报告题目：大数据集合查询问题研究
时间：2016年3月30日周三14:30
地点：主楼四区305
杨仝，2010-2013，就读于清华大学计算机计算机网络专业。2013-2014年到中科院计算所客座访问。2015年进入北京大学信息学院计算机系网络所，研究方向为网络与大数据。发表多篇著名国际会议论文，包括sigcomm、vldb、icnp、icdcs等。
abstract: set queries are fundamental operations in computer systems and applications. this paper addresses the fundamental problem of designing a probabilistic data structure that can quickly process set queries using a small amount of memory. we propose a shifting bloom filter (shbf) framework for representing and querying sets. we demonstrate the effectiveness of shbf using three types of popular set queries: membership, association, and multiplicity queries. the key novelty of shbf is on encoding the auxiliary information of a set element in a location offset. in contrast, prior bf based set data structures allocate additional memory to store auxiliary information. we conducted experiments using real-world network traces, and results show that shbf significantly advances the state-of-the-art on all three types of set queries.
该论文研究大数据处理中最基础的大集合查询问题，主要包括集合包含、多集合、元素出现次数三个关键问题。该论文未发表之前的网络版已经被哈佛大学计算机副系主任引用。
