Finding Frequent Trajectories of Dynamic Objects - 6 Angebote vergleichen
Bester Preis: € 79,23 (vom 28.06.2020)1
Finding Frequent Trajectories of Dynamic Objects
~EN NW
ISBN: 9783639859720 bzw. 3639859723, vermutlich in Englisch, Scholar'S Press, neu.
Lieferung aus: Deutschland, Lieferzeit 1-3 Werktage, Versandkostenfrei innerhalb von Deutschland.
Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach.
Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach.
2
Finding Frequent Trajectories of Dynamic Objects
~EN NW AB
ISBN: 9783639859720 bzw. 3639859723, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, neu, Hörbuch.
Lieferung aus: Niederlande, Lieferzeit: 5 Tage, zzgl. Versandkosten.
Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach.
Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach.
3
Finding Frequent Trajectories of Dynamic Objects
~EN PB NW
ISBN: 9783639859720 bzw. 3639859723, vermutlich in Englisch, SPS, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Finding Frequent Trajectories of Dynamic Objects: Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach. Englisch, Taschenbuch.
Finding Frequent Trajectories of Dynamic Objects: Data mining has attracted a great deal of attention not only the information industry and in society but also the commuters, electronic routing and players as a whole in recent years, due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. In this research, we develop a class of five novel and efficient methods for mining frequent trajectories from huge trajectory databases. Initial approach is by modifying the Apriori algorithm for finding frequent trajectory patterns. Secondly the frequent trajectory patterns are obtained by modifying the frequent pattern tree algorithm. Thirdly the longest frequent trajectories are obtained by modifying the association mining approaches. Fourth approach is that frequent trajectories of moving objects was found by a variable block box method. Fifth one is for finding the frequent trajectories of dynamic objects by clustering and sequential pattern mining approach. Englisch, Taschenbuch.
4
Finding Frequent Trajectories of Dynamic Objects
~EN PB NW
ISBN: 3639859723 bzw. 9783639859720, vermutlich in Englisch, SPS, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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Finding Frequent Trajectories of Dynamic Objects Arthur A. Shaw Author
~EN PB NW
ISBN: 9783639859720 bzw. 3639859723, vermutlich in Englisch, KS Omniscriptum Publishing, Taschenbuch, neu.
Lieferung aus: Vereinigte Staaten von Amerika, Lagernd, zzgl. Versandkosten.
Finding Frequent Trajectories of Dynamic Objects,Arthur A Shaw.
Finding Frequent Trajectories of Dynamic Objects,Arthur A Shaw.
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