By Matthias Eichstädt
ISBN-10: 3663104028
ISBN-13: 9783663104025
ISBN-10: 3824421259
ISBN-13: 9783824421251
A new breed of knowledge dissemination platforms known as webcasting or push platforms has attracted huge, immense realization within the net undefined. Push expertise stems from a very easy suggestion. instead of requiring clients to explicitly request the data that they wish, facts could be despatched to clients with no need them particularly ask for it. A push process instantly provides details content material akin to advertisements or buying goods in response to the user`s curiosity. Matthias Eichstädt introduces novel thoughts for matching person curiosity profiles opposed to varied details content material in huge scale webcasting systems.
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Additional info for Internet Webcasting: Generating and Matching Profiles
Example text
Scalability, adaptability and high performance are the three corner stones for the parallel algorithms. In addition, the following four requirements are critical to the applicability of our algorithms. First, the load must be distributed among the processors automatically. Overloaded processors must be able to share the load with other processors dynamically. Second, the parallel matehing algorithms have to support lively changes in the user profiles because short term interest profiles change frequently.
PARALLEL PROFILE MATCHING ALGORITHMS 55 sized subgraphs. At each step, each seed tries to include its neighboring nodes into its components; conflicts are resolved by making edges local to each component. For better partitions, the k seeds should be pairwisely "far" away from each other. 3) Two subsets are "close" if their overlap ratio is large. We can choose k mutually faraway seeds as follows: Let S1 be the set with the largest weight. For i = 2 to k, let Si be the set with the largest weight among those whose overlap ratio with G 1 , ...
2 describes the evaluation, upward and downward propagation processes. Routine Evaluation iterates through all the leaf nodes in a chosen order, evaluating a node's truth value when necessary and invoking the Upward_Propagation routine, which recursively propagates a truth value upwards. The DownwardYropagation routine recursively traverses downwards and assigns the DontCare value to nodes whose parents have known truth value. Note that the propagation algorithms are linear because each node can be propagated at most once.
Internet Webcasting: Generating and Matching Profiles by Matthias Eichstädt
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