http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Yufei Tao (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
Range Aggregation With Set Selection
Yufei Tao,Cheng Sheng,Chin-Wan Chung,Jong-Ryul Lee IEEE 2014 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERIN Vol.26 No.5
<P>In the classic range aggregation problem, we have a set S of objects such that, given an interval I, a query counts how many objects of S are covered by I. Besides COUNT, the problem can also be defined with other aggregate functions, e.g., SUM, MIN, MAX and AVERAGE. This paper studies a novel variant of range aggregation, where an object can belong to multiple sets. A query (at runtime) picks any two sets, and aggregates on their intersection. More formally, let S<SUB>1</SUB>,...,S<SUB>m</SUB> be m sets of objects. Given distinct set ids i, j and an interval I, a query reports how many objects in S<SUB>i</SUB> ∩ S<SUB>j</SUB> are covered by I. We call this problem range aggregation with set selection (RASS). Its hardness lies in that the pair (i, j) can have (<SUB>2</SUB><SUP>m</SUP>) choices, rendering effective indexing a non-trivial task. 2 The RASS problem can also be defined with other aggregate functions, and generalized so that a query chooses more than 2 sets. We develop a system called RASS to power this type of queries. Our system has excellent efficiency in both theory and practice. Theoretically, it consumes linear space, and achieves nearly-optimal query time. Practically, it outperforms existing solutions on real datasets by a factor up to an order of magnitude. The paper also features a rigorous theoretical analysis on the hardness of the RASS problem, which reveals invaluable insight into its characteristics.</P>
-
Tao, Yufei Korean Institute of Information Scientists and Eng 2013 Journal of Computing Science and Engineering Vol.7 No.3
This invited paper introduces results on Web science and technology obtained during work with the Korea Advanced Institute of Science and Technology. In the first part, we discuss algorithms for exploring the deep Web, which refers to the collection of Web pages that cannot be reached by conventional Web crawlers. In the second part, we discuss sorting algorithms on the MapReduce system, which has become a dominant paradigm for massive parallel computing.
-
Yufei Tao 한국정보과학회 2013 Journal of Computing Science and Engineering Vol.7 No.3
This invited paper introduces results on Web science and technology obtained during work with the Korea Advanced Institute of Science and Technology. In the first part, we discuss algorithms for exploring the deep Web, which refers to the collection of Web pages that cannot be reached by conventional Web crawlers. In the second part, we discuss sorting algorithms on the MapReduce system, which has become a dominant paradigm for massive parallel computing.
-
Cost-Based Predictive Spatiotemporal Join
Wook-Shin Han,Jaehwa Kim,Byung Suk Lee,Yufei Tao,Rantzau, R.,Markl, V. IEEE 2009 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERIN Vol.21 No.2
<P>A predictive spatiotemporal join finds all pairs of moving objects satisfying a join condition on future time and space. In this paper, we present CoPST, the first and foremost algorithm for such a join using two spatiotemporal indexes. In a predictive spatiotemporal join, the bounding boxes of the outer index are used to perform window searches on the inner index, and these bounding boxes enclose objects with increasing laxity over time. CoPST constructs globally tightened bounding boxes 'on the fly' to perform window searches during join processing, thus significantly minimizing overlap and improving the join performance. CoPST adapts gracefully to large-scale databases, by dynamically switching between main-memory buffering and disk-based buffering, through a novel probabilistic cost model. Our extensive experiments validate the cost model and show its accuracy for realistic data sets. We also showcase the superiority of CoPST over algorithms adapted from state-of-the-art spatial join algorithms, by a speedup of up to an order of magnitude.</P>
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
