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To predict the web users navigation with the help of Web Usage Mining techniques. This book primarily focuses on real world applicability of a new Web page Recommendation approach using both Weighted Sequential patterns and Markov probabilistic model. To find the Weighted Sequential patterns, the existing PrefixSpan algorithm has been modified by incorporating the weightage constraints such as spending time and recent visiting. Once the weighted sequential patterns are identified, a Patricia-trie based tree is constructed. Finally from the constructed pattern tree, the recommendation of web pages to the current users is done with the help of Markov probabilistic model. This model enables the reasoning and computation as intractable to identify the future access web pages based on the user past browsing interests.
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Web Page Recommendation Approach Using Weighted Sequential Patterns
Editore:
LAP LAMBERT Academic Publishing Nov 2021, 2021
ISBN 10: 6204717634
ISBN 13: 9786204717630
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -To predict the web users navigation with the help of Web Usage Mining techniques. This book primarily focuses on real world applicability of a new Web page Recommendation approach using both Weighted Sequential patterns and Markov probabilistic model. To find the Weighted Sequential patterns, the existing PrefixSpan algorithm has been modified by incorporating the weightage constraints such as spending time and recent visiting. Once the weighted sequential patterns are identified, a Patricia-trie based tree is constructed. Finally from the constructed pattern tree, the recommendation of web pages to the current users is done with the help of Markov probabilistic model. This model enables the reasoning and computation as intractable to identify the future access web pages based on the user past browsing interests. 188 pp. Englisch. Codice articolo 9786204717630
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Web Page Recommendation Approach Using Weighted Sequential Patterns
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204717634
ISBN 13: 9786204717630
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Da: moluna, Greven, Germania
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: K SuneethaI have an insatiable desire for addressing the Data Mining problems. I believe that there are many possible avenues of investigation which includes genetic algorithms and programming, support vector machines, clustering te. Codice articolo 533956063
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Web Page Recommendation Approach Using Weighted Sequential Patterns
Editore:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204717634
ISBN 13: 9786204717630
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Web Page Recommendation Approach Using Weighted Sequential Patterns | Suneetha K | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204717630 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 120909333
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Web Page Recommendation Approach Using Weighted Sequential Patterns
Editore:
LAP LAMBERT Academic Publishing Nov 2021, 2021
ISBN 10: 6204717634
ISBN 13: 9786204717630
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -To predict the web users navigation with the help of Web Usage Mining techniques. This book primarily focuses on real world applicability of a new Web page Recommendation approach using both Weighted Sequential patterns and Markov probabilistic model. To find the Weighted Sequential patterns, the existing PrefixSpan algorithm has been modified by incorporating the weightage constraints such as spending time and recent visiting. Once the weighted sequential patterns are identified, a Patricia-trie based tree is constructed. Finally from the constructed pattern tree, the recommendation of web pages to the current users is done with the help of Markov probabilistic model. This model enables the reasoning and computation as intractable to identify the future access web pages based on the user past browsing interests.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 188 pp. Englisch. Codice articolo 9786204717630
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Web Page Recommendation Approach Using Weighted Sequential Patterns
Editore:
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204717634
ISBN 13: 9786204717630
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - To predict the web users navigation with the help of Web Usage Mining techniques. This book primarily focuses on real world applicability of a new Web page Recommendation approach using both Weighted Sequential patterns and Markov probabilistic model. To find the Weighted Sequential patterns, the existing PrefixSpan algorithm has been modified by incorporating the weightage constraints such as spending time and recent visiting. Once the weighted sequential patterns are identified, a Patricia-trie based tree is constructed. Finally from the constructed pattern tree, the recommendation of web pages to the current users is done with the help of Markov probabilistic model. This model enables the reasoning and computation as intractable to identify the future access web pages based on the user past browsing interests. Codice articolo 9786204717630
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