Measuring and enhancing the social connectivity of UGC video systems: a case study of YouKu
Proceedings of the Nineteenth International Workshop on Quality of Service
FAST: Friends Augmented Search Techniques - System Design & Data-Management Issues
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Expertise ranking using activity and contextual link measures
Data & Knowledge Engineering
Semi-structured semantic overlay for information retrieval in self-organizing networks
Proceedings of the 21st international conference companion on World Wide Web
| Hi-index | 14.98 |
Previous multikeyword search in DHT-based P2P systems often relies on multiple single keyword search operations, suffering from unacceptable traffic cost and poor accuracy. Precomputing term-set-based index can significantly reduce the cost but needs exponentially growing index size. Based on our observations that 1) queries are typically short and 2) users usually have limited interests, we propose a novel index pruning method, called TSS. By solely publishing the most relevant term sets from documents on the peers, TSS provides comparable search performance with a centralized solution, while the index size is reduced from exponential to the scale of O(nlog(n)). We evaluate this design through comprehensive trace-driven simulations using the TREC WT10G data collection and the query log of a major commercial search engine.