ISBN: 9786200588869 - location predicated gregarious networks: machine learning (6 risultati)

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Condizione: Neu. LOCATION PREDICATED GREGARIOUS NETWORKS | Machine Learning | D. Shanthi | Taschenbuch | 84 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786200588869 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the wide application of location-predicated gregarious networks (LBSNs), Point of interest guidance has become one of the major accommodations in LBSNs. The deportments of users in LBSNs are mainly checking in Point of Interests, and these checking in deportments are influenced by user's demeanor daily habits and his/her friends. 'In convivial networks, convivial influence is often used to avail businesses to magnetize more users'. Each user target utilizers have a different influence on different Point of Interest in gregarious networks. This paper culls the list of Point of Interests with the greatest influence for recommending users. Our aims are to gratify the target user's accommodation need, and simultaneously to promote businesses' locations Point of Interests.This Project defines a point of interest guidance quandary for location promotion. Adscititiously, we utilize sub modular properties to solve the optimization quandary. At last, this Project conducted a comprehensive performance evaluation for our method utilizing two authentic LBSN datasets. 84 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the wide application of location-predicated gregarious networks (LBSNs), Point of interest guidance has become one of the major accommodations in LBSNs. The deportments of users in LBSNs are mainly checking in Point of Interests, and these checking in deportments are influenced by user's demeanor daily habits and his/her friends. 'In convivial networks, convivial influence is often used to avail businesses to magnetize more users'. Each user target utilizers have a different influence on different Point of Interest in gregarious networks. This paper culls the list of Point of Interests with the greatest influence for recommending users. Our aims are to gratify the target user's accommodation need, and simultaneously to promote businesses' locations Point of Interests.This Project defines a point of interest guidance quandary for location promotion. Adscititiously, we utilize sub modular properties to solve the optimization quandary. At last, this Project conducted a comprehensive performance evaluation for our method utilizing two authentic LBSN datasets.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shanthi Dr. D.Dr. D.Shanthi Ph.D (CSE) is working as an Associate Professor for CSE department in CVR College of Engineering, Ibr.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the wide application of location-predicated gregarious networks (LBSNs), Point of interest guidance has become one of the major accommodations in LBSNs. The deportments of users in LBSNs are mainly checking in Point of Interests, and these checking in deportments are influenced by user's demeanor daily habits and his/her friends. 'In convivial networks, convivial influence is often used to avail businesses to magnetize more users'. Each user target utilizers have a different influence on different Point of Interest in gregarious networks. This paper culls the list of Point of Interests with the greatest influence for recommending users. Our aims are to gratify the target user's accommodation need, and simultaneously to promote businesses' locations Point of Interests.This Project defines a point of interest guidance quandary for location promotion. Adscititiously, we utilize sub modular properties to solve the optimization quandary. At last, this Project conducted a comprehensive performance evaluation for our method utilizing two authentic LBSN datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.…