Distributed multimedia access system and method
First Claim
1. A computer-readable storage medium which stores instructions which, when executed by a computer, enables a distributed multimedia access system applied in a P2P network having a plurality of nodes and a request node, a user located at the request node inputting preference parameters to the P2P network to obtain a peer list that contains some of the plurality of nodes, to:
- designate some of the nodes in the peer list that are at shorter distances from the request node than the others of the nodes as first node candidates and performs a random walk process on the first node candidates to search the peer list for second node candidates;
calculate similarity between the preference parameters of the request node and preference parameters of the first and second node candidates to obtain similarity values;
select some of the first and second node candidates that have similarity values smaller than similarity values of the others of the first and second node candidates as buddies for the user located at the request node; and
establish and store a buddy list that contains the buddies;
wherein the node candidates store objects related to the preference parameters input by users located at the node candidates;
wherein when the preference parameters are determined through attributes of the objects input by the user located at the request node, the similarity calculation module lets object (ci) represent the objects input by the user ci located at the request node and be defined as a vector of weights ({right arrow over (wi)})=(wik1, wik2, . . . , wikn), wherein the weight wikn represents the user ci'"'"'s preference for the objects and is described by keyword kn, the distributed multimedia access system is further enabled to perform the following calculation;
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Abstract
A distributed media access system and method. The method includes making each of a plurality nodes in a P2P network designate at least one nearest neighbors as a first node candidate and perform at least one random walk to obtain a second node candidate according to the peer list; calculating user preferences of the request node and user preferences of the first and second node candidates according to the first and second node candidates and the preference parameters corresponding to the first and second node candidates so as to obtain a plurality of similarity values; selecting the more similar candidate as buddies of user of the node according to the calculated similarity values; and establishing a buddy list according to the buddies of user and storing the buddy list such that the P2P network can quickly find buddies of the node through the buddy list.
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Citations
17 Claims
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1. A computer-readable storage medium which stores instructions which, when executed by a computer, enables a distributed multimedia access system applied in a P2P network having a plurality of nodes and a request node, a user located at the request node inputting preference parameters to the P2P network to obtain a peer list that contains some of the plurality of nodes, to:
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designate some of the nodes in the peer list that are at shorter distances from the request node than the others of the nodes as first node candidates and performs a random walk process on the first node candidates to search the peer list for second node candidates; calculate similarity between the preference parameters of the request node and preference parameters of the first and second node candidates to obtain similarity values; select some of the first and second node candidates that have similarity values smaller than similarity values of the others of the first and second node candidates as buddies for the user located at the request node; and establish and store a buddy list that contains the buddies; wherein the node candidates store objects related to the preference parameters input by users located at the node candidates; wherein when the preference parameters are determined through attributes of the objects input by the user located at the request node, the similarity calculation module lets object (ci) represent the objects input by the user ci located at the request node and be defined as a vector of weights ({right arrow over (wi)})=(wik1, wik2, . . . , wikn), wherein the weight wikn represents the user ci'"'"'s preference for the objects and is described by keyword kn, the distributed multimedia access system is further enabled to perform the following calculation; - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A distributed multimedia access method applied in a P2P network having a plurality of nodes and a request node, a user located at the request node inputting preference parameters to the P2P network to obtain a peer list that contains some of the nodes, the method comprising the following steps of:
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(1) designating some of the nodes in the peer list that are at shorter distances from the request node than the others of the nodes as first node candidates and performing a random walk process on the first node candidates to search the peer list for second node candidates; (2) calculating similarity between the preference parameters of the request node and preference parameters of the first and second node candidates to obtain similarity values; (3) selecting some of the first and second node candidates that have similarity values smaller than similarity values of the others of the first and second node candidates as buddies for the user located at the request node; and (4) establishing a buddy list that contains the buddies; wherein the node candidates store objects related to the preference parameters input by users located at the node candidates; wherein when the preference parameters are determined through attributes of the objects input by the user of the request node, object(ci) represents the objects input by the user ci of the node, which is defined as a vector of weights ({right arrow over (wi)})=(wik1, wik2, . . . , wikn), wherein weight wikn re resents the user ci'"'"'s reference for the objects described by keyword kn, wikn is calculated through the following equation; - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
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Specification