Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy...Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.展开更多
We discuss some methods for constructing recommender systems. An important feature of the methods studied here is that we assume the availability of a description, representation, of the objects being considered for r...We discuss some methods for constructing recommender systems. An important feature of the methods studied here is that we assume the availability of a description, representation, of the objects being considered for recommendation. The approaches studied here differ from collaborative filtering in that we only use preferences information from the individual for whom we are providing the recommendation and make no use the preferences of other collaborators. We provide a detailed discussion of the construction of the representation schema used. We consider two sources of information about the users preferences. The first are direct statements about the type of objects the user likes. The second source of information comes from ratings of objects which the user has experienced.展开更多
基金Supported by the National Natural Science Foundation of China(No.61379057,61073186,61309001,61379110,61103202)Doctoral Fund of Ministry of Education of China(No.20120162130008)the National Basic Research Program of China(973 Program)(No.2014CB046305)
文摘Opportunistic networks are random networks and do not communicate with each other among respective communication areas.This situation leads to great difficulty in message transfer.This paper proposes a reducing energy consumption optimal selection of path transmission(OSPT) routing algorithm in opportunistic networks.This algorithm designs a dynamic random network topology,creates a dynamic link,and realizes an optimized selected path.This algorithm solves a problem that nodes are unable to deliver messages for a long time in opportunistic networks.According to the simulation experiment,OSPT improves deliver ratio,and reduces energy consumption,cache time and transmission delay compared with the Epidemic Algorithm and Spray and Wait Algorithm in opportunistic networks.
文摘We discuss some methods for constructing recommender systems. An important feature of the methods studied here is that we assume the availability of a description, representation, of the objects being considered for recommendation. The approaches studied here differ from collaborative filtering in that we only use preferences information from the individual for whom we are providing the recommendation and make no use the preferences of other collaborators. We provide a detailed discussion of the construction of the representation schema used. We consider two sources of information about the users preferences. The first are direct statements about the type of objects the user likes. The second source of information comes from ratings of objects which the user has experienced.
