Retrieval of Trending Keywords in a Peer-to-Peer Micro-blogging OSN

被引：1
|
作者：
Asthana, H. [1 ]
Cox, Ingemar [1 ]
机构：
[1] UCL, Dept Comp Sci, Gower St, London WC1E 6BT, England
来源：
PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13) | 2013年
关键词：
Unstructured Peer-to-Peer Network; Micro-blogging; Social Network; Trending Keywords;
D O I：
10.1145/2505515.2507862
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We investigate the problem of identifying trending information in a peer-to-peer micro-blogging online social network. In a distributed decentralized environment, the participating nodes do not have access to global statistics such as the frequencies of the keywords and the information creation rate. We propose a two step solution. First, nodes make a local estimate of the frequency of keywords in the network based on their local information. At each iteration a subset of nodes collect this information from a small subset of random nodes in the network and aggregate the results. The most frequently occurring keywords are identified. In the second step, a node requests another small random subset of nodes to identify when, in the recent past, the more frequently occurring keywords were seen in micro-blogs. Once again this information is aggregated the fraction of time within a consecutive period that keywords were encountered is calculated. If this fraction, referred to as the trending fraction, is close to 1, then the keyword is predicted to be trending. A simulation on a network of 10,000 nodes shows that the solution is capable of detecting multiple trending keywords with a moderate increase in bandwidth.
引用
收藏
页码：1229 / 1232
页数：4
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