in the market for utilization and their deficiencies.…”

Section: Introductionmentioning

confidence: 99%

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Comparative Analysis of Ranking Algorithms Used On Web

Suri¹,

Gupta²,

Sharma³

2020

AETiC

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With the evolution in technology huge amount of data is being generated, and extracts the necessary data from large volumes of data. This process is significantly complex. Generally the web contains bulk of raw data and the process of converting this data to information mining process can be performed. At whatever point the user places some inquiry on particular web search tool, outcomes are produced with respect to the requests which are dependent on the magnitude of the document created via web information retrieval tools. The results are obtained using calculations and implementation of well written algorithms. Well known web search tools like Google and other varied engines contain their specific manner to compute the page rank, various outcomes are obtained on various web crawlers for a same inquiry because the method for deciding the importance of the sites contrasts among number of algorithm. In this research, an attempt to analyze well-known page ranking calculation on the basis of their quality and shortcomings. This paper places the light on a portion of the extremely mainstream ranking algorithm and attempts to discover a better arrangement that can optimize the time spent on looking through the list of sites.

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Section: Dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Ranking Algorithms Used On Web

Suri¹,

Gupta²,

Sharma³

2020

AETiC

Self Cite

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“…Author also mentioned that technique is also used for clustering of huge data sets. Moreover author also mentioned that the proposed technique could be applicable for some realistic clustering applications having large data sets, such as satellite imaging analysis, twitter data analysis, and video analysis [17].…”

Section: Literature Reviewmentioning

confidence: 99%

Pragmatic Influence of MapReduce in Big Data using Hadoop A literature review

Kaleem¹,

Khuram²

2018

Seventh International Conference on Advances in Computing Electronics and Communication ACEC2018

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A term "Big Data" explain innovative technologies and techniques to store, manage, capture, analyze and distribute large size or petabyte data sets with high acceleration and dynamic structures. Big Data is categorized as semi-structured, unstructured, and structured, which results in an inability of traditional data managerial techniques. Data is produced from numerous resources and reached the system at different rates. This immense amount of data is processed in an efficient, and inexpensive manner, a technique of parallelism is practiced. Big Data parameters which include diversity, scale, and complexity required new techniques, architectures, analytics, and algorithms for the purpose of management of data and the knowledge hidden in it. Hadoop is a famous software platform to make data useful for the purpose of analytics to solve problems and structured the Big Data. Distributed processing is enabled by the help of Hadoop for huge datasets across the bunch of servers. It is specially designed to scale from one to thousands of high computing machines, with high fault tolerance degree.

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“…Furthermore, Mittal et al [11] presented an intelligent gravitation search algorithm-based method to obtain optimal cluster centroids. Sharma et al [12] introduced an enhanced grey wolf optimization-based method for the optimal clustering of the data. Pal et al [13] presented genetic algorithmbased energy-efficient weighted clustering method.…”

Section: Introductionmentioning

confidence: 99%

A new recommendation system using map-reduce-based tournament empowered Whale optimization algorithm

Tripathi

Mittal

Saxena

et al. 2020

Complex Intell. Syst.

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In the era of Web 2.0, the data are growing immensely and is assisting E-commerce websites for better decision-making. Collaborative filtering, one of the prominent recommendation approaches, performs recommendation by finding similarity. However, this approach fails in managing large-scale datasets. To mitigate the same, an efficient map-reduce-based clustering recommendation system is presented. The proposed method uses a novel variant of the whale optimization algorithm, tournament selection empowered whale optimization algorithm, to attain the optimal clusters. The clustering efficiency of the proposed method is measured on four large-scale datasets in terms of F-measure and computation time. The experimental results are compared with state-of-the-art map-reduce-based clustering methods, namely map-reduce-based K-means, map-reduce-based bat algorithm, map-reduce-based Kmeans particle swarm optimization, map-reduce-based artificial bee colony, and map-reduce-based whale optimization algorithm. Furthermore, the proposed method is tested as a recommendation system on the publicly available movie-lens dataset. The performance validation is measured in terms of mean absolute error, precision and recall, over a different number of clusters. The experimental results assert that the proposed method is a permissive approach for the recommendation over large-scale datasets.

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A Novel Clustering Method Using Enhanced Grey Wolf Optimizer and MapReduce

Cited by 94 publications

References 29 publications

Comparative Analysis of Ranking Algorithms Used On Web

Comparative Analysis of Ranking Algorithms Used On Web

Pragmatic Influence of MapReduce in Big Data using Hadoop A literature review

A new recommendation system using map-reduce-based tournament empowered Whale optimization algorithm

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