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Efficient Keyword Searching in Large-scale Social Network Service

Efficient Keyword Searching in Large-scale Social Network Service

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Efficient Keyword Searching in Large-scale Social Network Service

†Different from traditional Web searching, the relevant information for a Social Network System (SNS) is commonly the content from his/her friends. Such a difference makes content indexing extremely difficult for an Online Social Network (OSN) search system because every user has an individual view during searching. Building such a per-user view index over existing SNS Key-Value stores raises a large amount of communication cost due to the complex interconnections among OSN users, making the search system unscalable. To address the problem, we propose a novel protocol called summary index to support keyword searching. In the protocol, each user keeps a directory of the succinct summaries of his/her neighbors, and checks these summaries for potential hits before sending any queries. Two factors contribute to the low overhead of our design: the summary index representations are memory efficient, and the summary dissemination for index updating is communication efficient. First, we design an incremental scalable Bloom filter for summarizing the content constantly generated by a neighbor of a user. For an issued query by a user, the search system first checks against the summary index for a userís neighbor to predict the neighbors likely having desired content.



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  • Model: PROJ5219
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Tuesday 13 September, 2016.

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